Sargur Srihari

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Curriculum vitae

Sargur N. Srihari

SUNY Distinguished Professor University at Buffalo, The State University of New York

Department of Computer Science and Engineering Buffalo, NY 14260, USA

Mobile: (716) 984-7258 E-mail: srihari@buffalo.edu

April 16, 2020

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Curriculum vitae

Sargur N. Srihari

Contents

1 Personal Information ..................................................................................................................3 2 Education ...................................................................................................................................3 3 Academic Positions ....................................................................................................................3 4 Advisory Positions .....................................................................................................................3 5 Honors and Awards ....................................................................................................................4 6 Professional Activities ...............................................................................................................5 7. Research Impact. .…………………………………………………………..……………….6 8. Teaching Impact. …………………………………………………………………….………8 9. Publications ................................................................................................................................9 9.1 Journal Articles ...................................................................................................................9 9.2 Books……………………………………………………………………………………..11 9.3 Book Chapters……………………………………………………………………………12 9.4 Papers in Conference Proceedings...……………………………………………………...13 9.5 Patents……………………………………………………………………………………24 9.6 Abridged Papers/Abstracts ................................................................................................24 10. Grants and Contracts as Principal Investigator………………………………………………26 11. Doctoral Dissertations Supervised ..........................................................................................29 12. Invited Lectures and Conference Presentations……………………………………………. 31

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Sargur N. Srihari 1. PERSONAL Born: May 7, 1950 Contact: Dept. of CSE, University at Buffalo, Davis Hall, Buffalo NY 14260 Email: srihari@cedar.buffalo.edu Phone: 716-645-6162 2. EDUCATION Ph.D., 1976: Computer & Information Science, The Ohio State University, Columbus, Ohio M.S., 1972: Computer & Information Science, The Ohio State University, Columbus, Ohio B.E., 1970: Electrical Communication Engineering, Indian Institute of Science, Bangalore, India B.Sc., 1967: Physics & Mathematics, Bangalore University, Bangalore, India 3. ACADEMIC POSITIONS 2020: Satish Dhawan Visiting Chair Professor, Indian Institute of Science, Bangalore, India 2018: Rukmini Gopalakrishnachar Chair Professor, Indian Institute of Science, Bangalore, India 1997-Present: SUNY Distinguished Professor, University at Buffalo, The State University of New York

Department of Computer Science and Engineering, Adjunct Professor, Department of Electrical Engineering, Adjunct Professor, Department of Biostatistics

1991-Present: Director, Center of Excellence for Document Analysis and Recognition (CEDAR) 1991-1997: Pattern Recognition Professor, Computer Science, SUNY at Buffalo 1987-1991: Professor, Computer Science, SUNY at Buffalo 1987-1988: Acting Chairman, Computer Science, SUNY at Buffalo 1982-1987: Associate Professor, Computer Science, SUNY at Buffalo 1978-1982: Assistant Professor, Computer Science, SUNY at Buffalo 1976-1978: Assistant Professor, Computer Science, Wayne State University, Detroit, MI 1970-1975: Research Assistant, Computer and Inform Sci, The Ohio State University Columbus, O 4. ADVISORY POSITIONS National (Government) 2014-2018: Member City of Houston Forensics Technology Advisory Group 2015-2018: Member Expert Working Group on Human Factors in Handwriting Examination, NIST/NIJ 2008-2011: Member Expert Working Group on Human Factors in Latent Print Analysis, NIST/NIJ 2007-2008: Member National Academy of Sciences/National Research Council Committee on Identifying the Needs of the Forensic Science Community 2002-2007: Member, Board of Scientific Counselors, National Library of Medicine Corporate 2005-2014: Member, Board of Janya, Inc. 2000-2005: Member, Technical Advisory Board, Cymfony, Inc. 1996-Present: Chairman, Cedartech, Inc. University (External)

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2010-2012: External Evaluator, School of Computer Science, University of Putra, Malaysia 2006: Queens College, City University of New York, Comp. Science Department Evaluation Committee 5. HONORS AND AWARDS Professional Societies Outstanding Achievements Award, ICDAR-IAPR, 2011 Fellow, International Association for Pattern Recognition, 1996 Fellow, Institute of Electrical and Electronics Engineers, 1994 Fellow, Institution of Electronics and Telecommunications Engineers, India, 1989 University Awards University at Buffalo Excellence in Graduate Mentoring Award, 2018 SUNY Outstanding Inventor Award, SUNY Research Foundation, SUNY, 2002 Distinguished Alumnus, College of Engineering, The Ohio State University, 1999 New York State United University Professions Excellence Award for 1990-91 National Merit Scholarship, India (Awarded to B.Sc rank holders), 1967-70 Paper Best Presentation Paper Award, 7th Intl Conf. Doc. Analysis and Recog., Edinburgh, Scotland, 2003

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6. PROFESSIONAL ACTIVITIES CONFERENCES AND WORKSHOPS General Chair, International Workshop on Computational Forensics, National Academy of Sciences Keck Center, Washington D.C., 2008 General Chair, Eighth Intl.. Workshop on Frontiers in Handwriting Recognition, Niagara-on-the-lake, Ontario, Canada, 2002 General Chair, Fifth Intl. Conference on Document Analysis and Recognition, Bangalore, India, 1999 General Co-chair, Third Intl. Conference on Document Analysis & Recognition, Montreal, Canada, 1995 General Chair, Third Intl. Workshop on Frontiers of Handwriting Recognition, Buffalo, NY, 1993 Program Co-chair, First Intl. Conference on Document Analysis & Recognition, St. Malo, France 1991 SOCIETIES Publicity and Publications Committee Chair and Web Editor, Int. Assoc. for Pattern Recognition (IAPR), 2002--2008 Chairman, Technical Committee on Text Processing (TC-11), International Association of Pattern Recognition 1986-1988 Member--Association for Computing Machinery, American Association for Artificial Intelligence, Institute of Electrical and Electronics Engineers, American Association for the Advancement of Science EDITORSHIPS Member of Editorial Board, Frontiers of Computer Science in China, 2007-2010 Associate Editor, Pattern Recognition Journal, 1982-2002 Editor-in-Chief, International Journal of Document Analysis and Recognition, 1997-2004 International Journal of Pattern Recognition and Artificial Intelligence, 1992-1996

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7. RESEARCH IMPACT STATEMENT Srihari’s research career spans five decades. A career focusing on artificial intelligence, beginning with statistical pattern recognition and culminating in deep learning. He has contributed to the methodology of these fields, while also drawing motivation from two application areas of broad societal interest:

• Document image analysis • Forensics.

Srihari’s first major papers were in representation of three-dimensional images, such as those produced in computing tomography. His ACM Computing Surveys article on the topic was influential, with citations even to this day in 3-D printing. His work with his first PhD student , on hyper-quad trees for multi-dimensional images, was published in CACM and featured on its cover Srihari’s first external research funding was from the National Science Foundation (NSF). It was for the study of the role of context in recognizing text. At its successful conclusion (resulting in a paper in IEEE-PAMI), he approached the United States Postal Service (USPS) for funding as there was potential use of his research in address reading machines. USPS provided him with a small ($100K) grant to study existing printed address reading technology. This eventually led to large-scale funding from the United States Postal Service for several ancillary projects:

• Determining address blocks on letters, flats and irregular parcels, • Reading poor quality printed addresses and • Reading handwritten addresses.

This work culminated in his group being recognized as a USPS Center of Excellence for Document Analysis and Recognition, known as CEDAR. The center’s work eventually involved more than a dozen projects and more than a hundred of graduate students and a dozen full-time research staff, with funding exceeding $60 million over 25 years. The work of CEDAR received worldwide attention. Among the more impactful work at CEDAR were:

• Handwritten digit recognition was recognized as the fruit-fly of AI and machine learning. The USPS data set collected in Buffalo was succeeded by the more widely used MNIST digits.

• Document analysis and recognition was recognized as an important application area of pattern recognition and machine learning, spawning several conferences and a journal.

• The first large-scale handwritten address interpretation systems in the world was deployed by the USPS, eventually allowing reading over 90% of the handwritten US mail. This work is exhibited in the National Postal Museum in Washington DC. The work received worldwide attention including features on Beyond 2000(Australia), CNN, ABC News with Peter Jennings, Discovery Channel, etc.

• Name and address block reader (NABR) or the Internal Revenue Service (to read off of 1040EZ) • Handwritten address readers for UK Royal Mail and for Australia Post.

Over the next decade, Srihari turned his research focus to forensic science. The National Institute of Justice (NIJ) contacted him about the need for a scientific basis for continuing to allow impression evidence such as handwriting to be presented as evidence in the courts. Srihari’s first effort with funding from the NIJ was on quantifying the individuality of handwriting. A resulting paper in the Journal of Forensic Sciences was hailed by the community of questioned document examiners as providing a basis for admitting handwriting evidence in several cases. Srihari testified in several “Daubert hearings”,

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including at the federal level, as to whether handwriting could be admitted as evidence. The handwriting work led to the first automated system, known as CEDAR-FOX—for determining whether two handwritten samples came from the same or different writer. It was issued a United States Patent. Srihari formed a company CEDARTECH to commercialize CEDAR-FOX. Srihari and CEDAR-FOX were featured in a NOVA episode on PBS regarding the Lindbergh kidnapping. Srihari extended his studies on comparing handwriting to comparing fingerprints and footwear prints. As a consequence of his forensic work, Srihari was invited to serve on a prestigious National Academy of Sciences Committee on Identifying the Needs of the Forensic Science Community. Srihari was the only computer scientist on this committee, which was headed by a Federal Appeals Court Judge Harry Edwards. The report has had a major impact on courts worldwide and received a prestigious award by the Innocence Project.

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8. TEACHING IMPACT STATEMENT Srihari has been teaching courses in artificial intelligence, pattern recognition and machine learning over four decades. He has developed an extensive set of lecture slides covering several topics on

• Introductory Machine Learning. • Deep Learning • Probabilistic Graphical Models

His lecture slides and videos are widely used in courses around the world. All three courses are listed in "Ten Free Top-Notch Machine Learning Courses" of the influential site KDNuggets. Srihari has conducted numerous tutorials on the use of CEDAR-FOX, a software system for handwriting comparison. This software was widely known to the forensic community and a several tutorials were conducted, including one organized by the National Forensic Science Technology Center. Some of the others were at different meetings of the Questioned Document Examination community (ASQDE, SWAFDE, etc). Srihari’s current teaching efforts are focused on integrating the avalanche of research being produced in deep learning—available in books, papers and blogs. He is currently video recording his explanation of topics in deep learning on Zoom and livestreaming on Facebook. His recent lectures on topics such as attention models and recommender systems have received over a thousand views each. Srihari has served as principal advisor to 41 PhD students and hundreds of MS students. The most financially successful of these has been

• Yanhong Robin Li, who founded the search engine giant Baidu and became the first Chinese billionaire.

Among the more notable of Srihari’s PhD students are • Tin Kam Ho, who invented Random Forests, an important classification method. She served as

Distinguished Scientist at Lucent Bell Labs. • Jonathan Hull, who holds a record number of United States Patents (over a hundred). He served

for several decades as a principal research scientist at Ricoh Silicon Valley • Venugopal Govindaraju, who is a Distinguished Professor and Vice President of Research at the

University at Buffalo • Dar-Shyang Lee, who has made important contributions to deep learning at Google

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9. PUBLICATIONS The following are a list of about 400 published papers in the pattern recognition, machine learning and artificial intelligence literature. Google Scholar indicates over 19,000 citations with a h-index of 62. 9.1 Journal Articles 1. S. N. Srihari, L. Meng and L. Hanson, “Development of Handwriting Individuality in Children,” Journal of Forensic

Sciences, October 2016. 2. A. Farasat, A. Nikolaev, S. N. Srihari and R.Blair, “Probabilistic Graphical Models in Modern Social Network

Analysis,” Social Network Analysis and Mining, 5(1), 62:1-62:18, Springer, 2015. 3. Y. Tang and S. N. Srihari, “Likelihood Ratio Estimation in Forensic Identification using Similarity and Rarity,” Pattern

Recognition, 47(3), 945-958, 2014. 4. S. N. Srihari and K. Singer. “Role of Automation in the Examination of Handwritten Items,” Pattern Recognition,

47(3), 1083-1095, 2014. 5. Y. Tang, H. Kasiviswanathan and S. N. Srihari, An efficient clustering-based retrieval framework for real crime scene

footwear marks. International Journal of Granular Computing, Rough Sets and Intelligent Systems, 2012; 2 (4): 327-360.

6. S. N. Srihari, “Computing the Scene of a Crime,” IEEE Spectrum (Invited paper), 12(47), 2010: 38-43. 7. S. N. Srihari and H. Srinivasan, "Comparison of ROC and Likelihood Decision Methods in Automatic Fingerprint

Verification," International Journal of Pattern Recognition and Artificial Intelligence, 22(3), 2008: 535-553. 8. S. N. Srihari, C. Huang, H. Srinivasan and V. Shah, "On the Discriminability of the Handwriting of Twins," Journal of

Forensic Sciences, 53(2), 2008: 430-446. 9. S. N. Srihari, J. Collins, R. K. Srihari, H. Srinivasan, S. Shetty and J. Brutt-Giffler, “Automatic scoring of short

handwritten essays in reading comprehension tests,” Artificial Intelligence, 172 (2008): 300-324. 10. S. N. Srihari, H. Srinivasan, and G. Fang, "Discriminability of the Fingerprints of Twins," Journal of Forensic

Identification, 58(1), 2008: 109-127. 11. S. N. Srihari, X. Yang and G. R. Ball, "Offline Chinese Handwriting Recognition: An Assessment of Current

Technology," Frontiers of Computer Science in China, 1(2), 2007: 137-155. 12. S. N. Srihari, H. Srinivasan and K. Desai, "Questioned Document Examination using CEDAR-FOX,"Journal of

Forensic Document Examination, 18, 2007, pp. 1-20. 13. S. N. Srihari, H. Srinivasan, C. Huang and S. Shetty, "Spotting Words in Latin, Devanagari and Arabic Scripts," Vivek:

Indian Journal of Artificial Intelligence, 16(3), 2006: 2-9. 14. B. Zhang and S. N. Srihari, "Handwriting Identification using MultiScale Features," Journal of Forensic Document

Examination, Vol. 16, Fall 2004: 1-20. 15. M. K. Kalera, S. N. Srihari and A. Xu, "Offline signature verification and identification using distance statistics,"

International Journal of Pattern Recognition and Artificial Intelligence, 18(7), 2004: 1339-1360. 16. Zhang, B. and S. N. Srihari, "Fast nearest neighbor classification using cluster-based trees,"IEEE Transactions on Pattern

Analysis and Machine Intelligence: 26(4), 2004: 525-528. 17. Srihari, S. N., “Author’s Response to Saks’ critique,” Journal of Forensic Sciences, July 2003, 48(4): pp. 919-920. 18. Srihari, S. N. S.-H. Cha, H. Arora, and S. Lee, "Individuality of Handwriting," Journal of Forensic Sciences, 47(4), 2002:

856-872. 19. Cha, S.-H., and S. N. Srihari, "A Fast Nearest Neighbor Search Algorithm by Filtration, Pattern Recog., 35(2), 2002: 515-

525. 20. Park, J., V. Govindaraju and S. N. Srihari, “OCR in a Hierarchical Feature Space,” IEEE Transactions on Pattern

Analysis and Machine Intelligence, 22(4), 2000: 400-407. 21. Plamondon, R., and S. N. Srihari, “On-line and Off-line Handwriting Recognition: A Comprehensive Survey,” IEEE

Transactions on Pattern Analysis and Recognition, 22(1), 2000: 63-84. 22. Srihari, S. N., “Handwritten Address Interpretation: A Task of Many Pattern Recognition Problems,” International Journal

of Pattern Recognition and Artificial Intelligence, 14(5), 2000: 663-674. 23. Wang, X., V. Govindaraju and S. N. Srihari, “Holistic Digit Pair Recognition,” Pattern Recognition, 33(12), 2000: 1967-

1974.

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24. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “A Methodology for Mapping Scores to Probabilities,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(9), 1999: 923-927.

25. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “Postprocessing Recognition of Strings Using Nonstationary Markovian Models,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 21(10), 1999: 990-999.

26. Kim, G., V. Govindaraju and S. N. Srihari, “An Architecture for Handwritten Text Recognition Systems,” International Journal of Document Analysis and Recognition, 2(1), 1999: 37-44.

27. Liu, Y., and S. N. Srihari, “Document Image Binarization Based on Texture Features,” IEEE Transactions on Pattern Recognition and Machine Intelligence, 19(5), 1997: 540-544.

28. Srihari, S. N., T. Hong and G. Srikantan, “Machine-printed Japanese Document Recognition,” Pattern Recognition, 30(8), 1997: 1301-1313.

29. Madhvanath, S., V. Govindaraju and S. Srihari, “Reading Handwritten Phrases on U.S. Census Forms,” International Journal of Imaging Systems and Technology, 7, 1996: 312-319.

30. Niyogi, D., and S. N. Srihari, “An Integrated Approach to Document Decomposition and Structural Analysis,” International Journal of Imaging Systems and Technology, 7, 1996, 330-342.

31. Palumbo, P. W., and S. N. Srihari, “Postal Address Reading in Real Time,” International Journal of Imaging Systems and Technology, 7, 1996: 370-378.

32. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and D.-S. Lee, “A System to Read Names and Addresses on Tax Forms,” Proceedings of IEEE, 84(7), 1996, pp. 1038-1049.

33. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and Z. Shi, “Document Image-processing System for Name and Address Recognition,” International Journal of Imaging Systems and Technology, 7, 1996: 379-391.

34. Chen, M. Y., A. Kundu and S. N. Srihari, “Variable Duration Hidden Markov Model and Morphological Segmentation of Handwritten Words,” IEEE Transactions on Image Processing, 4(12), 1995: 1675-1688.

35. Cohen, E., J. J. Hull and S. N. Srihari, “Control Structure for Interpreting Handwritten Addresses,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(10), 1994: 1049-1055.

36. Ho, T. K., J. J. Hull and S. N. Srihari, “Decision Combination in Multiple Classifier Systems,” IEEE Transactions on Pattern Analysis and Machine Intelligence, 16(1), 1994: 66-75.

37. Wang, D., and S. N. Srihari, “Analysis of Form Images,” International Journal of Pattern Recognition and Artificial Intelligence, 8(5), 1994, pp. 1031-1052.

38. Chen, J. S., and S. N. Srihari, “Hypothesis Generation in Conflict-based Diagnosis,” International Journal of Pattern Recognition and Artificial Intelligence, 7(3), 1993: 465-492.

39. Srihari, S. N., “Recognition of Handwritten and Machine-printed Text for Postal Address Interpretation,” Pattern Recognition Letters, 1993: 291-302.

40. Ho, T. K., J. J. Hull and S. N. Srihari, “A Computational Model for Recognition of Multi-font Word Images,” Machine Vision and Applications, 5(1), 1992: 157-168.

41. Ho, T.K., J.J. Hull and S.N. Srihari, “Multiclassifier Approach to Word Recognition,” Pattern Recognition Letters, 1992.

42. Ho, T. K., J. J. Hull and S. N. Srihari, “Word-Shape Analysis Approach to Lexicon-Based Word Recognition,” Pattern Recognition Letters, 1992: 821-826.

43. Palumbo, P. W., S. N. Srihari, J. Soh, R. Sridhar and V. Demjanenko, “Postal Address Block Location in Real-time,” IEEE Computer, 25(7), 1992: 33-45.

44. Shin, Y.-C., R. Sridhar, V. Demjanenko, P. W. Palumbo and S. N. Srihari, “A Special-Purpose Content Addressable Memory Chip for Real-time Image Processing,” IEEE Journal of Solid State Circuits, 27(5), 1992: 737-744.

45. Srihari, S. N., "High Performance Reading Machines, Proceedings of IEEE, 80(7), 1992: 1120-1132. 46. Cohen, E., J. J. Hull and S. N. Srihari, “Understanding Text in a Structured Environment: Determining ZIP Codes from

Addresses,” International Journal of Pattern Recognition and Artificial Intelligence, 5(1 & 2), 1991: 221-264. 47. Bozinovic, R., and S. N. Srihari, “Off-line Cursive Script Word Recognition,” IEEE Transactions on Pattern Analysis

Machine Intelligence, 11(1), 1989: 68-83. 48. Soh, J., P. W. Palumbo and S. N. Srihari, “Towards Developing a Real-time System for Address Block Location,”

International Journal of Research and Engineering—Postal Applications, 1(1), 1989: 57-76. 49. Srihari, S. N., E. Cohen, J. J. Hull and L. Kuan, “A System to Locate and Recognize ZIP Codes in Handwritten

Addresses,” International Journal of Research & Engineering—Postal Applications, 1(1), 1989, pp. 37-56. 50. Srihari, S. N., and V. Govindaraju, “Analysis of Textual Images Using the Hough Transform,” Machine Vision and

Applications, 2, 1989: 141-153. 51. Srihari, S. N., and Z. Xiang, “Spatial Knowledge Representation,” International Journal of Pattern Recognition and

Artificial Intelligence, 3(1), 1989: 67-84. 52. Wang, D., and S. N. Srihari, “Classification of Newspaper Image Blocks Using Texture Analysis,” Computer Vision,

Graphics and Image Processing, 47, 1989: 327-352.

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53. Wang, C.-H., and S. N. Srihari, “A Framework for Object Recognition in a Visually Complex Environment and Its Application to Locating Address Blocks on Mail Pieces,” International Journal of Computer Vision, 2, 1988: 119-145.

54. Sheikholeslami, G., S. N. Srihari, and V. Govindaraju, “Computer-aided Graphology and Persian Handwriting,” Computer Magazine, 9 (61), 1998, (in Arabic).

55. Bozinovic, R.M. and S.N. Srihari, “A Multilevel Perception Approach to Cursive Script Recognition,” Artificial Intelligence Journal, 33(2), 1987: 217-255.

56. Palumbo, P. W., and S. N. Srihari, “Text Parsing Using Spatial Information for Recognizing Addresses in Mail Pieces,” Electro Technology: Journal of the Society of Electronic Engineers of India, XXXI (1 & 2), 1987: 28.

57. Srihari, S. N., C.-H. Wang, P. W. Palumbo and J. J. Hull, “Address Block Location: Specialized Tools and Problem-Solving Architecture,” AI Magazine, Winter 1987, pp. 25-40. (Cover feature for this issue.)

58. Chutkow, J. G., S. C. Shapiro, S. N. Srihari and Z. Xiang, “Computerized Neurological Diagnosis: A Paradigm of Modeling and Reasoning,” Health Care Instrumentation, 1985: 90-105.

59. Hardas, D., and S. N. Srihari, “Progressive Refinement of 3-D Images Using Coded Binary Trees: Algorithms and Architecture,” IEEE Transactions on Pattern Analysis Machine Intelligence, 6(6), 1984: 748-757.

60. Srihari, S. N., “Pyramid Representations for Solids,” Information Sciences, 34, 1984, pp. 25-46. 61. Hull, J. J., S. N. Srihari and R. Choudhari, “An Integrated Algorithm for Text Recognition: Comparison with a

Cascaded Algorithm,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 5(4), 1983: 384-395. 62. Srihari, S. N., J. J. Hull and R. Choudhari, “Integrating Diverse Knowledge Sources in Text Recognition,” ACM

Transactions on Office Information Systems, 1(1), 1983, pp. 68-87. (Reviewed in Computing Reviews, 1983.) 63. Yau, M., and S. N. Srihari, “A Hierarchical Data Structure for Multidimensional Digital Images,” Communications of

the ACM, 26(7), 1983: 504-515. (Cover feature for this issue.) 64. Bozinovic, R., and S. N. Srihari, “String Correction Algorithm for Cursive Script Recognition,” IEEE Transactions on

Pattern Analysis & Machine Intelligence, 4(6), 1982: 655-663 (corresp.). 65. Hull, J. J., and S. N. Srihari, “Experiments in Text Recognition with Binary N-gram and Viterbi Algorithms,” IEEE

Transactions on Pattern Analysis & Machine Intelligence, 4(5), 1982, pp. 520-530 (corresp.). 66. Srihari, S. N., “Reliability Analysis of Biased Majority-vote Systems,” IEEE Transactions on Reliability, 31(1), 1982:

117-118. 67. Srihari, S. N., “Reliability Analysis of Majority-vote Systems,” Information Sciences, 26, 1982, pp. 243-256. 68. Udupa, J. K., S. N. Srihari and G. T. Herman, “Boundary Detection in Multidimensions,” IEEE Transactions on Pattern

Analysis & Machine Intelligence, 4(1), 1982: 41-50. 69. Srihari, S. N., “Representation of Three-dimensional Digital Images,” ACM Computing Surveys, 13(4), 1981: 399-424. 70. Srihari, S. N., “On Choosing Measurements for Invariant Pattern Recognition,” Inform. Sciences, 21(1), 1980: 1-11. 71. Srihari, S. N., T. Snabb and L. J. White, “An Algorithm for Determining Identity of Nearest-neighbor and Potential

Function Decision Rules,” Pattern Recognition, 12(5), 1980: 293-299. 72. Srihari, S. N., “Recursive Implementation of a Two-step Nonparametric Decision Rule,” IEEE Transactions on Pattern

Analysis & Machine Intelligence, 1(1), 1979: 90-94 (corresp.). 73. Srihari, S. N., and M. K. Ohanesian, “An Efficient Algorithm for Determining Hadamard Sequency Vectors,” IEEE

Transactions on Computers, (3), 1979: 243-244 (corresp.). 74. Srihari, S. N., “Feature-ordering Criteria for Composite Classes Arising in Invariant Pattern Recognition,” IEEE

Transactions on Systems, Man & Cybernetics, 8(7), 1978: 556-561 (corresp.). 9.2 Books 1. A. K. Muda, Y-H Choo, A. Abraham and S. N. Srihari (Eds.) Computational Intelligence in Digital Forensics: Forensic

Investigation and Applications, Springer, Studies in Computational Intelligence 555, 2014, 452 pages. 2. Taylor, M. K.; Kaye, D. H.; Busey, T.; Gische, M.; LaPorte, G.; Aitken, C.; Ballou, S. M.; Butt, L.; Champod, C.;

Charlton, D.; Dror, I. E.; Epstein, J.; Garrett, R. J.; Houck, M.; Imwinkelried, E. J.; Keaton, R.; Langenburg, G.; Leben, D. A.; Maceo, A.; Martin, K. F.; Mnookin, J. L.; Neumann, C.; Polski, J.; Roberts, M. A.; Shappell, S. A.; Shaver, L.; Srihari, S. N.; Stern, H. S.; Stoney, D.; Swienton, A.; Theofanos, M. F.; Thompson, R. M.; Vanderkolk, J.; Weir, M.; Wertheim, K. Latent Print Examination and Human Factors: Improving the Practice through a Systems Approach, NIST Interagency/Internal Report (NISTIR) - 7842, 2012.

3. S. N. Srihari and K. Franke, Eds., Computational Forensics, Springer, LNCS 5158, 2008. 4. S. N. Yanushkevich, P. S. P. Wang, M. L. Gavrilova and S. N. Srihari, Eds., Image Pattern Recognition: Synthesis and

Analysis in Biometrics, World Scientific, 2007. 5. Srihari, S. N.,Computer Text Recognition and Error Correction: A Tutorial, IEEE Computer Society Press, 1984, 363

pp. (ISBN 0-8186-0579-0).

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9.3 Book Chapters 1. S. N. Srihari, "Probabilistic Graphical Models," in Encyclopedia of Social Network Analysis and Mining (ESNAM),

Second Edition, R. Alhajj and J. Rokne, eds., Springer, 2017. 2. S. N. Srihari, "Synthetic Data Sets," in Encyclopedia of Social Network Analysis and Mining (ESNAM), R. Alhajj and J.

Rokne, eds., Springer, 2017. 3. S. N. Srihari and Y. Tang, "Computational Methods for the Analysis of Footwear Evidence,' in Computational

Intelligence in Digital Forensics, A. Muda, Y-H. Choo, A. Abraham and S. N. Srihari (eds.), Springer 2014, 333-383. 4. S. N. Srihari, “Probabilistic Graphical Models,” in Encyclopedia of Social Network Analysis and Mining, R. Alhajj and

J. Rokne (eds.), Springer 2013. 5. S. N. Srihari and G. R. Ball, "An Assessment of Arabic Handwriting Recognition Technology," in V. Margner and H.

El Abed (Eds.), Guide to OCR for Arabic Scripts , Springer 2012, pp. 3-34 6. C. Su and S. N. Srihari, “ Generative Models and Probability Evaluation for Forensic Science,” Pattern Recognition,

Biometrics and Machine Intelligence, P. Wang, Springer 2011. 7. H. Srinivasan and S. N. Srihari, "Use of Conditional Random Fields for Signature-based Retrieval of Scanned

Documents," in Computational Methods for Counterterrorism, S. Argamon & N. Howard (eds). Springer, 2009, 17-32. 8. S. N. Srihari, H. Srinivasan and M. Beal, "Machine Learning for Signature Verification," in Machine Learning in

Document Analysis and Recognition. S. Marinai and H. Fujisawa (eds.), Springer Series: Studies on Computational Intelligence, vol. 90, 2008, pp. 387-408.

9. S. N. Srihari, G. R. Ball and H. Srinivasan,”Versatile Search of Scanned Arabic Handwriting,” in Arabic and Chinese Handwriting Recognition, D. Doermann and S. Jaeger (eds.), LNCS 4768, Springer 2008, pp. 57-69.

10. S. N. Srihari, C. Huang, H. Srinivasan and V. A. Shah, “Biometric and Forensic Aspects of Digital Document Processing”, in Digital Document Processing, B. B. Chaudhuri (ed.), Springer, 2006.

11. Srihari, S.N., “Handwriting Recognition, Automatic”, in Encyclopedia of Language and Linguistics, 2nd Ed, Elsevier, 2006.

12. Cha, S.-H., and S. N. Srihari, "Writing Speed and Writing Sequence Invariant On-line Handwriting Recognition," Pattern Recognition: From Classical to Modern Approaches, S. K. Pal and A. Pal (eds), World Scientific, 2001,559-574.

13. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Address Interpretation,” Mail Technology–Tomorrow’s World: Business Opportunities and Solutions in a Global Market, ImechE, 1999, pp. 147-156.

14. Niyogi, D., S. N. Srihari and V. Govindaraju, “Analysis of Printed Forms,” Handbook of Character Recognition and Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific Publishing, 1997, pp. 485-502.

15. Srihari, S. N., G. Srikantan, T. Hong and S. W. Lam, “Research in Japanese OCR,” Handbook of Character Recognition and Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific, 1997, pp. 357-378.

16. Srihari, S. N., T. Hong and G. Srikantan, “Japanese Optical Character Recognition,” Handbook of Document Image Analysis, H. Bunke and P. S. P. Wang, eds., World Scientific Publishing, 1996.

17. Srihari, S. N., and R. K. Srihari, “Written Language Recognition,” NSF-CEC Joint Survey on Speech and Natural Language Processing, 1996, pp. 69-74.

18. Govindaraju, V., R. K. Srihari and S. N. Srihari, “Handwritten Text Recognition,” Document Analysis Systems, A. L. Spitz and A. Dengel eds., World Scientific Publishing, 1995, pp. 288-306.

19. Srihari, S. N., S. W. Lam and J. J., Hull, “Document Recognition for Digital Library,” Digital Libraries, N. R. Adam, B. K. Bhargava, and Y. Yesha , eds., Springer-Verlag, 1995, pp. 119-128.

20. Fenrich, R., S. Lam and S. N. Srihari, “Optical Character Recognition,” Encyclopedia of Computer Science and Engineering, A. Ralston, ed., third edition, Van Nostrand, 1992, pp. 993-1000.

21. Srihari, S. N., and V. Govindaraju, “Pattern Recognition,” Encyclopedia of Computer Science and Engineering, A. Ralston, ed., third edition, Van Nostrand, 1992, pp. 1034-1041.

22. Srihari, S. N., and J. J. Hull, “Character Recognition,” Encyclopedia of Artificial Intelligence, S. C. Shapiro, ed., second edition, Wiley, 1992, pp. 138-150.

23. Lee, D. S., S. N. Srihari and R. Gaborski, “Bayes and Neural Network Pattern Recognition: A Theoretical Connection and Empirical Results with Handwritten Digits,” Artificial Neural Networks and Statistical Pattern Recognition, I. S. Sethi and and A. K. Jain, eds., North-Holland, 1991, pp. 89-108.

24. Srihari, S. N., “High-performance Reading Machines,” Pattern Recognition: Architecture, Algorithms and Applications, R. Plamondon and H. D. Cheng, eds., World Scientific Publishing, 1991, pp. 271-300.

25. Srihari, S. N., “Applications of Expert Systems in Engineering: An Overview,” Knowledge-Based System Diagnosis, Supervision, and Control, S. G. Tzafestas, ed., Plenum Press, 1989, pp. 1-10.

26. Srihari, S. N., “Feature Extraction for Address Block Location,” From Pixels to Features, J. C. Simon, ed., North Holland, 1989, pp. 261-274.

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27. Srihari, S. N., “The Viterbi Algorithm,” Encyc. of Artificial Intelligence, S. C. Shapiro, ed., Wiley, 1987, 1160-1162. 28. Srihari, S. N., “Multiresolution Representations for 3-D Image Processing and Graphics,” Multiresolution Image

Processing and Analysis, A. Rosenfeld, ed., Springer-Verlag, 1983, pp. 224-236. 29. Jernigan, M. E., and S. N. Srihari, “Pattern Recognition,” Encyclopedia of Computer Science, A. Ralston, ed., second

edition, Van Nostrand Reinhold, 1982, pp. 1110-1119. 30. Altschuler, M. D., Y. Censor, G. T. Herman, A. Lent, R. M. Lewitt, S. N. Srihari, H. Tuy and J. K. Udupa,

“Mathematical Aspects of Image Reconstruction from Projections,” Progress in Pattern Recognition, L. Kanal and A. Rosenfeld, eds., North-Holland, 1981, pp. 323-375.

9.4 Papers in Conference Proceedings

1. T. Duan, Q. Lou, S. N. Srihari, X. Xie, “Sequential embedding induced text clustering: a nonparametric Bayesian approach,” in Proc. Pacific Asia Conf. on Knowledge Discovery and Data Mining (PAKDD), Macau, China, 2019.

2. J. Chu, M. A. Shaikh, M. Chauhan, L. Meng, S. N. Srihari, “Writer verification using CNN feature extraction,” in Proc. Int. Conf. Frontiers of Handwriting Recognition (ICFHR), Niagara Falls, NY 2018, 181-186.

3. M. A. Shaikh, M. Chauhan, J. Chu , S. N. Srihari, “Hybrid feature learning for writer verification,” in Proc. Int. Conf. Frontiers of Handwriting Recognition (ICFHR), Niagara Falls, NY 2018, 187-192.

4. T. Duan and S. N. Srihari, "Layerwise interweaving convolutional LSTM, in Proc. Canadian Conference on Artificial Intelligence, 2017.

5. Z. Xu, S.N. Srihari and W. Dong, “Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model”, in Proc. Neural Information Processing Systems (NIPS), Barcelona, Spain, 2016.

6. T. Duan and S. N. Srihari, “Pseudo-boosted Deep Belief Network,” in Proc. 25th Int. Conf. Artificial Neural Networks, Barcelona, Spain, 2016.

7. Z. Xu and S. N. Srihari, "Missing Value Imputation: Application to Handwriting Data," in Proc. Document Recognition and Retrieval XXII, San Francisco, CA, 2015.

8. G. Fang and S. N. Srihari, “Removing Structural Noise in Handwriting Images using Deep Learning,” in Proc. Int. Conf. Computer Vision, Graphics and Image Processing, Bangalore, India, 28:1-28:8, 2014.

9. G. Fang and S. N. Srihari,"A Noisy-Or Discriminative Restricted Boltzmann Machine for Recognizing Handwriting Style Development," Proc. Int. Conf. Handwriting Recognition, Crete, Greece, 714-719, 2014.

10. S. N. Srihari and Z. Xu, “Development of Handwriting Individuality: An Information-Theoretic Study,” in Proc. Int. Conf. Handwriting Recognition, Crete, Greece, pp. 601-606, 2014.

11. M. Puri, S. N. Srihari and L. Hanson, "Probabilistic Modeling of Children's Handwriting," in Proc. Document Recognition and Retrieval XXI, San Francisco, CA, Feb. 2014.

12. M. Puri, S. N. Srihari and Y. Tang, "Bayesian Network Structure Learning and Inference Methods for Handwriting," in Proc. Int. Conf. Document Analysis and Recognition, Washington DC, Aug. 2013.

13. S. N. Srihari, "Determining Writership of Historical Manuscripts using Computational Methods," in On-line Proceedings Automatic Pattern Recognition and Historical Handwriting Analysis, Erlangen, Germany, June 2013.

14. Y. L. Wong, S. M. Shamsuddin and S. N. Srihari: Fusing Modalities in Forensic Identification with Score Discretization. in AFHA 2013: 46-50, 2013.

15. S. N. Srihari, D. Kovalenko, Y. Tang and G. R. Ball, "Combining Evidence using Likelihood Ratios in Writer Verification'', in Proc. Document Recognition and Retrieval XX, San Francisco, CA, Feb. 2013.

16. D. Kovalenko and S. N. Srihari, "On Methods for Incorporating Evidences into Posterior Scoring of Hypotheses", in Proc. Int. Conf. Pattern Recognition, Tsukuba, Japan, Nov. 2012.

17. Y. Tang and S. N. Srihari. "An Efficient Algorithm for Learning Bayesian Networks for Multinomials," in Proc. Int. Conf. Pattern Recognition, Tsukuba, Japan, Nov. 2012.

18. S. N. Srihari and K. Singer, "Role of Automation in the Examination of Handwritten Items," in Proc. Int. Conf. Handwriting Recognition, Bari, Italy, September 2012.

19. Y. Tang, S. N. Srihari and H. Srinivasan, "Handwriting Individualization Using Distance and Rarity," in Proc. Document Recognition and Retrieval XIX, San Francisco, CA, Jan. 2012.

20. K. Das, S. N. Srihari and H. Srinivasan, "Questioned Document Workflow for Handwriting with Automated Tools," in Proc. Document Recognition and Retrieval XIX, San Francisco, CA, Jan. 2012

21. Y. Tang and S. N. Srihari, "Robust Ellipse Detection," in Proc International Conference on Image Processing, Brussels, Belgium, September 2011.

22. S. N. Srihari, “Evaluating the Rarity of Handwriting Formations,” in Proc. ICDAR, Beijing, China, September 2011.

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23. G. R. Ball and S. N. Srihari, "Statistical Characterization of Handwriting Characteristics using Automated Tools", in Proc. Document Recognition and Retrieval, San Francisco, CA, January 2011.

24. C. Su and S. N. Srihari, "Evaluation of Rarity of Fingerprints in Forensics," in Proc Neural Information Processing Systems, Vancouver, Canada, Dec. 2010.

25. G. R. Ball, S. N. Srihari and R. Stittmeyer, "Writer Identification of Historical Documents Among Cohort Writers," in Proc Int Conference on Frontiers of Handwriting Recognition, Kolkata, India, Nov. 2010.

26. Y. Tang, S. Srihari, H. Kasiviswanathan and J. Corso, "Footwear Print Retrieval System for Real Crime Scene Marks," in Proc Int Workshop on Computational Forensics, Tokyo, Japan, Nov 11-12, 2010.

27. C. Su and S. N. Srihari. "Latent Fingerprint Rarity Analysis in Madrid Bombing Case,"in Proc International Workshop on Computational Forensics, Tokyo, Japan, Nov 11-12, 2010.

28. C. Su and S. N. Srihari, "Latent Fingerprint Core Point Prediction Based on Gaussian Processes”, in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug 2010, pp. 1634-1637.

29. D. Pu and S. N. Srihari, “A Probabilistic Measure for Signature Verification based on Bayesian Learning,” in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug, 2010, pp. 1188-1191.

30. G. R. Ball, S. N. Srihari and H. Kasiviswanathan,"Top Down Analysis of Line Structure in Handwritten Documents," in Proceedings International Conference on Pattern Recognition, Istanbul, Turkey, Aug, 2010.

31. G. R. Ball, R. Stittmeyer and S. N. Srihari, "Writer Verification in Historical Documents," in Proc. Document Recognition and Retrieval XVII, San Jose, CA, January 2010.

32. C. Su and S. N. Srihari, "Probability of Random Correspondence for Fingerprints," in Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009.

33. Y. Liu and S. N. Srihari, "A Computational Discriminability Analysis of Twin Fingerprints," in Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009.

34. D. Pu, G. R. Ball and S. N. Srihari, "A Machine Learning Approach to Off-Line Signature Verification using Bayesian Inference," Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009.

35. K. Manning and S. N. Srihari, "Computer-Assisted Handwriting Analysis: Interaction with Legal Issues in U. S. Courts," Proc. Third International Workshop on Computational Forensics, The Hague, Netherlands, Springer 2009.

36. G. R. Ball and S. N. Srihari, "Semi-supervised Learning for Handwriting Recognition," in Proc Tenth Int. Conf. on Document Analysis Recognition (ICDAR-2009), Barcelona, Spain, July 2009, IEEE Computer Society Press, pp. 29-30.

37. G. R. Ball and S. N. Srihari, "Comparison of Statistical Models for Writer Verification," in Proc Document Recognition and Retrieval XVI, San Jose, CA, January 2009, SPIE, pp. 7247OE 1-8.

38. S. N. Srihari, G. R. Ball and V. Ramakrishnan, "Identification of Forgeries in Handwritten Petitions for Ballot Propositions," Proc. Document Recognition and Retrieval XVI, San Jose, CA, January 2009,

39. C. Su and S. N. Srihari, "Generative Models for Fingerprint Individuality using Ridge Models," Proc International Conference on Pattern Recognition, Tampa, FL, 2008.

40. V. Ramakrishnan and S. N. Srihari, "Extraction of Shoeprint Patterns from Impression Evidence using Conditional Random Fields," Proc International Conference on Pattern Recognition, Tampa, FL, 2008.

41. S. N. Srihari and G. R. Ball, "Language Independent Word Spotting in Scanned Documents," Proc International Conference on Asia-Pacific Digital Libraries, Bali, Indonesia, 2008.

42. S. N. Srihari and G. R. Ball, "Writer verification of Arabic handwriting," Proc. Eighth Int. Workshop on Document Analysis Systems, Nara Japan, IEEE Computer Society Press, 2008, pp. 28-34.

43. G. R. Ball and S. N. Srihari, "Prototype Integration in Off-line Handwriting Recognition Adaptation,", Proc International Conference on Frontiers in Handwriting Recognition, Montreal, Canada, pp. 529-534.

44. K. Kuzhinjedathu, H. Srinivasan, S. N. Srihari, "A Bayesian Approach to Off-Line Signature Verification," Proceedings International Conference on Frontiers in Handwriting Recognition, Montreal, Canada, pp. 611-616.

45. K. Franke and S. N. Srihari, "Computational Forensics: An Overview,"Computational Forensics: Proc Second International Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 1-10.

46. S. N. Srihari and C. Su, "Computational Methods for Determining Individuality,"Computational Forensics: Proceedings Second International Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 11-21.pdf

47. V. Ramakrishnan, M. Malgireddy and S. N. Srihari, "Shoeprint Extraction from Latent Images using CRFs," in Computational Forensics: Proc. Second Int. Workshop, Washington D.C., 2008, Springer LNCS 5158, pp. 105-112.

48. S. N. Srihari, K. Kuzhinjedathu, H. Srinivasan and C. Huang, "Signature Verification using Bayesian Approach,"in Computational Forensics: Proc Second International Workshop , Wash. D.C., 2008, Springer LNCS 5158, 192-203.

49. C. Huang and S. N. Srihari, "Word Segmentation of Off-line Handwritten Documents," Proc. Document Recognition and Retrieval XV, San Jose, CA, SPIE Vol. 6815, January 2008, pp. 68150E-1-6.

50. G. R. Ball and S. N. Srihari, "Writer adaptation in off-line Arabic handwriting," Proc. Document Recognition and Retrieval XV, IST/SPIE Annual Symposium, San Jose, CA, Vol. 6815, January 2008, pp. 681505-1-6.

51. K. Kuzhinjedathu, H. Srinivasan and S. N. Srihari, "Robust line segmentation for handwritten documents," Proc.

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Document Recognition and Retrieval XV, San Jose, CA, SPIE Vol. 6815, January 2008, pp. 68150CC-1-9. 52. C. Huang and S. N. Srihari "Automatic Writer Verification with Handwriting of Twins and Non-Twins," Proc.

International Graphonomics Society Conference Melbourne, Australia, November 2007, pp. 184-187. 53. K. Kuzhinjedathu, H. Srinivasan and S. N. Srihari, "Segmentation of Overlapping Handwritten Lines," Proc.

International Graphonomics Society Conference, Melbourne, Australia, November 2007, pp. 28-31. 54. H. Srinivasan, S. Kabra, C. Huang and S. N. Srihari, "On Computing the Strength of Evidence for Writer Verification,"

Proc. International Conference on Document Analysis and Recognition, Curitiba, Brazil, September 2007, pp.844-848. 55. A. Bharadwaj, A. Singh, H. Srinivasan, and S. N. Srihari, "On the use of Lexeme features for writer verification," in

Proc. Int. Conference on Document Analysis Recognition (ICDAR-2007), Curitiba, Brazil, Sept. 2007, pp. 1088-1092. 56. S. Shetty, H. Srinivasan, and S. N. Srihari, "Handwritten Word Recognition using Conditional Random Fields," in

Proc. Int. Conference on Document Analysis Recognition (ICDAR-2007), Curitiba, Brazil, Sept. 2007, pp. 1098-1102. 57. K. Franke and S. N. Srihari, "Computational Forensics: Towards Hybrid-Intelligent Crime Investigation", Proc. Int.

Symp. Information Assurance Security/ Int. Wkshop on Computational Forensics (IWCF 2007), Manchester, England, Aug. 2007, IEEE-CS Press, pp. 383-386.

58. G. Fang, H. Srinivasan and S. N. Srihari, "Use of Ridge Types in Generative Models of Fingerprint Individuality," Proc. Int. Symp. Information Assurance and Security/ Int. Wkshop Computational Forensics ( IWCF 2007), Manchester, England, Aug. 2007, IEEE-CS Press, pp. 423-428.

59. G. Fang, S. N. Srihari, H. Srinivasan, and P. Phatak, "Use of ridge points in partial fingerprint matching," in Proc. Defense Security Symp, A. Ross(ed) Proc. SPIE, Orlando, FL, April 2007, vol. 6539, pp. 65390D-1 to 65390D-9.

60. M. Arivazhagan, H. Srinivasan, and S. N. Srihari, "A Statistical Approach to Handwritten Line Segmentation", in Proc. Document Recognition and Retrieval IV, Proceedings of SPIE, San Jose, CA, February 2007, pp. 6500T-1 to 6500T-11.

61. S. Shetty, H. Srinivasan, S. N. Srihari and M. Beal, "Use of Conditional Random Fields in Document Image Retrieval," in Proc. Document Recognition and Retrieval IV, Proc. SPIE, San Jose, CA, February 2007, pp. 6500U1-6500U9.

62. S. N. Srihari, R. K. Srihari, H. Srinivasan and P. Babu, "On the Automatic Scoring of Handwritten Essays," in Proc. International Joint Conference on Artificial Intelligence(IJCAI), Hyderabad, India, Jan. 2007, pp. 2880-2884.

63. C. Huang and S. N. Srihari, "Mapping Transcripts to Handwritten Text,"Proc. International Workshop on Frontiers in Handwriting Recognition (IWFHR-10), La Baule, France, October 2006, pp. 15-20.

64. G. Ball, S. N. Srihari and H. Srinivasan, "Segmentation-Free and Segmentation-Dependent Approaches to Arabic Word Spotting," in Proc. Int. Wkshop Frontiers in Handwriting Recognition, La Baule, France, Oct. 2006, pp. 53-58.

65. S. Chen and S. N. Srihari, "Machine Print Filter for Handwriting Analysis," in Proc. International Workshop on Frontiers in Handwriting Recognition (IWFHR-10), La Baule, France, October 2006, pp. 569-573.

66. S. Chen and S. N. Srihari, "A New Off-line Signature Verification Method based on Graph Matching," Proc. International Conference on Pattern Recognition (ICPR 2006), Hong Kong, Aug. 2006.

67. S. N. Srihari, S. Shetty, S. Chen, H. Srinivasan, C. Huang, G. Agam, O. Frieder, "Document Image Retrieval using Signatures as Queries," in Proc. Second IEEE International Conference on Document Image Analysis for Libraries, Lyon, France, April 27-28, 2006, pp. 198-203.

68. H. Srinivasan, S. N. Srihari and M. Beal, "Comparison of Classification Methods for Fingerprint Verification for Variable Number of Minutiae," in Proc. Biometric Technology for Human Identification III: SPIE Defense and Security Symposium, Orlando, FL, April 17-22, 2006, pp. 620209-1 to 620209-12.

69. S. N. Srihari, J. Collins, R. K. Srihari, P. Babu and H. Srinivasan "Automatic Scoring of Handwritten Essays using Latent Semantic Analysis" Proc. Document Analysis Systems Springer, Nelson, New Zealand, Feb. 2006, pp. 71-83.

70. S. N. Srihari, H. Srinivasan, P. Babu and C. Bhole, "Spotting Words in Handwritten Arabic Documents," Proc. Document Recognition and Retrieval XIII(SPIE), San Jose, CA, January 2006, pp. 606702-1 to 606702-12.

71. S. Chen and S. N. Srihari, "Combining one- and two-dimensional signal recognition approaches to off-line signature verification," Proc. Document Recognition Retrieval XIII(SPIE), San Jose, CA, Jan. 2006, pp. 606701-1 to 606701-10.

72. S. N. Srihari, H. Srinivasan, P. Babu and C. Bhole, "Handwritten Arabic Word Spotting using the CEDARABIC Document Analysis System," Proc. Symp. Doc. Image Understanding (SDIUT 05), Nov. 2005, pp. 123-132.

73. S. Chen and S. N. Srihari, "Use of Exterior Contours and Word Shape in Off-line Signature Verification," Proc. International Conference on Document Analysis and Recognition, Seoul, Korea, August 2005, pp. 1280-1284.

74. S. N. Srihari, M. Beal, K. Bandi, V. Shah and P. Krishnamurthy, "A Statistical Model for Writer Verification," Proc. International Conference on Document Analysis and Recognition, Seoul, Korea, August 2005, pp. 1105-1109.

75. H. Srinivasan, S. N. Srihari and M. Beal, "Signature Verification using Kolmogorov-Smirnov Statistic," Proc. International Graphonomics Society Conference (IGS), June 2005, Salerno, Italy, pp. 152-156.

76. K. Bandi and S. N. Srihari, "Writer Demographic Identification using Bagging and Boosting," Proc. International Graphonomics Society Conference (IGS), June 2005, Salerno, Italy, pp.133-137.

77. H. Srinivasan, M. Beal and S. N. Srihari, "Machine Learning for Person Identification and Verification", SPIE Conf. Homeland Security, Orlando, FL, March 2005, Society of Photo Instrumentation Engineers (SPIE), 574-586.

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78. S. N. Srihari, C. Huang and H. Srinivasan, "A Search Engine for Handwritten Documents", Document Recognition and Retrieval XII, San Jose, CA, January 2005, Society of Photo Instrumentation Engineers (SPIE), pp. 66-75.

79. S. N. Srihari, C. Huang and H. Srinivasan, "Content-Based Retrieval of Handwritten Document Images," Knowledge Based Computer Systems (KBCS 2004), Hyderabad, India, December 2004, pp. 302-311.

80. A. Xu, S.N. Srihari, and M. K. Kalera "Learning Strategies for Signature Verification", Proc. Int. Workshop Frontiers in Handwriting Recognition (IWFHR 2004), Tokyo, Japan, Nov. 2004, IEEE Computer Society Press, pp. 161-166.

81. C. Tomai, B. Zhang and S. N. Srihari, "Discriminatory power of handwritten words for writer recognition," Proc. International Conference on Pattern Recognition (ICPR 2004), Cambridge, England, August 2004, pp. 638-641.

82. B. Zhang and S. N. Srihari, "Discovery of a tri-edge inequality for binary dissimilarity measures", Proc. International Conference on Pattern Recognition (ICPR 2004), Cambridge, England, August 2004, pp. 669-672.

83. Zhang, Bin, S. N. Srihari and C. Huang, “Word Image Retrieval Using Binary Features,” Document Recognition and Retrieval XI (E.H.B. Smith, J. Hu and J. Allan, eds.) SPIE, Bellingham WA, 2004, ISBN 0-8194-5199-1, pp. 45-53.

84. Tomai, Catalin, D. M. Kshirsagar and S. N. Srihari, “Group Discriminatory Power of Handwritten Characters,” Document Recognition and Retrieval XI (E.H.B. Smith, J. Hu and J. Allan, eds.) SPIE, Bellingham WA, 2004, pp. 116-123.

85. M. Kalera, B. Zhang and S. N. Srihari,” Off-line signature verification and identification using distance statistics,” Proceedings eleventh International Graphonomics Society Conf. (IGS), pp. 228-232, Nov. 2003, Scottsdale, Arizona.

86. B. Zhang, and S. N. Srihari, "Handwriting Identification using Multiscale Features," Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 270-273, November 2003, Scottsdale, Arizona.

87. A. Shekhawat, S. N. Srihari, and S. Parulekar "Individuality Studies for On-line Handwriting” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 266-269, November 2003, Scottsdale, Arizona.

88. Z. Shi, B. Zhang, C. Tomai, and S. N. Srihari, “Recognition based system for handwriting verification and identification,” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 261-265, Nov. 2003, Scottsdale, Arizona.

89. S. N. Srihari and G. Leedham, “A survey of computer methods in forensic document examination,” Proceedings eleventh International Graphonomics Society Conference (IGS), pp. 278-281, November 2003, Scottsdale, Arizona.

90. B. Zhang, C. Tomai, S. Srihari and V. Govindaraju, “Construction of handwriting databases using transcript-based mapping,” Proceedings of Document Image Analsysi Digital Libraries (DIAL 2004), pp. 288-298, Palo Alto, CA, Jan. 2004.

91. S, N. Srihari and Z. Shi, Forensic Handwritten Document Retrieval System, Proceedings of Document Image Analsysi for Digital Libraries (DIAL 2004), pp. 188-194, Palo Alto, CA, January 2004.

92. C. I. Tomai and S.N. Srihari, Combination of Type III Digit Recognizers using Dempster-Shafer Theory of Evidence, Proceedings International Conference on Document Analysis Recognition (ICDAR), Edinburgh, Scotland, Aug. 2003.

93. S. N. Srihari, C. I. Tomai, B. Zhang and S-J. Lee, “Individuality of Numerals,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003.

94. B. Zhang and S. N. Srihari, “Individuality of Characters,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003.

95. B. Zhang and S. N. Srihari, “Individuality of Words,” Proceedings International Conference on Document Analysis and Recognition (ICDAR), Edinburgh, Scotland, August 2003.

96. S.N.Srihari, C. Tomai, B. Zhang, S-J.Lee, Z. Shi and Y.C.Shin, “Handriwitng Matching and Recognition,” Proceedings Symposium of Document Image Undertanding (SDIUT), Greenbelt, MD, April 2003.

97. B. Zhang and S.N.Srihari, “Binary vector dissimilarity measures for handwriting identification,”Proceedings, Electronic Imaging, SPIE vol. 5010, January 2003, pp.28-38.

98. Lee, S., S.-H. Cha and S. N. Srihari, "Combining Macro and Micro Features for Writer Identification," SPIE, Document Recognition and Retrieval IX, San Jose, CA, January 2002, pp. 155-166.

99. Srihari, S. N., S.-H. Cha and S. Lee, "The Discriminatory Power of Handwriting," Invited Paper, SPIE, Document Recognition and Retrieval IX, San Jose, CA, January 2002, pp. 129-142.

100. Zhang, B., C. Tomai, A. Zhang and S. N. Srihari, "An Adaptive Image Retrieval System Using Wavelets," International Conference on Image Processing (ICIP 2002), Rochester, NY, September 2002.

101. Cha, S.-H., and S. N. Srihari, “Apriori Algorithm for Sub-category Classification Analysis of Handwriting,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 1022-1025

102. Cha, S.-H., and S. N. Srihari, “Handwritten Document Image Database Construction and Retrieval Systems,” SPIE Document Recognition and Retrieval VIII, San Jose, CA, January, 2001, pp. 13-21.

103. Setlur, R., A. Lawson, V. Govindaraju and S. N. Srihari, “Truthing, Testing and Evaluation Issues in Complex Systems,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 1205-1214.

104. Srihari, S. N., S.-H. Cha, H. Arora and S. Lee, “Individuality of Handwriting: A Validation Study,” Sixth International Conference on Document Analysis and Recognition (ICDAR'01), Seattle, WA, September 2001, pp. 106-109.

105. Srihari, S. N., S.-H. Cha and S. Lee, “Establishing Handwriting Individuality Using Pattern Recognition Techniques,”

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Sixth International Conf. Document Analysis and Recognition (ICDAR'01), Seattle, WA, Sept. 2001, pp. 1195-1204. 106. Cha, S.-H., Y.-C. Shin and S. N. Srihari, “Approximate String Matching for Stroke Direction and Pressure Sequences,”

SPIE: Document Recognition and Retrieval VII, San Jose, CA, January 2000, pp. 2-10. 107. Cha, S.-H., and S. N. Srihari, “Assessing the Authorship Confidence of Handwritten Items,” Fifth Workshop on the

Application of Computer Vision 2000, Palm Springs, CA, December 2000, pp. 42-47. 108. Cha, S.-H., and S. N. Srihari, “Comparing Color Images Using Angular Histogram Measures,” Joint Conference on

Information Sciences, Atlantic City, NJ, February 2000, pp. 139-142. 109. Cha, S.-H., and S. N. Srihari, “Convex Hull Discriminant Function and Its Application to the Writer-Identification

Problem,” Joint Conference on Information Sciences, Atlantic City, NJ, February 2000, pp. 13-16. 110. Cha, S.-H., and S. N. Srihari, “Distance between Histograms of Angular Measurements and its Application to

Handwritten Character Similarity,” International Conference Pattern Recog., Barcelona, Spain, Sept. 2000, pp. 21-24. 111. Cha, S.-H., and S. N. Srihari, “Mapping the Many-Class Problem into a Dichotomy Using Distance Measures,”

International Conference of Statistics, San Antonio, TX, March 2000, pp. 57-58. 112. Cha, S.-H., and S. N. Srihari, “Multiple Feature Integration for Writer Identification,” Seventh International Workshop

on Frontiers of Handwriting Recognition, Amsterdam, The Netherlands, September 2000, pp. 333-342. 113. Cha, S.-H., and S. N. Srihari, “Nearest Neighbor Search Using Additive Binary Tree,” IEEE Conference on Computer

Vision and Pattern Recognition (CVPR00), Hilton Head, SC, June 2000, pp. 738-745. 114. Cha, S.-H., and S. N. Srihari, “System That Identifies Writers,” Seventeenth National Conference of American

Association of Artificial Intelligence 2000, Austin, TX, July 2000, p. 1068. 115. Cha, S.-H., and S. N. Srihari, “Writer Identification: Statistical Analysis and Dichotomizer,” International Workshop on

Structural and Syntactical Pattern Recognition 2000, Alicante, Spain, August 2000, pp. 123-132. 116. Srihari, S. N., “A Survey of Sequential Combination of Word Recognizers in Handwritten Phrase Recognition at

CEDAR,” Lecture Notes in Computer Science, IAPR International Workshop on Multiple Classifier Systems, Cagliari, Italy, June 2000, pp. 45-51.

117. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “Recognition of Strings Using Non-Stationary Markovian Models: An Application in ZIP Code Recognition,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR99), Fort Collins, CO, June 1999, pp. 174-179.

118. Cha, S.-H., Y.-C. Shin and S. N. Srihari, “Approximate Stroke Sequence String Matching Algorithm for Character Recognition and Analysis,” Fifth International Conference on Document Analysis and Recognition (ICDAR99), Bangalore, India, September 1999, pp. 53-56.

119. Govindaraju, V., S. N. Srihari and Y.-C. Shin, “Use of Handwriting Recognition Features in Handwriting Recognition,” International Graphonomics Society Conference, Singapore, June 1999, pp. 73-78.

120. Jung, M.-C., Y.-C. Shin and S.N. Srihari, “Machine-Printed Character Segmentation Method Using Side Profiles,” IEEE International Conference on Systems, Man and Cybernetics, Tokyo, Japan, October 1999.

121. Jung, M.-C., Y.-C. Shin and S. N. Srihari, “Multifont Classification Using Typological Attributes,” Fifth International Conference on Document Analysis and Recognition (ICDAR99), Bangalore, India, September 1999, pp. 353-356.

122. Mahadevan, U., and S. N. Srihari, “Parsing and Recognition of City, State, and ZIP Codes in Handwritten Addresses,” Fifth International Conf. Document Analysis Recognition (ICDAR99), Bangalore, India, Sept. 1999, pp. 325-328.

123. Park, J., V. Govindaraju and S. N. Srihari, “Efficient Word Segmentation Driven by Unconstrained Handwritten Phrase Recognition,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 605-608.

124. Srihari, S. N., “Mining Postal Databases for Address Interpretation,” International Symposium on Document Analysis and Speech Recognition, Indian Statistical Institute, Calcutta, India, December 1999.

125. Srihari, S. N., “A Task of Many Pattern Recognition Problems,” Second International Conference on Multimodal Interface (ICMI99), Kowloon Tong, Hong Kong, January 1999, pp. 2-4.

126. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Address Interpretation,” Mail Technology–Tomorrow’s World, Brighton, UK, June 1999, pp. 147-158.

127. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Information Theoretic Modeling of Postal Address Fields for Overcoming Ambiguity,” HKK Conference, Waterloo, Ontario, Canada, June 1999, pp. 105-110.

128. Srihari, S. N., W.-J. Yang and V. Govindaraju, “Information Theoretic Analysis of Postal Address Fields for Automatic Address Interpretation,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 309-312.

129. Wang, X., V. Govindaraju and S. N. Srihari, “Multi-Experts for Touching Digit String Recognition,” Fifth International Conference on Document Analysis and Word Recognition (ICDAR99), Bangalore, India, September 1999, pp. 800-803.

130. Bartnik, D., V. Govindaraju, S. N. Srihari and B. Phan, “Postal Reply-Card Mail Processing,” Fourteenth International Conference on Pattern Recognition, Brisbane, Australia, August 1998, pp. 633-636.

131. Bouchaffra, D., V. Govindaraju and S. N. Srihari, “A Methodology for Deriving Probabilistic Correctness from

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Recognizers,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR98), Santa Barbara, CA, June 1998, pp. 930-935.

132. Govindaraju, V., K. Ianakiev and S. N. Srihari, “Improving Classifier Accuracy by Simulating Fuzzy Boundaries between Classes,” North American Fuzzy Logic and Image Processing Conf., Pensacola, FL, August 1998, pp. 161-164.

133. Kim, G., V. Govindaraju and S. N. Srihari, “Architecture for Handwritten Text Recognition Systems,” Sixth International Workshop on Frontiers of Handwriting Recognition (IWFHRVI), Taejon, Korea, Aug. 1998, pp. 113-122.

134. Madhvanath, S., and V. Govindaraju, “Perceptual Features for Off-Line Handwritten Word Recognition: A Framework for Heuristic Prediction,” IAPR Workshop Matching and Representation, Syntactic and Statistical Pattern Recognition, Sydney, Australia, August 1998.

135. Park, J., V. Govindaraju, and S. N. Srihari, “OCR in Hierarchical and Multi-Resolution Feature Space,” IEEE Conference on Systems, Man and Cybernetics, San Diego, CA, October 1998, pp. 4324-4329.

136. Srihari, S. N., W.-J. Yang, V. Govindaraju, X. Song and X. Wang, “Statistical Analysis of United States Postal Addresses,” International Conference on Combinatorics, Statistics, Pattern Recognition and Related Areas (Fifth International Conference of the Forum for Interdisciplinary Mathematics), Mysore, India, December 1998, pp. 71-72.

137. Wang, X., V. Govindaraju and S. N. Srihari, “Holistic Recognition of Touching Digits,” Sixth International Workshop on Frontiers of Handwriting Recognition (IWFHRVI), Taejon, Korea, August 1998, pp. 295-303.

138. Bouchaffra, D., E. Koontz, V. Krpsundar, R. K. Srihari and S. N. Srihari, “Integrating Signal and Language Context to Improve Handwritten Phrase Recognition: Alternative Approaches,” Sixth International Workshop on Artificial Intelligence and Statistics, Fort Lauderdale, FL, January 1997, pp. 47-54.

139. Govindaraju, V., and S. N. Srihari, “Paradigms in Handwriting Recognition,” IEEE International Conference on Systems, Man and Cybernetics, Orlando, FL, October 1997, pp. 1498-1503.

140. Hong, T. and S. N. Srihari, “Representing OCR'ed Documents in HTML,” International Conference on Computational Intelligence and Multimedia Applications (ICCIMA'97), Gold Coast, Australia, February 1997, pp. 18-22.

141. Hong, T. and S. N. Srihari, “Representing OCR'ed Documents in HTML,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 831-835.

142. Madhvanath, S., E. Kleinberg, V. Govindaraju and S. N. Srihari, “The HOVER System for Rapid Holistic Verification of Off-line Handwritten Phrases,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 855-859.

143. Niyogi, D., and S. N. Srihari, “The Use of Document Structure Analysis to Retrieve Information from Documents in Digital Libraries,” SPIE/IS&T Symposium on Electronic Imaging: Science & Technology, San Jose, CA, February 1997.

144. Shi, Z., S. N. Srihari, Y.-C. Shin and V. Ramanaprasad, “A System for Segmentation and Recognition of Totally Unconstrained Handwritten Numeral Strings,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 455-458.

145. Srihari, S. N., and E. J. Keubert, “Integration of Handwritten Address Interpretation Technology into the United States Postal Service Remote Computer Reader System,” Fourth International Conference on Document Analysis and Recognition (ICDAR97), Ulm, Germany, August 1997, pp. 892-896.

146. Srihari, S. N., and G. Kim, “PENMAN: A System for Reading Unconstrained Handwritten Page Images,” Symposium on Document Image Understanding Technology (SDIUT97), Annapolis, MD, April 1997, pp. 142-153.

147. Favata, J., S. N. Srihari and V. Govindaraju, “Off-Line Handwritten Sentence Recognition,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 171-176.

148. Govindaraju, V., and S. N. Srihari, “Assessment of Image Quality to Predict Readability of Documents,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, pp. 137-138.

149. Hong, T., and J. J. Hull and S. N. Srihari, “A Unified Approach towards Text Recognition,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 130.

150. Hong, T., G. Srikantan, V.C. Zandy, C. Fang and S.N. Srihari, Character Recognition in a Japanese Text Recognition System, IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p.p. 51-62.

151. Hong, T., S. Wu, S. N. Srihari, “Evaluating Japanese Document Recognition in the Internet/Intranet Environment,” Fifth Symposium on Document Analysis and Information Retrieval (SDAIR96), Las Vegas, NV, April 1996, pp. 271-286.

152. Hong, T., S. Wu and S. N. Srihari, “Evaluating Japanese Document Recognition in the Internet/Intranet Environment,” Workshop on Document Analysis Systems (DAS96), October 1996, pp. 633-650.

153. Kim, G., V. Govindaraju and S. N. Srihari, “Extension of a Handwritten Word Recognition Method to Street Name Images,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 221-226.

154. Kim, G., V. Govindaraju and S. N. Srihari, “Handwritten Word Recognition Using Dynamic Matching with Variable Duration,” International Conference on Acoustics, Speech and Signal Processing, Atlanta, GA, May 1996, pp. 3454-

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3457. 155. Kim, G., V. Govindaraju and S. N. Srihari, “A Segmentation and Recognition Strategy for Handwritten Phrases,”

Thirteenth International Conference on Pattern Recognition (ICPR96), Vienna, Austria, August 1996, pp. D510-D513. 156. Madhvanath, S., and S. N. Srihari, “Effective Reduction of Large Lexicons for Recognition of Off-Line Cursive

Script,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp.189-194.

157. Madhvanath, S., and S. N. Srihari, “Modes and Measures: A Framework for Design of Parallel Word Classifier Combination Schemes,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 449-452.

158. Madhvanath, S., and S. N. Srihari, “A Technique for Local Baseline Determination,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 445-448.

159. Mahadevan, U., and S. N. Srihari, “Hypothesis Generation for Word Separation in Handwritten Lines,” Fifth International Workshop Frontiers Handwriting Recognition (IWFHRV), Essex, England, Sept.1996, pp. 453-456.

160. Niyogi, D., and S. N. Srihari, “Using Domain Knowledge to Derive the Logical Structure of Documents,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 133.

161. Ramanaprasad, V., Y.-C. Shin and S. N. Srihari, “Reading Handprint Addresses on IRS Tax Forms,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, pp. 135-136.

162. Sheikholeslami, G., S. N. Srihariand and V. Govindaraju, “Computer-Aided Graphology,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 457-460.

163. Srihari, S. N., “Image Quality and Readability,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January, 1996.

164. Srihari, S. N., “Recent Advances in Off-line Handwriting Recognition,” Fifth International Workshop on Frontiers in Handwriting Recognition (IWFHRV), Essex, England, September 1996, pp. 1-15.

165. Srihari, S. N., “System for Reading Handwritten Documents,” IEEE International Conference on Systems, Man, and Cybernetics, San Jose, CA, January 1996.

166. Srihari, S. N., G. Srikantan and T. Hong, “A General-Purpose Japanese OCR System,” Fifth Symposium on Document Analysis and Information Retrieval (SDAIR96), Las Vegas, NV, April 1996, pp. 271-286.

167. Srikantan, G., T. Hong, V. C. Zandy and S. N. Srihari, “Japanese OCR System for Machine-Printed Document Images,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, January 1996, p. 131.

168. Bhate, A., S. W. Lam and S. N. Srihari, “Sliding Window Technique for Word Recognition,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, CA, February 1995, p. 236.

169. Govindaraju, V., and S.N. Srihari, “Image Quality and Human Readability,” IEEE International Conference on Image Processing (ICIP95), Washington, D.C., October 1995, Vol. III, pp. 324-327.

170. Hong, T., S.W. Lam, J.J. Hull and S.N. Srihari, “The Design of a Nearest-Neighbor Classifier and Its Use for Japanese Character Recognition,” Third International Conference on Document Analysis and Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 270-273.

171. Hong, T., S. W. Lam, J. J. Hull and S. N. Srihari, “Visual Similarity Analysis of Chinese Characters and Its Uses in Japanese OCR,” IS&T/SPIE Symposium Electronic Imaging: Science Tech., San Jose, California, Feb. 1995, p. 242.

172. Lam, S. W., Q. Liao and S. N. Srihari, “Divide-and-Conquer Approach to Japanese Text Segmentation,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 241.

173. Lee, D.-S., and S. N. Srihari, “Classifier Combination Using Neural Network Approach,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 236.

174. Lee, D.-S., and S.N. Srihari, “A Theory of Classifier Combination: The Neural Network Approach,” Third International Conference on Document Analysis Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 42-45.

175. Lii, J., and S. N. Srihari, “Location of Name and Address on Fax Cover Pages,” Third International Conference on Document Analysis and Recognition (ICDAR'95), Montreal, Canada, August 1995, pp. 756-759.

176. Madhvanath, S., V. Govindaraju, V. Ramanaprasad, D.-S. Lee and S. N. Srihari, “Reading Handwritten US Census Forms,” Third Int. Conference Document Analysis Recognition (ICDAR'95), Montreal, Canada, Aug. 1995, pp. 82-85.

177. Niyogi, D., and S.N. Srihari, “Knowledge-Based Derivation of Document Logical Structure,” Third International Conference on Document Analysis and Recognition (ICDAR '95), Montreal, Canada, August 1995, pp. 472-475.

178. Srihari, S. N., “Japanese OCR ,” Symp. Doc. Image Und. Tech. (SDIUT), Bowie, MD, Oct. 1995, pp. 236-246. 179. Srihari, S. N., “System for Reading Handwritten Documents,” IEEE International Conference on Systems, Man and

Cybernetics, Vancouver, Canada, October 1995. 180. Srihari, S. N., V. Govindaraju and J. Favata, “Unconstrained Handwritten Text Recognition,” Symposium on Document

Image Understanding Technology (SDIUT), Bowie, MD, October 1995, pp. 226-235. 181. Srihari, S. N., Y.-C. Shin, V. Ramanaprasad and D.-S. Lee, “Name and Address Block Reader System for Tax Form

Processing,” Third Int. Conf. Document Analysis Recog. (ICDAR ’95), Montreal, Canada, Aug. 1995, pp. 5-10.

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182. Srikantan, G., and S. N. Srihari, “Data Representations in Learning,” Fifth Int. Workshop on Artificial Intelligence & Statistics, Florida, January 1995, 495.

183. Zhao, S., and S. N. Srihari, “A Word Recognition Algorithm for Machine-Printed Word Images of Multiple Fonts and Varying Qualities,” Third Int. Conf. Document Anal. Recog. (ICDAR'95), Montreal, Canada, Aug.1995, pp. 351-354.

184. Zhao, X., and S. N. Srihari, “Word Recognition Using a Lexicon Constrained by First/Last Character Decisions,” IS&T/SPIE Symposium on Electronic Imaging: Science & Technology, San Jose, California, February 1995, p. 238.

185. Cullen, P., R. S. Curtis, P. D. Filipski, J. J. Hull and S. N. Srihari, “Machine Print Address Interpretation Utilizing Contextual Knowledge,” Inst. Mech. Engineers Mail Systems 2000 Int. Conf., London, England, May 1994, pp. 97-105.

186. Favata, J., G. Srikantan and S. N. Srihari, “Hand-printed Character/Digit Recognition Using a Multiple Feature/Resolution Philosophy,” Int. Wkshp Front. Hand. Recog. (IWFHR IV), Dec. 1994, Taipei, Taiwan, pp. 57-66.

187. Govindaraju, V., R. K. Srihari and S. N. Srihari, “Handwritten Text Recognition,” International Conference on Document Analysis Systems (DAS 94), Kaiserslautern, Germany, October 1994, pp. 157-171.

188. Lam, S., V. Govindaraju, R. K. Srihari, J. J. Hull and S. N. Srihari, “Intelligent Data Retrieval from Raster Images of Documents,” First Annual Conference Theory Practice of Digital Libraries, College Station, TX, Jun. 1994, pp. 34-40.

189. Lii, J., and S. N. Srihari, “Use of Character Recognition and Syntax in Locating Address Paragraphs in Complex Documents,” Twelfth International Conference on Pattern Recognition, October 1994, pp. 1241-1255.

190. Srihari, S. N., S. Lam and J. J. Hull, “Document Recognition for Digital Libraries,” Workshop on Digital Libraries, Newark, NJ, May 1994.

191. Srihari, S. N., R. K. Srihari and V. Govindaraju, “Handwritten Text Recognition,” Fourth International Workshop on the Frontiers of Handwriting Recognition (IWFHRIV), Taipei, Taiwan, December 1994, pp. 265-274.

192. Srikantan, G., R. K. Fenrich and S. N. Srihari, “Contrast Enhancement for Mailpiece Images,” IEEE Southwest Symposium on Image Analysis and Interpretation, Dallas, TX, April 1994, p. 82.

193. Srikantan, G., and S. N. Srihari, “A Study Relating Image Sampling Rate and Image Pattern Recognition,” IEEE Conference on Computer Vision and Pattern Recognition, Seattle, WA, June 1994, p. 709.

194. Lam, S.W., L. Javanbakht and S.N. Srihari, “Anatomy of a Form Reader,” Second International Conference on Document Analysis and Recognition (ICDAR93), Tsukuba Science City, Japan, October 1993, pp. 506-509.

195. Lam, S.W., X. Shen and S.N. Srihari, “Representing Lexicons by Modified Tie for Fast Partial String Matching,” SPIE/IS&T Symposium on Electronic Imaging Science and Technology, San Jose, CA, February 1993.

196. Lii, J., P.W. Palumbo and S.N. Srihari, “Address Block Location Using Character Recognition and Address Syntax,” Second International Conference Document Anal. Recognition (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 330-335.

197. Liu, Y., R. Fenrich and S.N. Srihari, “An Object Attribute Thresholding Algorithm for Document Image Binarization,” Second International Conf. Document Analysis Recog. (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 278-281.

198. Srihari, S. N., “From Pixels to Paragraphs: The Use of Models in Text Recognition,” Second Symposium on Document Analysis and Recognition, Las Vegas, NV, April 1993, 47-64.

199. Srihari, S.N., V. Govindaraju and A. Shekhawat, “Interpreting Handwritten Addresses in US Mailstream,” Second International Conference on Document Analysis and Recognition (ICDAR93), Tsukuba, Japan, Oct. 1993, pp. 291-294.

200. Srikantan, G., S.W. Lam and S.N. Srihari, “Gradient-Based Contour Encoding for Grayscale Character Recognition,” SPIE/IS&T Symposium on Electronic Imaging Science and Technology, San Jose, CA, February 1993.

201. Zhou, J., V. Govindaraju, R. Acharya and S.N. Srihari, “Recognition of State Name Abbreviations,” Third International Workshop on Frontiers of Handwriting Recognition (IWFHRIII), Buffalo, NY, May 1993, pp. 423-430.

202. Chen, M. Y., A. Kundu, J. Zhou and S. N. Srihari, “Off-line Handwritten Word Recognition Using Hidden Markov Model,” United States Postal Service Advanced Technology Conf., Washington, DC, November 1992, pp. 563-578.

203. Cullen, P., T.-K. Ho, J. J. Hull, M. Prussak and S .N. Srihari, “Contextual Analysis of Machine-Printed Addresses,” Machine Vision Applications Character Recognition Industrial Inspection, San Jose, CA, February 1992, pp. 257-268.

204. Cullen, P., J. J. Hull and S. N. Srihari, “A Constraint-based Approach to Postal Address Interpretation,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 367-377.

205. Favata, J., and S. N. Srihari, “Recognition of General Handwritten Words Using a Hypothesis Generation and Reduction Methodology,” United States Postal Service Adv. Tech. Conf, Washington, DC, Nov. 1992, pp. 237-251.

206. Fenrich, R., S. N. Srihari, P. Scott and M. Woolston, “Real-time High-resolution Image Acquisition Prototype,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 1113-1127.

207. Filipski, P., J. J. Hull and S. N. Srihari, “Compression for Fast Read-only Access of a Large Database,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 795-807.

208. Govindaraju, V., S. N. Srihari and D. Sher, “A Computational Model for Face Location Based on Cognitive Principles,” AAAI Tenth National Conference on Artificial Intelligence, San Diego, CA, July 1992, pp. 350-355.

209. Govindaraju, V., D. Wang and S. N. Srihari, “Using Temporal Information in Off-line Word Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 529-544.

210. Ho, T. K., J. J. Hull and S. N. Srihari, “On Multiple Classifier Systems for Pattern Recognition,” Eleventh Annual

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International Conference on Pattern Recognition, Amsterdam, Netherlands, 1992, pp. 84-87. 211. Lam, S., A. Girardin and S. N. Srihari, “Gray Scale Character Recognition Using Boundary Features,” Machine Vision

Applications in Character Recognition and Industrial Inspection, San Jose, CA, February 1992, pp. 98-105. 212. Lee, D. S., and S. N. Srihari, “Machine-printed Character Recognition with Biological and Theoretical Bases,” United

States Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 689-699. 213. Li, L., T. K. Ho, J. J. Hull and S. N. Srihari, “A Hypothesis Testing Approach to Word Recognition Using Dynamic

Feature Selection,” Eleventh Annual Int. Conf. Pattern Recognition, Amsterdam, Netherlands, 1992, pp. 586-589. 214. Lii, Y., P. W. Palumbo and S. N. Srihari, “Use of Character Recognition and Address Syntax in Address Block

Location,” United States Postal Service Advanced Technology Conference, Wash. DC, Nov. 1992, pp. 1241-1255. 215. Srihari, S. N., “Model-based OCR,” DARPA Workshop Document Understanding, May 1992, Palo Alto, CA, 5 pages. 216. Srihari, S.N., “Next Generation USPS Address Recognition Unit,” Japanese Postal Technology Conference, Tokyo,

Japan, January 1992, 8 pages. 217. Srihari, S. N., E. Cohen, V. Govindaraju and A. Shekhawat, “Determining Delivery Point Codes on Handwritten

Addresses,” United States Postal Service Advanced Technology Conf., Wash. DC, November 1992, pp. 321-335. 218. Wong, P. K., T. K. Ho and S. N. Srihari, “Firm Recognition for Automatic Address Interpretation,” United States

Postal Service Advanced Technology Conference, Washington, DC, November 1992, pp. 757-770. 219. Cohen, E., J. J. Hull and S. N. Srihari, “Understanding Spatially Structured Handwritten Text,” International

Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 984-992 220. Govindaraju, V., and S. N. Srihari, “Separating Handwritten Text from Overlapping Non-textual Contours,” Second

International Workshop Frontiers Handwriting Recognition (IWFHRII), Bonas, France, September 1991, pp. 229-240. 221. Ho, T. K., J. J. Hull and S. N. Srihari, “Word Recognition with Multi-level Contextual Knowledge,” First International

Conference on Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 905-916. 222. Hull, J. J., T. K. Ho, J. Favata, V. Govindaraju and S. N. Srihari, “Combination of Segmentation-based and Holistic

Handwritten Word Recognition Algorithms,” Int. W. Front. H. Recog. (IWFHRII), Bonas, Fr., Sept.1991, pp. 111-122. 223. Lam, S., and S. N. Srihari, “Frame-Based Knowledge Representation for Multi-Domain Document Layout Analysis,”

IEEE Conference on Systems, Man and Cybernetics, Charlottesville, VA, September 1991. 224. Lam, S., and S. N. Srihari, “Multi-domain Document Layout Understanding,” First International Conference on

Document Analysis and Recognition (ICDAR91), St. Malo, France, September 1991, pp. 112-120. 225. Wang, D., and S. N. Srihari, “Analysis of Form Images,” First International Conference on Document Analysis and

Recognition (ICDAR91), St. Malo, France, September 1991, pp. 181-191. 226. Cohen, E., J. J. Hull and S. N. Srihari, “Reading and Understanding Handwritten Addresses,” United States Postal

Service Advanced Technology Conference, Washington, DC, November 1990, pp. 821-836. 227. Cullen, P. B., T. K. Ho, J. J. Hull, M. Prussak and S. N. Srihari, “Contextual Analysis of Machine-printed Addresses,”

United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 779-793. 228. Demjanenko, V., Y. C. Shin, R. Sridhar, P. W. Palumbo and S. N. Srihari, “Real-time Connected Component Analysis

for Address Block Location,” United States Postal Service Adv. Tech. Conf., Wash. DC, Nov. 1990, pp. 1059-1066. 229. Favata, J. T., and S .N. Srihari, “Recognition of Handwritten Words for Address Reading,” United States Postal Service

Advanced Technology Conference, Washington, DC, November 1990, pp. 191-205. 230. Govindaraju, V., S. N. Srihari and D. B. Sher, “A Computational Model for Face Location,” Third International

Conference Computer Vision, Osaka, Japan, December 1990, pp. 718-721. 231. Ho, T. K., J. J. Hull and S. N. Srihari, “Combination of Structural Classifiers,” Workshop on Structural and Syntactic

Pattern Recognition, Murray Hill, NJ, June 1990, pp. 123-136. 232. Ho, T. K., J. J. Hull and S. N. Srihari, “A Word Shape Analysis Approach to Recognition of Degraded Word Images,”

United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 217-229. 233. Lam, S., D. Wang and S. N. Srihari, “Reading Newspaper Text,” Tenth International Conference on Pattern

Recognition, Atlantic City, NJ, June 1990, pp. 703-705. 234. Lee, D. S., S. Lam and S. N. Srihari, “A Structural Approach to Recognize Hand-printed and Degraded Machine-

printed Characters,” Workshop on Structural & Syntactic Pattern Recognition, Murray Hill, NJ, June 1990, pp. 256-272.

235. Palumbo, P. W., J. Soh and S. N. Srihari, “Real-time Address Block Location Using Pipelining and Multiprocessing,” United States Postal Service Advanced Technology Conference, Washington, DC, November 1990, pp. 73-87.

236. Srihari, S. N., “High-performance Reading Machines,” Vision Interface '90, Halifax, Nova Scotia, Canada, May 1990, pp. 150-155.

237. Srihari, S. N., “High-performance Reading Machines,” Conference on Knowledge-Based Computer Systems, Pune, India, December 1990, pp. 489-492.

238. Srihari, S. N., “Reading Unconstrained Handwriting with Bounded Context,” International Workshop on Frontiers of Handwriting Recognition, Montreal, Canada, April 1990, pp. 109-116.

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239. Chen, J. S., and S. N. Srihari, “Candidate Ordering and Elimination in Model-based Fault Diagnosis,” Eleventh International Joint Conference on Artificial Intelligence, Detroit, MI, August 1989, pp. 1363-1368.

240. Govindaraju, V., S. Lam, D. Niyogi, D. B. Sher, R. K. Srihari, S. N. Srihari and D. Wang, “Newspaper Image Understanding,” Conference on Knowledge-Based Computer Systems, Bombay, India, December 1989, pp. 375-386.

241. Govindaraju, V., D. B. Sher, R. K. Srihari and S. N. Srihari, “Locating Human Faces in Newspaper Photographs,” IEEE-CS Conference on Computer Vision Pattern Recognition, San Diego, CA, June 1989, pp. 549-555.

242. Soh, J., P. W. Palumbo and S. N. Srihari, “Real Time Recognition of Address Blocks on Mail Pieces,” Optical Society of America Topical Meeting: Image Understanding and Machine Vision, Cape Cod, MA, June 1989, pp. 10-13.

243. Srihari, S. N., “Feature Extraction for Address Block Location,” From Pixels to Features: COST-13 Workshop, Bonas, France, 1989, pp. 261-274.

244. Hull, J. J., S. N. Srihari, E. Cohen and C. L. Kuan, “A Blackboard-Based Approach to Handwritten ZIP Code Recognition,” United States Postal Service Advanced Technology Conference, Washington DC, May 1988, pp. 1018-1032.

245. Hull, J. J., S. N. Srihari, E. Cohen, L. Kuan, P. Cullen and P. W. Palumbo, “A Blackboard-Based Approach to Handwritten ZIP Code Recognition,” Ninth International Conference on Pattern Recognition, Rome, Italy, November 1988, pp. 111-113.

246. Kuan, L., and S. N. Srihari, “A Stroke-Based Approach to Handwritten Numeral Recognition,” United States Postal Service Advanced Technology Conference, May 1988, pp. 1033-1041.

247. Niyogi, D., and S. N. Srihari, “Expert Systems and Pattern Recognition,” Seventh Biennial Convention of South East Asia Regional Computer Confederation, November 1988, pp. 119-128.

248. Palumbo, P. W., and S. N. Srihari, “Advanced Computer Architectures for Address Block Location,” United States Postal Service Advanced Technology Conference, Washington DC, May 1988, pp. 318-326.

249. Pawlicki, T. F., D.-S. Lee, J. J. Hull and S. N. Srihari, “Neural Network Models and Their Application to Handwritten Digit Recognition,” IEEE International Conference on Neural Networks, San Diego, CA, July 1988, pp. 63-70

250. Pawlicki, T. F., D.-S. Lee, J. J. Hull and S. N. Srihari, “Neural Network Models and Their Application to Handwritten Digit Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, May 1988, pp. 751-767.

251. Wang, C.-H., P. W. Palumbo and S. N. Srihari, A Framework for Object Recognition and Its Application to Locating Address Blocks on Mail Pieces,” AAAI Blackboard Workshop, St. Paul, MN, August 1988.

252. Wang, C.-H., P. W. Palumbo and S. N. Srihari, “Object Recognition in Visually Complex Environments: Architecture for ABLS,” Ninth International Conference on Pattern Recognition, Rome, Italy, November 1988, pp. 365-367.

253. Wang, C.-H., P. W. Palumbo and S. N. Srihari, “Performance Evaluation of a System to Recognize Address Blocks on Mail Pieces,” AAAI Seventh National Conference on Artificial Intelligence, Minneapolis, MN, August 1988, pp. 837-841.

254. Wang, C.-H., P. W. Palumbo, S. M. Tylock, J. J. Hull and S. N. Srihari, “Performance of a System to Locate address Blocks on Mail Pieces,” United States Postal Service Advanced Technology Conference, Washington, DC, May 1988, pp. 705-718.

255. Geller, J., M.-R Taie, S. C. Shapiro and S. N. Srihari, “Device Representation and Graphics Interfaces of VMES,” Application of AI in Engineering, Cambridge, MA, August 1987, pp. 15-28.

256. Hull, J. J., and S. N. Srihari, “Knowledge Utilization in Handwritten ZIP-Code Recognition,” Tenth International Joint Conference on Artificial Intelligence, Milan, Italy, August 1987, pp. 848-850.

257. Niyogi, D., and S. N. Srihari, “Using a Blackboard Architecture for Control in a Knowledge-based Document Understanding System,” SPIE: Applications of Artificial Intelligence, Orlando, FL, 1987, pp. 319-326.

258. Srihari, S.N., “Document Image Analysis: An Overview,” SPSE’s 40th Annual Conference and Symposium on Hybrid Imaging Systems, Rochester, May 1987, pp. 28-31.

259. Srihari, S. N., and R. Bozinovic, “A Multi-level Perception Approach to Reading Cursive Script,” Tenth International Joint Conference on Artificial Intelligence, Milan, Italy, August 1987, pp. 844-847.

260. Taie, M.-R., and S. N. Srihari, “Modeling Connections for Circuit Diagnosis,” Third Conference on Artificial Intelligence Applications, Orlando, FL, February 1987, pp. 81-86.

261. Hull, J. J., and S. N. Srihari, “A Computational Approach to Shape Recognition: Hypothesis Generation and Testing,” IEEE-CS Conference on Computer Vision Pattern Recognition, Miami Beach, FL, June 1986, pp. 156-161.

262. Hull, J. J., and S. N. Srihari, “Use of External Information in ZIP-Code Recognition,” United States Postal Service Advanced Technology Conference, Washington, DC, October 1986, pp. 361-370.

263. Niyogi, D., and S. N. Srihari, “A Knowledge-Based System for Document Image Understanding,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 128-134.

264. Niyogi, D., and S. N. Srihari, “A Rule-Based System for Document Understanding,” AAAI Fifth National Conference on Artificial Intelligence, Philadelphia, PA, August 1986, pp. 789-793.

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265. Palumbo, P. W., and S. N. Srihari, “Text Parsing Using Spatial Information for Recognizing Addresses in Mail Pieces,” Eighth International Conference on Pattern Recognition, Paris, France, October 1986, pp. 1068-1070.

266. Palumbo, P. W., P. Swaminathan and S. N. Srihari, “Document Image Binarization: Comparison of Techniques,” SPIE Applications of Digital Image Processing IX, San Diego, August 1986, pp. 278-285.

267. Shapiro, S. C., S. N. Srihari, M-R. Taie and J. Geller, “VMES: A Network-Based Versatile Maintenance Expert System,” Applications of AI to Engineering, Southampton, England, April 1986, pp. 925-936.

268. Srihari, S. N., “Document Image Understanding,” ACM-IEEE C/S Fall Joint Computer Conference, Dallas, TX, November 1986, pp. 87-96.

269. Srihari, S. N., J. J. Hull, P. W. Palumbo and C.-H. Wang, “Address Block Location: Specialized Tools and Problem-Solving Architecture,” United States Postal Service Advanced Technical Conference, Washington, DC, October 1986, pp. 116-131.

270. Srihari, S. N., and C.-H. Wang, “A Blackboard Architecture for Object Recognition,” SPIE Proceedings: Automated Inspection and Measurement, Cambridge, MA, October 1986, pp. 224-232.

271. Srihari, S. N., and G. W. Zack, “Document Image Analysis,” Eighth International Conference on Pattern Recognition, Paris, France, October 1986, pp. 434-436.

272. Taie, M. R., and S. N. Srihari, “Device Modeling for Fault Diagnosis,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 144-150.

273. Taie, M. R., S. N. Srihari, J. Geller and S. C. Shapiro, “Device Representation Using Instantiation Rules and Structural Templates,” Canadian Artificial Intelligence Conference, Montreal, May 1986, pp. 124-128.

274. Wang, C.-H., and S. N. Srihari, “Object Recognition in Structured and Random Environments: Locating Address Blocks in Mail Piece Images,” AAAI Fifth National Artificial Intelligence Conference, Philadelphia, PA, August 1986, pp. 1133-1137.

275. Xiang, Z., and S. N. Srihari, “Diagnosis Based on Empirical and Model Knowledge,” Sixth International Workshop Expert Systems, Avignon, France, April 1986, pp. 835-848. (Received award for “Outstanding Communication.”)

276. Xiang, Z., and S. N. Srihari, “Diagnosis Using Multi-level Reasoning,” Second Expert Systems in Government Symposium, McLean, VA, October 1986, pp. 151-158.

277. Kumar, R., and S. N. Srihari, “An Expert System for the Interpretation of Cranial CT Scan Images,” Expert Systems in Government Symposium, McLean, VA, October 1985, pp. 548-557.

278. Xiang, Z., J. G. Chutkow, S. C. Shapiro and S. N. Srihari, “Representation of Spatial Structure and Function in Diagnosis,” Second Conference on Artificial Intelligence Applications, Miami Beach, FL, December 1985, pp. 223-228.

279. Xiang, Z., and S. N. Srihari, “Graphics Interfaces to a Neurological Diagnosis System,” National Computer Graphics Association Conference, Dallas, TX, April 1985, pp. 215-222.

280. Xiang, Z., and S. N. Srihari, “Spatial Structure and Function Representation in Diagnostic Expert Systems,” Fifth International Workshop on Expert Systems, Avignon, France, May 1985, pp. 191-206.

281. Xiang, X., S. N. Srihari, S. C. Shapiro and J. G. Chutkow, “A Modeling Scheme for Diagnosis,” Expert Systems in Government Symposium, McLean, VA, October 1985, pp. 538-547.

282. Bozinovic, R., and S. N. Srihari, “Knowledge-based Cursive Script Interpretation,” Seventh International Conference on Pattern Recognition, Montreal, Canada, August 1984, pp. 774-777.

283. Hardas, D., and S. N. Srihari, “An Architecture for Progressive Refinement of Grey-level 3-D Images,” Seventh International Conference on Pattern Recognition, Montreal, Canada, August 1984, pp. 224-226.

284. Xiang, Z., and S. N. Srihari, “Representation of Structure in Neurological Diagnosis,” International Conference Computers, Systems & Signal Processing, Bangalore, India, December 1984, pp. 1166-1169.

285. Xiang, Z., S. N. Srihari, S. C. Shapiro and J. G. Chutkow, “Analogical and Propositional Representations of Structure in Neurological Diagnosis,” First Conference on Artificial Intelligence Applications, Denver, CO, December 1984, pp. 127-132.

286. Bozinovic, R., and S. N. Srihari, “Use of Knowledge in Visual Interpretation of Cursive Script,” IEEE-SMC International Conference on Cybernetics and Society, Bombay, India, 1983, pp. 187-191.

287. Srisuresh, P., and S. N. Srihari, “A Shrinking Algorithm for 3-D Objects,” IEEE-CS Conference on Computer Vision and Pattern Recognition, Arlington, VA, 1983, pp. 392-393.

288. Bozinovic, R., and S. N. Srihari, “A String Correction Algorithm for Cursive Script Recognition,” Sixth International Conference on Pattern Recognition, Munich, West Germany, 1982, pp. 44-46.

289. Hull, J. J., and S. N. Srihari, “Comparison of Two Contextual Postprocessing Algorithms for Text Recognition,” IEEE-CS Conference Pattern Recognition and Image Processing, Las Vegas, NV, June 1982, pp. 146-151.

290. Srihari, S. N., “Hierarchical Data Structures and Progressive Refinement of 3-D Images,” IEEE-CS Conference on Pattern Recognition Image Processing, Las Vegas, NV, June 1982, pp. 485-490.

291. Srihari, S. N., and J. J. Hull, “Knowledge Integration in Text Recognition,” AAAI National Conference on Artificial Intelligence, Pittsburgh, PA, August 1982, pp. 148-151.

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292. Srihari, S. N., J. J. Hull and R. Choudhari, “Integration of Top-down and Bottom-up Knowledge in Text Error Correction,” AFIPS National Computer Conference, Houston, TX, June 1982, pp. 501-508.

293. Srihari, S.N., J.J. Hull and R. Choudhari, “An Algorithm for Integrating Diverse Knowledge Sources in Text Recognition,” ACM Conference on Office Information Systems, Philadelphia, PA, 1982, pp. 46-54.

294. Srihari, S. N., and J. Tindall, “Multiresolution Representation of Three-dimensional Objects,” IEEE-SMC International Conference Cybernetics and Society, Seattle, WA, October 1982, pp. 327-331.

295. Yau, M., and S. N. Srihari, “Convex Hulls from Hierarchical Data Structures,” Seventh Conference Canadian Man-Computer Communications Society, Waterloo, Ontario, June 1981, pp. 163-171.

296. Yau, M., and S. N. Srihari, “Recursive Generation of Hierarchical Data Structures for Multidimensional Digital Images,” IEEE-CS Conference Pattern Recognition and Image Processing, Dallas, TX, August 1981, pp. 42-44.

297. Srihari, S. N., “On the Complexity of Determining Equivalence of Decision Algorithms,” International Conference Cybernetics and Society, Cambridge, MA, October 1980, pp. 553-556.

298. S. N. Srihari, “Hierarchical Representations for Serial Section Images,” Fifth International Conference on Pattern Recognition, Miami Beach, FL, December 1980, pp. 1075-1080.

299. Srihari, S. N., “Pattern Classification with Composite Classes,” IEEE-CS Conference on Pattern Recognition and Image Processing, Chicago, IL, August 1979, pp. 173-180.

300. Srihari, S. N., T. Snabb and L. J. White, “An Algorithm for Determining Identity of Nearest-neighbor and Potential Function Decision Rules,” IEEE-CS Conference on Pattern Recognition and Image Processing, Chicago, IL, August 1979, pp. 63-70.

301. Srihari, S. N., J. K. Udupa and M. Yau, “Understanding the Bin-of-Parts,” International Conference on Cybernetics and Society, Denver, CO, October 1979, pp. 44-49.

9.5 United States Patents

1. Srihari, S. N., Y. C. Shin, et.al., Method and Apparatus for Analyzing and/or Comparing Handwritten and/or Biometric

Samples, United States Patent No. 7,580,551, Aug 29, 2009. 2. Shin, Y.-C., R. Sridhar, S. Srihari and V. Demjanenko, Local Adaptive Contrast Enhancement, United States Patent No.

5,524,070, June 4, 1996. 3. Govindaraju, V., D. Wang and S. N. Srihari, System for recognizing handwritten words of cursive script, United States

Patent No. 5,515,455, May 7, 1996. 4. Fenrich, R. K., and S. N. Srihari, A system for recognizing handwritten character strings containing overlapping and/or

broken characters, United States Patent Number 5,321,768, June 14, 1994. 5. Shin, Y.-C., R. Sridhar, V. Demjanenko, P. W. Palumbo and S. N. Srihari, Digital Data Memory Unit and Memory Unit

Array, United States Patent Number 5,257,220, October 26, 1993. 6. Kuan, L., J. J. Hull and S. N. Srihari, Method and apparatus for handwritten character recognition, United States Patent

Number 5,058,182, Oct. 15, 1991. 7. Srihari, S. N., and J. J. Hull, A system to achieve automatic recognition of linguistic strings, United States Patent Number

4,654,875, March 31, 1987. 9.6 Abridged Papers/Abstracts

1. Srihari, S.N., “Quantitative Assessment of Handwriting,” European Academy of Forensic Sciences Meeting, September

2003, p.59. 2. Srihari, S. N., “Postal Address Finding and Reading,” Electronic Imaging East 90, Boston, MA, 1990, pp. 208-211. 3. Pawlicki, T., and S. N. Srihari, “Connectionist Neural Network Approach,” Workshop on Systems and Signal

Processing, Bangalore, India, January 1988. 4. Shapiro, S. C., S. N. Srihari, J. Geller, and M.-R. Taie, “A Fault Diagnosis System Based on an Integrated Knowledge

Base,” IEEE Software, March 1986, pp. 48-49. 5. Srihari, S. N., W. I. Rapaport and D. Kumar, “Natural Language Processing Using SNePS and Its Relevance to Sanskrit

Grammatical Analysis,” First National Conference on Knowledge Representation and Inference in Sanskrit, Bangalore, India, December 1986.

6. Xiang, Z., and S. N. Srihari, “Diagnosis Based on Empirical and Model Knowledge,” IEEE Software, March 1986, pp. 50-51. (Computation and its application to handwritten digit recognition, Indo-U.S.)

7. Shapiro, S. C., S. N. Srihari, M.-R. Taie and J. Geller, “Development of an Intelligence Maintenance Assistant,” SIGART Newsletter, 92, April 1985, pp. 48-49.

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8. Srihari, S. N., J. J. Hull and R. Choudhari, “An Algorithm for Integrating Diverse Knowledge Sources in Text Recognition,” ACM Conference Office Information Systems, Philadelphia, 1982, pp. 46-54.

9. Herman, G. T., S. N. Srihari and J. K. Udupa, “Detection of Changing Boundaries in Two and Three Dimensions,” Workshop Computer Analysis Time-Varying Imagery, Philadelphia, 1979, pp. 14-16.

10. Srihari, S. N., “An Efficient Measurement Selection for Invariant Pattern Recognition,” Fourth International Cybernetics and Systems Congress, Amsterdam, Netherlands, 1978, pp. 67-68.

11. Srihari, S. N., “Use of Majority-vote in N-Sample Decision-making,” IEEE International Symposium Information Theory, Ithaca, NY, 1977, p. 29.

12. Srihari, S. N., and L. J. White, “Statistical Classifier Design for Aircraft Identification,” Third ACM Computer Science Conference, Washington, DC, 1975, p. 57.

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10. GRANTS AND CONTRACTS AS PRINCIPAL INVESTIGATOR 2017-2002 Project Title Funding Source Amount Period

1 Development of Individual Handwriting Characteristics in 1800 Students: Statistical Analysis and Likelihood Ratios That Emerge Over an Extended Period of Time

National Institute of Justice (NIJ)/State of Minnesota

$235,000 2012-15

2 Statistical Characterization of Handwriting Characteristics National Institute of Justice (NIJ)

$425,077 2010-12

3 Quantitative Measures in Support of Latent Print Comparison NIJ $498,784 2009-2012

4 Computational Methods for the Assessment of Handwriting NIJ $668,806 2004-10 5 Quantitative Assessment of the Individuality of Friction Ridge

Patterns NIJ $596,478 2005-08

6 Analysis of Footwear Impression Evidence NIJ $350,172 2007-10 6 Recognition of Handwritten Words in School Essays using

Conditional Random Fields National Science Foundation (NSF)

$100,000 2007-08

7 IES and Other Support for APPS programs United States Postal Service (USPS)

$405,955 2007-08

8 Comparative evaluation of DQI and other Recognition Programs USPS $462,000 2007-08

9 Complex Document Information Processing DOE (Batelle subcontract) $12,820 2005-06

10 Handwriting Recognition Technology Assessment for Arabic and Chinese

CIA $45,000 2006

10 Creation of Arabic Corpus In-Q-Tel $50,000 2004-05 11 Digital Camera use in Barcode Imaging USPS $409,867 2003-07 12 Image Collection and Truthing USPS $3,906,541 2003-07 13 Flats Image Collection and Truthing USPS $1,499,471 2003-07 14 Alternate Keying Strategies USPS $165,000 2004-05 15 Reply Card Scanning USPS $210,000 2003-04 16 Quantitative Assessment of the Discriminatory Power of

Handwriting and Validating Identification Procedures NIJ $298,237 2002-04

17 Personal Name Lookups USPS $1,204,000 2001-03 18 Comparison Study of Barcodes USPS $470,000 2003-05 19 UK Address Interpretation Lockheed Martin (LM) $15,000 2003 20 Image evaluation Systems-Flats USPS $340,000 2002-03 21 Micropayment Processing USPS $1,204,000 2001-03 22 HWAI Plus Siemens $317,000 2002-03 23 AAPS Parcel Address Recognition Siemens $90,000 2002 24 Canadian Postcode Interpretation Siemens $50,000 2000-01 25 Handwritten Address Interpretation Siemens $300,000 2000-01 26 Canadian Postcode Recognition System House Ltd $10,000 1994 27 Mailpiece Library USPS $190,000 2002 28 Evaluation of Identification Codes USPS $133,000 2001 29 Return Merchandise System USPS $300,000 2001-02 30 Image Evaluation System Development USPS $1,850,583 199-03 31 Information-based Indicia USPS $300,000 1999-01 32 UK Address Interpretation LM $1,245,000 2000-02 SUB-TOTAL $17,697,714

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2001-1997

32 RCR/HWAI LM $660,000 2000-0133 SDMM Directory Generation and Validation LM $44,235 2000-0134 Image Truthing USPS $1,102,000 2000-0235 Address Interpretation Systems for UK Program LM $1,224,367 200036 Handwriting Identificiation: Validity of

Individuality and Computer-assisted ProceduresNIJ $428,328 1999-01

37 HWAI Control Strategy LM $129,190 1999-0038 PROZE Character Recognition Improvements LM $128,395 1999-0039 VRR Word Recognition Improvements LM $42,590 1999-0040 Last Line and Foreign Processing LM $101,417 1999-0041 RCR/HWAI Improvements LM $503,480 1999-0042 UKAI Initial Tasks-Parsing and Resolution LM $152,442 1999-0043 Truthing for Recognition Improvement Plan USPS $75,000 1999-0044 Truthing and Analysis of Mailpiece Images USPS $290,636 1999-0045 New Image Evaluation System USPS $395,257 1999-0046 Implementation of Semi-automated Encoding USPS $185,261 1999-0047 Sender Information Processing USPS $134,167 1999-0048 Equipment Grant USPS $46,200 1999-0049 Travel Grant USPS $34,103 1999-0050 HWAI of Australian Addresses LM $218,333 199951 Last Line, Foreign Processing LM $100,412 199952 Image Processing Functions LM $69,156 199953 Control Strategy LM $101,468 199954 Word Recognizer LM $46,541 199955 New Character Recognition LM $45,019 199956 HWAI of Australian Addresses LM $319,959 199957 Gray Scale Image Processing USPS $790,000 1998-0058 Address Truthing Analysis USPS $1,424,641 1998-0059 HWAI Control Structures LM $79,200 1998-9960 Database Enhancement LM $52,500 1998-9961 New Parsing Techniques LM $77,500 1998-9962 New Word Recognition Techniques LM $132,000 1998-9963 New Character Recognition LM $88,000 1998-9964 RCR/HWAI Improvements LM $400,000 1998-9965 HWAI porting to NT LM $28,586 1998-9966 HWAI Recognition Co-processor USPS $650,000 199867 HWAI of Australian Addresses LM $1,144,418 1997-9868 RCR/HWAI Integration LM $1,500,000 1997-9869 HWAI PC Integration USPS $494,924 1997-9870 HWAI/RCR Research LM $550,860 1997-9871 HWAI/RCR LM $407,686 1997

SUB-TOTAL $14,398,271

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1997-1983

Grand Total = $ 64,307,889

72 Directory Compression USPS $37,959 199773 Image Analysis USPS $40,722 199774 Recognition through Evolutionary

ComputingUSPS $57,410 1997

75 HWAI PC Porting USPS $215,497 199776 HWAI RCR USPS $585,924 1996-9777 HWAI/RCR Integration LM $596,474 1996-9778 HWAI PC Integration Task 1 USPS $255,076 1996-9779 HWAI Integration Testing USPS $99,750 1996-9780 Improvements in HWAI USPS $2,510,681 1993-9681 Reply Card Processing-Phase III USPS $1,388,534 1995-9682 Reply Card Processing PIMS USPS $1,435,416 1993-9583 Handwritten Text Recognition National Security

Agency (NSA)$532,939 1994-96

84 Document Analysis and Recognition Xerox Corp $70,000 1993-0085 Recognitiion of Handprinted Forms Reader's Digest $10,000 199486 Interactive Service Research Support USPS $1,299,519 1993-9687 CEDAR Supplemental Activities USPS $750,000 1991-9588 HWAI Research USPS $3,256,837 1991-9489 PENMAN: Handwritten OCR NSA $423,536 1994-9690 Japanese Optical Character Recognition NSA $805,706 1993-9691 Universal Message Routing System USPS $988,128 1993-9692 Reply Card Processing USPS $2,781,416 1993-9793 Implementation for RCR Application USPS $2,209,688 1993-9594 SCRIPS; Name and Address Block Reader Grumman Data

Systems$1,960,723 1994-96

95 CEDAR Supplementary Funds USPS $750,000 1992-9396 Laboratory Address Recognition Unit USPS $1,000,000 1991-9297 Machine-Printed Character Recognition USPS $1,724,687 1991-9298 Handwritten Address Interpretation USPS $3,000,000 1991-9499 Knowledge-Based Document Image

UnderstandingNSF $185,000 1991-93

100 Recognition of Handwritten Address ZIP Codes

USPS $1,750,000 1986-90

101 Advanced Address Block Location USPS $690,000 1985-88102 Expert Automated Maintenance System

(Shaprio, PI)RADC $819,000 1984-89

103 AI-Graphics Interface for Rule-based system (Shapiro, PI)

RADC $52,266 1984-85

104 Advanced Character Recognition USPS $248,000 1984-85105 Contextual Algorithms for Text

RecognitionNSF $54,800 1980-83

SUB-TOTAL $32,585,688

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11. DOCTORAL STUDENTS SUPERVISED Most recent listed first. 1. Jun Chu, Representation Learning and Data Augmentation in Forensic Comparison. 2018, Facebook, Mountainview,

CA. 2. Junfei Wang, Improving Large-Scale Recommendation Systems with Contextual Signals, 2017, Facebook, Seattle, WA. 3. Zhen Xu, Using Social Dynamics to Make Individual Predictions: Variational Inference with Stochastic Kinetic Model,

2016, Google, Mountain View, CA. 4. Gang Chen, Sequential Classification using Deep Learning, 2015 Amazon, Seattle, WA. 5. Yu Liu, A Probabilistic Similarity Measure for Latent Fingerprints, 2014. EPIC Systems, Madison, WI. 6. Yi Tang, Evaluating the Probability of Identification in Forensic Science, 2012, Microsoft, Redmond, WA. 7. Chang Su, Machine Learning in Fingerprint Probability Models, Computer Science and Engineering 2011. Member of

Technical Staff, E-bay, Santa Clara, CA. 8. Harish Srinivasan, Machine Learning Approaches to Person Identification with Applications to Forensic Document

Analysis, 2008. Amazon, Seattle, WA. 9. Chen Huang, Content-based Handwritten Document Indexing and Retrieval, 2008 10. Gregory Ball, Arabic Handwriting Recognition using Machine Learning Approaches, 2007, CEDAR. 11. Siyuan Chen, Signature Verification using Flexible Template Matching Approaches, 2006. 12. Catalin Tomai, A Computational Theory of Visual Word Recognition, 2003. Microsoft Corp, Seattle. 13. Bin Zhang, Handwriting Pattern Matching and Retrieval with Binary Features, 2003. Icahn School of Medicine, New

York, NY. 14. Sung-Hyuk Cha, Use of Distance Measures in Handwriting Analysis, 2001. Pace University. 15. Minchul Jung, Font Classification ad Character Segmentation for Postal Address Reading, 2001. 16. Jaehwa Park, Hierarchical Character Recognition and Its Use in Word/Phrase Recognition, 1999. University, Korea. 17. Uma Mahadevan, Robust Vision through Imperfect Eyes: A System for Processing City, State and ZIP Code Fields in

Handwritten Addresses., 1998. 18. Jung Soh, A Theory of Document Object Locator Combination, 1998. Defense Research Institute, South Korea. 19. Jeon-Man Park, Address Block Location System Using Multi-Resolution State-Space Search, 1997. Samsung Data

Systems, South Korea. 20. Ajay Shekhawat, A Framework for Handwritten Document Recognition, 1997, Yahoo, Inc, Mountain View, CA. 21. Gyeonghwan Kim, Recognition of Offline Handwritten Words and Its Extension to Phrase Recognition, 1996. Sogang

University, South Korea. 22. Sriganesh Madhvanath, Histolic Techniques for Handwritten Word Recognition Engines, Computer Science; 1996. ,

IBM, Almaden Research Center, Almaden, CA. 23. Dar-Shyang Lee, A Theory of Classifier Combinations: The Neural Network Approach, Computer Science; 1995.

Google, Inc., Mountainview, CA. 24. Jenchyou Lii, Use of Character Recognition and Syntax in Locating Address Paragraphs in Complex Documents, 1995.

ESS, CA. 25. Ying Liu, Document Image Binarization Based on Texture Analysis, 1995. ADT, St. Louis, MO. 26. Stephen Lam, A Computational Framework for Adaptive Reading in Document Image Understanding, 1994.

Enterpreneur, Hong Kong.. 27. Debashish Niyogi, A Knowledge-Based Approach to Deriving Logical Structure from Document Images, 1994. Oracle

Corporation, San Mateo, CA. 28. Geetha Srikantan, Image Sampling Rate and Pattern Recognition, 1994. Sun Microystems, Mountain View, CA. 29. Xin Zhao, Machine-Printed Word Recognition Using Ideal Word Patterns and Lexical Reduction; 1994. Oracle

Corporation, San Mateo, CA. 30. Mou-Yen Chen, Handwritten Word Recognition Using Hidden Markov Models, 1993. 31. John Favata, Recognition of Handwritten Words Using Multi-Level Generate-and-Test, 1993. SUNY College, Buffalo,

NY. 32. Jiah-Shing Chen, A Probabilistic Theory of Model-Based Diagnosis, 1992. Chungliu University, Taiwan. 33. Edward Cohen, Interpreting Handwritten Text in a Structured Environment, Computer Science; 1992. Software

Division, Tritech Technologies. 34. Venugopal Govindaraju, Computational Theory for Locating Human Faces in Photographs, 1992. SUNY at Buffalo. 35. Tin-Kam Ho, Theory of Multiple Classifier Systems and Its Application to Visual Word Recognition, Computer Science;

1992. Lucent Bell Labs, Murray Hills, NJ.

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36. Jonathan J. Hull, A Computational Theory of Visual Word Recognition, Computer Science; 1988. Ricoh Corporation, Menlo Park, CA.

37. Ching-huei Wang, Object Recognition in a Visually Complex Environment and Its Application to Locating Address Blocks. Boeing, Seattle, WA

38. Zhigang Xiang, Multi-Level, Model-Based Diagnostic Reasoning, Computer Science; 1988. Queens College, CUNY, New York, NY.

39. Mingruey R. Taie, Representation of Device Knowledge for Versatile Fault Diagnosis, Computer Science; 1987. AT&T Bell Labs, Middletown, NJ.

40. Radmilo M. Bozinovic, Recognition of Cursive Script: A Case of Multi-Level Perception, Computer Science; 1985. Apple Computer Corporation, Cupertino, CA.

41. Mann-May Yau, Hierarchical Representation of Three Dimensional Digital Objects, Computer Science; 1983. AT&T Bell Labs, Middletown, NJ.

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12. INVITED LECTURES AND CONFERENCE PRESENTATIONS

Date

Title Organization/Auspices Location

Mar 11, 2020 July 26, 2019 June 21, 2019 April 10, 2019 Feb 20, 2019 Feb 18, 2019 Oct 5, 2018 July 20, 2018 July 17, 2018 May 9, 2018 Jun 4-25, 2018 Jan 10, 2018 Aug 3, 2017 June 25, 2017 June 5, 2017 April 25, 2017 June 1, 2016 Mar 24, 2014 Jan 13, 2014 Oct 2, 2013 June 4, 2013 May 21, 2013 Feb 21, 2013

Probabilistic Knowledge Graphs Explainable AI Artificial Intelligence Explainable AI Modern Machine Learning Artificial Intelligence Artificial Intelligence Artificial Intelligence Artificial Intelligence and Deep Learning Artificial Intelligence and Deep Learning Deep Learning Lecture Series Representation Learning Short course on Deep Learning Artificial and Machine Intelligence Artificial Intelligence Machine Learning: Overview Towards a Forensic Data Science Uncertainty in forensic identification Learning Causality Evaluating Likelihood Ratios in Forensic ID Interactive Writer Ident-CEDAR-FOX system Writer Id of Historical Documents Statistical Char of Handwritten Items

NIST Ontology Summit Deep Learning Summer School IISc Global Summit NIST Ontology Summit National Communications Conf University of Mysore Endo Lec Buffalo Niagara Medical Center Ek Step Ind. Inst Science, Public Lecture Peace Tech Summit Indian Institute of Science Int Conf Pattern Recog and AI Indian Inst of Info. Technology Data Intelligence: Practioner ML National Institute of Standards Praxair NIST IBM Research Labs. Biometrics: Theory, Apps Syst NIST Advanced Pat. Recog & Historical Handwrit. Wkshp AAFS

Online Warsaw, Poland Palo Alto, CA Gaithersberg, MD Bangalore, India Mysore, India Buffalo, NY Bangalore, India Bangalore, India Washington, DC Bangalore, India Bangalore, India Allahabad, India McLean Va Gaithersburg, MD Buffalo, NY Gaithersburg, MD Valletta, Malta Bangalore, India Washington DC Gaithersburg, MD Erlangen, Germany Washington DC

Feb 5, 2013 Combining Evidence using Likelihood Ratios in Writer Verification

Document Recognition and Retrieval Conference San Francisco, CA

Nov 21, 2012 Learning Probabilistic Graphical Models from Data Indian Institute of Science Bangalore, India

Nov 13, 2012 Methods for Incorporating Evidence into Posterior Scoring of Hypotheses

International Conference on Pattern Recognition Tsukuba, Japan

Sept 21, 2012 Evaluating the Probability of Identification in the Forensic Sciences

International Conference on Frontiers in Handwriting Recognition

Bari, Italy

Jan 28, 2012 Questioned Document Workflow: Example of the Lindbergh case

Document Recognition and Retrieval Conference San Francisco, CA

Dec 19, 2011 Probabilistic Graphical Models and Social Networks

Indo-US Workshop of Large Scale data Analytics and Intelligent Services

Bangalore, India

Sept 25,2011 Probabilistic Graphical Models in Machine Learning Department of Biostatistics Buffalo, NY

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Sept 18, 2011 Probabilistic Graphical Models in Machine Learning

International Conference on Document Anal. Recognition Beijing, China

April 28, 2011 Probabilistic Graphical Models in Machine Learning (I) Acharya Institute of Technology Bangalore, India

Jan 28, 2011 Statistical Characterization of Handwriting Characteristics using Automated Tools

Document Recognition and Retrieval Conference San Francisco, CA

Dec 6, 2010 Evaluation of Rarity of Fingerprints (Poster) Neural Information Processing Systems (NIPS) Vancouver, BC

Nov 16-18, 2010

Writer Verification of Historical Documents among Cohort Writers

Int Conf on Frontiers in Handwriting Recognition Kolkata, India

Aug, 2010 Latent Fingerprint Core point prediction using Gaussian Processes

International Conference on Pattern Recognition Istanbul, Turkey

Aug 6-8, 2010 Impression and Pattern Evidence Symposium (I) NIJ Clearwater Beach,

FL

July 16, 2010 Content-Based Retrieval OF Footwear Images (I) Indian Institute of Science Bangalore, India

July 15, 2010 Statistics and data Mining (I) Amrita University Bangalore, India

June 14, 2010 Impression Evidence: Strengthening the Disciplines through Research - Panel (I) NIJ Conference Arlington, VA

May 7, 2010 Computational Forensics (I) Computational Modeling of Objects in Images(CompImage ) Buffalo, NY

Mar 10, 2010 Software Tools for Crime Scene Investigation (I)

Gifted Math Program 25th Anniversary Buffalo, NY

Jan 29, 2010 Probability Models for Pattern and Impression Evidence (I) DOJ Indigent Symposium Washington, DC

Jan 21, 2010 Comparison of Historical Documents for Writership

SPIE Document Recognition and Retrieval Conference San Jose, CA

Dec 14, 2009 Machine Learning (I) Infosys Bangalore, India

Dec 11, 2009 Gaussian Processes: Tutorial and Applications (I)

Indian Institute of Science (School of CSA) Bangalore, India

Dec 11, 2009 Machine Learning and Pattern Recognition (I)

Adobe India Distinguished Lecture Bangalore, India

Dec 7, 2009 Machine Learning (I) National University of Malaysia Putrajaya, Malaysia

Dec 6, 2009 Recent Developments in Pattern Recognition and Machine Learning

Int Conf Soft Computing and Pattern Recognition Malacca, Malaysia

Dec 4, 2009 Computational Forensics (I) University of Putra Putra, Malaysia

Dec 1, 2009 Document Analysis and Recognition (I) University of Technology Malaysia Skudai, Malaysia

Sept 29, 2009 Computational Forensics (I) National Institute of Justice Washington D.C.

Aug18, 2009 Computational Analysis of Shoe-print Images (I)

International Association for Identification Tampa, FL

August 13-14, 2009

1. Discriminability of Fingerprints of Twins 2. Bayesian Signature Verification, 3. Individuality of Fingerprints

International Workshop on Computational Forensics (Netherlands Forensic Institute)

The Hague, The Netherlans

July 26, 2009 Semi-supervised Learning for Handwriting Recognition

International Conference on Document Analysis and Recognition

Barcelona, Spain

July 2, 2009 Computational Methods for Analysis of Shoe-print Evidence (I) Foster & Freeman Evesham, England

June 30, 2009 Writer Verification and Identification (I) Telecom Paris Tech Paris, France

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April 16, 2009 Case-work with CEDAR-FOX (I) Southeast Association of Forensic Document Examiners Atlanta, GA

April 13, 2009 Generative Models and Probability Evaluation in Forensics Indian Institute of Science Bangalore, India

April 8, 2009 Machine Learning in the Oil Industry (I) Saudi ARAMCO Dhahran, Saudi Arabia

April 4-7, 2009

Machine Learning Short Course (I) King Fahd University of Petroleum and Minerals

Dhahran, Saudi Arabia

March 9, 2009 Probability of Random Correspondence in Fingerprints (I) San Jose State University San Jose, CA

February 19, 2009

Individuality of Handwriting: A Twin’s Study (I)

American Academy of Forensic Sciences Denver, CO

January 20, 2009

Comparison of Statistical Models for Writer Verification

Document Recognition and Retrieval XVI San Jose, CA

December 9, 2008

Generative Models for Fingerprint Individuality using Ridge Models

International Conference on Pattern Recognition Tampa. FL

December 3, 2008

Language Independent Word Spotting in Scanned Docuemnts

Asia-Pacific Conference on Digital Libraries Bali, Indonesia

October 23, 2008

Artificial Intelligence in the Post Office and the Police Department (I) Telcordia Piscataway, NJ

September 24, 2008

Machine Learning using Bayesian Approaches (I) Indian Institute of Science Bangalore, India

September 16, 2008

Automatic Verification of Handwritten Arabic

International Workshop on Document Analysis Systems Nara, Japan

August 20, 2008

Computational Approaches to Shoeprint Verification (I)

International Association for Identification Louisville, KY

July 21, 2008 Panel on “Confirmation Bias in Fingerprint Examination” (I)

National Institute of Justice Conference Arlington, VA

June 1, 2008 Computational Forensics Netherlands Forensic Institute The Hague, The Netherlands

May 29, 2008 Machine Learning: New Paradigms and Perspectives (I)

Lund University Mathematical Sciences Lund, Sweden

May 27, 2008 Computational Forensics (I) Grojvik University Grojvik, Norway

May 26, 2008 Computational Forensics (I) Kripos Oslo, Norway

April 30, 2008 Machine Learning: New Paradigms and Perspectives (I) Yahoo! Bangalore, India

April 29, 2008 Machine Learning: New Paradigms and Perspectives (I) Infosys Bangalore, India

April 28, 2008 Machine Learning: New Paradigms and Perspectives (I)

International School of Information Management Mysore, India

April 21-25, 2008

Machine Learning Workshop (Five day solo workshop with 35 participants) (I)

International School of Information Management Bangalore, India

April 12, 2008 CEDAR-FOX System (One-day workshop with 30 participants) (I)

Southwest Association of Forensic Document Examiners San Diego, CA

February 18, 2008

Computational Methods for Handwritten Questioned Document Examination (I)

American Academy of Forensic Sciences Washington DC

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January 31, 2008

1. Writer Adaptation in Handwritten Arabic Recognition 2. Robust segmentation of handwritten lines 3. Handwritten word segmentation using local and global features

Document Recognition and Retrieval XV San Jose, CA

Nov 12, 2007 Segmentation of Overlapping Handwritten Lines

International Graphonomics Society

Melbourne, Australia

Sep 25, 2007 Computing Strength of Evidence in Writer Verification

International Conference on Document Analysis and Recog Curitiba, Brazil

Aug 30, 2007 Computational Forensics: Towards Hybrid Intelligent Crime Solving

Int Workshop on Computational Forensics Manchester, UK

July 25, 2007 Individuality of Fingerprints: Generative Models and Twins Studies

International Association for Identification

San Diego, CA

May 1, 2007 Computational Approaches to Scoring Handwritten Responses in Reading Comprehension Tests

Pearson Knowledge Technologies

Boulder, CO

May 1, 2007 Computer Processing of Handwriting in Documents (I)

University of Colorado Institute for Cognitive Sciences

Boulder, CO

April 9, 2007 Use of Ridge Points in Partial Fingerprint Matching

Biometric Technology for Human Identification IV

Orlando, FL

April 4, 2007 Computational; Methods for the Comparison of Extended Handwriting and Signatures

National Institute of Justice Applied Technology Conference

Garden Grove, CA

March 16, 2007

Language Models for Text Recognition (I) University of Mysore, International School of Information Management

Mysore, India

February 26, 2007

Pattern Recognition and Machine Learning Pitney Bowes Research Middlebury, CT

February 1, 2007

1. A Statistical Method of Line Segmentation 2. Segmentation of Documents using Conditional Random Fields

Document Recognition and Retrieval XVI

San Jose, CA

January 31, 2007

Machine Learning in Language Related Technologies (I)

Google Mountain View, CA

January 10, 2007

On the Automatic Scoring of Handwritten Essays

International Joint Conference on Artificial Intelligence

Hyderabad, India

January 4, 2007

Meeting of the Minds: Machine Learning in Language-related Technologies (I)

Hewlett Packard Research Laboratory

Bangalore, India

December 29, 2006

Meeting of the Minds: Machine Learning in Language-related Technologies (I)

International Symposium on Cognition and Recognition

Bangalore, India

December 22, 2006

Meeting of the Minds: Machine Learning in Language-related Technologies (I)

Indian Institute of Technology Mumbai, India

December 16, 2006

Machine Learning for Signature Verification International Conference on Graphics, Vision and Image Processing

Madurai, India

December 8, 2006

New Paradigms in Pattern Recognition (I) International Conference on Signal and Image Processing

Hubli, India

November 4, 2006

Panel on Legal Issues in Fingerprint Identification (I)

National Conference on Science, Technology and Law

St Petersburg, FL

October 24, 2006

Mapping Transcripts to Handwritten Text International Workshop on Frontiers in Handwriting Recognition

La Baule, France

September 29, 2006

Conditional Random Fields in Document Retrieval (I)

Descartes Conference on Mathematical Models in Counter-terrorism

Washington, DC

September 28, 2006

Versatile Retrieval of Arabic Documents Symposium on Arabic and Chinese Handwriting

College Park, MD

August 9, 2006

Automatic Interpretation and Assessment of Handwritten Answer Documents

Educational Testing Service Princeton, NJ

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July 4, 2006 Quality of Minutiae and Verification Accuracy

International Association for Identification

Boston, MA

April 27, 2006 Document Image Retrieval using Signatures as Queries

Document Image Analysis for Libraries

Lyons, France

April 21, 2006 Computer Processing of Handwriting in Documents

Michigan State University Computer Science Department Distinguished Lecture Series

East Lansing, MI

April 17, 2006 ROC and Likelihood Methods in Fingerprint Identification

Biometric Technology for Human Identification III (SPIE)

Orlando, FL

February 14, 2006

Scoring Handwritten School Essays using LSA

Document Analysis Systems VII Workshop

Nelson, New Zealand

January 31, 2006

Writer Verification and Identification NIJ Technology Partnership Workshop

Hilton Head, SC

January 18, 2006

Spotting Words in Handwritten Arabic Documents

Document Recognition and Retrieval XIII

San Jose, CA

December 29, 2005

Computer Processing of Handwriting in Documents

International Institute of Information Technology

Hyderabad, India

December 27, 2005

Malnad Engineering College Hassan, India

December 22, 2005

International Conference on Cognition and Recognition

Mysore, India

November 11, 2005

European Federation of Handwriting Examiners

Budapest, Hungary

November 3, 2005

Symposium Document Image Understanding Technology

College Park, MD

September 1, 2005

Int Conference on Document Analysis and Recognition

Seoul, Korea

August 13, 2005

American Society of Questioned Document Examiners

Montreal, Canada

June 27-28, 2005

International Graphonomics Society Conference

Salerno, Italy

June 23, 2005 UB Summer Lecture Series Buffalo, NY June 13, 2005 Florida Department of Education Tallahassee, FL April 7, 2005 MITRE Workshop on Optical

Handwriting Recognition McLean, VA

March 29, 2005

Complex Document Image Processing Workshop

Chicago, IL

March 30, 2005

SPIE Conference on Homeland Security

Orlando, Florida

Mar 10, 2005 Indian Institute of Science Bangalore, India March 8, 2005 International Workshop on

Document Analysis Calcutta, India

February 21, 2005

American Academy of Forensic Sciences

New Orleans, LA

January 19, 2005

Society of Photo-Instrumentn Engineers-DRR 13

San Jose, CA

December 2004

Conference on Lateral Computing

Bangalore, India

December 2004

Int. Conf. Knowledge Based Computer Systems

Hyderabad, India

November 2004

International Workshop Frontiers in Handwriting Recog

Tokyo, Japan

September 2004

Int Workshop on Document Analysis Systems

Florence, Italy

September 2004

Joint meeting of MAFS, MAAFS, CAFS, SAFS

Orlando, FL

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August 2004 International Conference on Pattern Recognition

Cambridge, England

June 22, 2004 Biometric Technologies-2004 Calgary, Canada June 14, 2004 Institute for Defense Analysis Alexandria, VA Mar 12, 2004 University of Maryland College Park, MD February 17, 2004

American Academy of Forensic Sciences

Dallas, TX

January 2004 Document Image Analysis for Libraries

Palo, Alto, CA

January 21, 2004

Tenth Int. Conf. on Doc. Recognition Retrieval (SPIE)

Santa Clara, CA

Dec 11, 2003 Indian Statistical Institute Calcutta, India November 3, 2003

International Graphonomics Society

Scottsdale, AZ

September 25, 2003

European Association of Forensic Sciences

Istanbul, Turkey

August 24, 2003

American Society of Questioned Document Examiners

Baltimore, MD

August 5, 2003

International Conference on Doc.Analysis and Recog.

Edinburgh, Scotland

May 7, 2003 National Security Agency Columbia, MD May 6, 2003 FBI Academy Quantico, VA April 11, 2003 Symposium on Document Image

Understanding Greenbelt, MD

February 2003 American Academy of Forensic Sciences

Chiacago, IL

October 2002 Indian Institute of Science Bangalore, India April 27, 2002 Southwest Association of

Forensic Document Examiners San Diego, CA

February 2002 American Academy of Forensic Sciences

Atlanta, GA

January 21-22, 2002

Ninth Int. Conf. on Doc. Recognition Retrieval (SPIE)

San Jose, CA

November 9, 2001

Canadian Forensic Sciences Conference

Toronto, Canada

November 2001

US Postal Inspection Service Washington, DC

October 2001 Indian Institute of Science Bangalore, India September 10-13, 2001

Sixth Int. Conf. on Doc. Analysis and Recognition

Seattle, WA

July 27, 2001 US Secret Service Washington, DC July 20, 2001 US Postal Inspection Service Washington, DC April 24, 2001 Symp. Document Image

Understanding Technology Annapolis, MD

February 21, 2001

American Academy of Forensic Sciences

Seattle, WA

April 14, 2000 University of Southwestern Louisiana

Baton Rouge, LA

March 16-19, 2000

Int. Conf. in honor of Prof. C. R. Rao

San Antonio, TX

February 20, 2000

Annual National Institute of Justice Grantees Meeting

Reno, NV

December 23, 1999

Indian Statistical Institute Calcutta, India

November 1999

University of Rochester Computer Science Colloquium

Rochester, NY

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September 20-22, 1999

Fifth Int Conference Document Anal and Recognition

Bangalore, India

August 15-16, 1999

Purdue University Advances Image Proc Understanding

W. Lafayette, IN

January 5-7, 1999

Second International Conference on Multimodal Interface

Hong Kong

August 16-20, 1998

International Conference on Pattern Recognition

Brisbane, Australia

Oct 15, 1997 SUNY at Buffalo Buffalo, NY August 18-20, 1997

Fourth Int. Conf. Document Analysis and Recognition

Ulm, Germany

August 25-29, 1997

Thirteenth Int. Conference of Pattern Recognition

Vienna, Austria

August 1997 United States Postal Service Buffalo, NY June 1997 Epcot Center Orlando, FL April 30, 1997 Symposium Document Image

Understanding Technology Annapolis, MD

April 23-25, 1997

Int. Conf. Computer Systems for Industrial Applications

Hsinchu, Taiwan

March 3-4, 1997

United States Postal Service Rochester, NY

February 10-12, 1997

Int Conf Computational Intelligence Multimedia Appls.

Gold Coast, Australia

Nov 20, 1996 University of Mysore Mysore, India Oct16-29, 1996

University of Bari Bari, Italy

September 2-5, 1996

Fifth Int Conf. Frontiers in Handwriting Recognition

Colchester, England

October 15, 1995

Third Int. Conf. Document Analysis and Recognition

Montreal, Canada

February 28, 1995

Concordia University, CS Department

Montreal, Canada

February 9, 1995

Information Sciences Institute, USC

Los Angeles, CA.

Feb 8, 1995 SPIE Conference San Jose, CA December 8, 1994

International Workshop Handwriting Recognition

Tapei, Taiwan

Dec 5, 1994 Yonsei University Seoul, S. Korea October 10, 1994

Document Analysis Systems Conference

Kaiserslautn, Germany

Oct 5, 1994 Tata Consultancy Services Bombay, India September 30, 1994

Indian Institute of Science Bangalore, India

June 20, 1994 Digital Libraries Conference College Station, TX May 19, 1994 Digital Libraries Conference Newark, NJ February 10, 1994

SPIE Conference San Jose, CA

October 22, 1993

Int. Conf. on Document Analysis and Recognition

Tsukuba , Japan

August 18, 1993

National Library of Medicine Bethesda, MD

May 14, 1993 SUNY at Stony Brook Stony Brook, NY April 25, 1993 Document Anal and Information

Retrieval Symposium Las Vegas, NV

April 1, 1993 Princeton University Princeton, NJ Jan 4, 1993 Indian Institute of Science Bangalore, India

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July 9, 1992 DARPA Workshop on Man-Machine Communications

Endicott, MA

May 12, 1992 University of North Carolina - IBM Symposium

Charlotte, NC

May 6, 1992 DARPA Workshop on Document Understanding

Palo Alto, CA

Jan 28, 1992 Ricoh Corporation Kawasaki, Japan January 26, 1992

Institute for Posts and Telecommunications Policy

Tokyo, Japan

October 1, 1991

First Int. Conf. Document Analysis and Recognition

St. Malo, France

December 18, 1990

Knowledge Based Computer Systems IV

Pune, India

November 6, 1990

USPS Advanced Technology Conference

Washington, DC

October 30, 1990

Electronic Imaging East Boston, MA

May 16, 1990 Vision Interface Halifax, Canada April 2, 1990 Int. Workshop on Frontiers of

Handwriting Recognition Montreal, Canada

December 11, 1989

Int. Conference on Knowledge Based Computer Systems

Bombay, India

October 18, 1989

Association Intelligent System Technologies

Syracuse, NY

September 25, 1989

Science Research Automation Council

Leningrad, USSR

September 8, 1989

COST-13 Summer School on From Pixels to Features

Bonas, France

August 15, 1989

Northeast Artificial Intelligence Consortium Conference

Blue Mtn. Lake, NY

June 12, 1989 Image Understanding Machine Vision (OSA Meeting)

Cape Cod, MA

June 5, 1989 IEEE-CS Computer Vision Pattern Recognition Conf.

San Diego, CA

Jan 19, 1989 MITRE Corporation McLean, VA November 30, 1988

South East Asia Regional Computer Confederation Conf.

New Delhi, India

Oct 24, 1988 AT&T Bell Laboratories Murray Hill, NJ September 6, 1988

CAS Int. Seminar on Artificial Intelligence

Dubrovnik, Yugoslav.

August 24, 1988

COST-13 Workshop on From Pixels to Predicates

Bonas, France

May 30, 1988 Eighth International Workshop on Expert Systems

Avignon, France

January 8, 1988

Indo-US Workshop on Systems and Signal Processing

Bangalore, India

January 4, 1988

Image Processing & AI Seminar - Indotronix Corp.

Hyderabad, India

December 29, 1987

Tata Research Design and Development Center

Pune, India

October 28, 1987

Int. Workshop on Expert Systems & Pattern Recognition

Novosibirsk, USSR

August 25, 1987

International Joint Conference on Artificial Intelligence

Milan, Italy

May 21, 1987 Society of Photographic Scientists and Engineers

Rochester, NY

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May 11, 1987 Seventh International Workshop on Expert Systems

Avignon, France

April 9, 1987 USPS Advanced Technology Advisory Board

Washington, DC

January 6, 1987

Institute of Electronics and Telecom. Engineers

Bangalore, India

January 6, 1987

Indian Institute of Science, ECE Department

Bangalore, India

December 30, 1986

Indian Institute of Technology, Department of CS

Madras, India

December 20, 1986

Conf. Knowledge Represent. and Inference in Sanskrit

Bangalore, India

November 20, 1986

ACM-IEEE Chapter Rochester, NY

November 5, 1986

Fall Joint Computer Conference Dallas, Texas

October 28, 1986

Eighth International Conference on Pattern Recognition

Paris, France

October 22, 1986

USPS Advanced Technology Conference

Washington, DC

October 15, 1986

SUNY Biophysics Department Buffalo, NY

Sepember 20, 1986

Northeast Artificial Intelligence Consortium Conference

Buffalo, NY

July 10, 1986 Northeast Artificial Intelligence Consortium Conference

Rochester, NY

April 29, 1986 AEG-Telefunken Ulm, W. Germany April 28, 1986 Sixth International Workshop on

Expert Systems Avignon, France

April 19, 1986 AI Applications to Engineering Southampton, UK Mar 20, 1986 SUNY College at Brockport Brockport, NY December 10, 1985

Second Artificial Intelligence Applications Conference

Miami Beach, FL

November 4, 1985

University of Rochester, Dept. of Computer Science

Rochester, NY

October 23, 1985

Expert Systems in Government Symposium

McLean, VA

September 27, 1985

Xerox Webster Res. Center, Cognitive System Group

Webster, NY

September 11, 1985

Calspan - UB series (ECE Department)

Amherst, NY

Aug 20, 1985 Rome Air Development Center Rome, NY July 17, 1985 Northeast Artificial Intelligence

Consortium Conference Minnowbrook, NY

June 28, 1985 Arthur D. Little, Inc. Washington, DC June 28, 1985 USPS Technology Resource

Department Washington, DC

May 13, 1985 Fifth International Workshop on Expert Systems

Avignon, France

April 16, 1985 National Computer Graphics Association Conference

Dallas, TX

February 25, 1985

Goal-Directed Computer Vision Workshop

Orlando, FL

February 19, 1985

USPS Advanced Technology Conference

Washington, DC

December 18, 1984

Indian Institute of Science, School of Automation

Bangalore, India

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December 17, 1984

Electronics Radar Development Establishment (LRDE)

Bangalore, India

December 10, 1984

International Conference Computers, Systems

Bangalore, India

August 1, 1984

Seventh International Conference on Pattern Recognition

Montreal, Canada

July 20, 1984 Xerox Webster Research Center, Imaging Systems Lab

Rochester, NY

June 4, 1984 AI: Relevance to Indian Industry :TRDDC Wkshp

Pune, India

May 28, 1984 University of Maryland, Computer Vision Laboratory

College Park, MD

April 1, 1984 University of Michigan, Department of EE and CS

Ann Arbor, MI

July 21, 1983 Multiresolution Image Processing & Analysis Workshop

Leesburg, VA

April 10, 1983 Honeywell Users Group Buffalo, NY January 12, 1983

Indian Institute of Technology, Department of CS

Madras, India

January 5, 1983

Indian Institute of Science, School of Automation

Bangalore, India

December 22, 1982

Tata Institute of Fundamental Research

Bombay, India

October10, 1982

International Conference on Cybernetics and Society

Seattle, WA

August 20, 1982

AAAI-82 National Conference on Artificial Intelligence

Pittsburgh, PA

June 21, 1982 ACM Conference on Office Information Systems

Philadelphia, PA

June 16, 1982 IEEE-CS Conference Pattern Recognition & Image Processing

Las Vegas, NV

June 8, 1982 AFIPS National Computer Conference

Houston, TX

August 3, 1981

IEEE-CS Conf. Pattern Recognition & Image Processing

Dallas, TX

June 10, 1981 Canadian Man-Computer Communications Society Conference

Waterloo, Ontario

December 1, 1980

Fifth International Conference on Pattern Recognition

Miami Beach, FL

October 8, 1980

International Conf. Cybernetics and Society (IEEE-SMC)

Cambridge, MA

October 10, 1979

International Conference Cybernetics and Society (IEEE-SMC)

Denver, CO

August 7, 1979 IEEE-CS Conf. Pattern Recognition & Image Processing Chicago, IL

August 22, 1978 Fourth International Cybernetics and Systems Congress Amsterdam, Netherlands

July 20, 1978 Indian Institute of Science, School of Automation Bangalore, India June 1, 1978 IEEE-CS Conf.Pattern Recognition & Image Processing Chicago, IL March 5, 1978 Michigan State University, Department of CS East Lansing, MI January 20, 1978 ACM Computer Science Conference Detroit, MI October 7, 1977 IEEE International Symposium on Information Theory Ithaca, NY February 2, 1975 ACM Computer Science Conference Washington, DC

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