Curriculum Vitae of Yi Ma

Mail Address: No. 5 Danling Street, Room T2-13255Haidian District, Beijing, P.R. China 100080

Telephone: +86 10-5917-5126; Fax: +86 10-8286-8527Email Address: mayi@microsoft.com or yima@illinois.edu

1 EDUCATION

• Ph.D. in Electrical Engineering and Computer Sciences, University of California at Berkeley, 2000.

• Master of Arts in Mathematics, University of California at Berkeley, 2000.

• Master of Science in Electrical Engineering and Computer Sciences, University of California at Berkeley,1997.

• Bachelor Degree in Automatic Control and a supplementary degree in Applied Mathematics, TsinghuaUniversity, Beijing, China, 1995.

2 PROFESSIONAL APPOINTMENTS

• Principal Researcher and group manager of the Visual Computing Group, Microsoft Research Asia, Beijing,China, since July 2011.

• Guest Professor of the University of Science and Technology in China (USTC), since 2011.

• Senior Researcher and group manager of the Visual Computing Group, Microsoft Research Asia, Beijing,China, January 2009 – July 2011.

• Adjunct Professor of the he Electrical & Computer Engineering Department, University of Illinois atUrbana-Champaign, since January 2012.

• Associate Professor (with tenure) of the Electrical & Computer Engineering Department, University ofIllinois at Urbana-Champaign, since August 2006 – December 2011.

• Affiliate Associate Professor of the Computer Science Department, University of Illinois at Urbana-Champaign, since August 2009.

• Senior Researcher and Research Manager of the Visual Computing Group, Microsoft Research Asia,Beijing, China, since January 2009.

• Research Associate Professor of the Coordinated Science Laboratory, and of the Beckman Institute,University of Illinois at Urbana-Champaign, since August 2006.

• Visiting Professor at Department of Electrical Engineering and Computer Sciences, University of Californiaat Berkeley, Spring 2007.

• Visiting Senior Researcher of the Director at Microsoft Research Asia, Beijing, China, Summer and Fall2006.

• Assistant Professor (tenure track) of the Electrical & Computer Engineering Department, University ofIllinois at Urbana-Champaign, August 2000 – August 2006.

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3 HONORS AND AWARDS

• Gold Star Award, Microsoft Corporate, 2011.

• Sang Uk Lee Best Student Paper Award at Asian Conference on Computer Vision, Xi’an, China,September 2009.

• Senior Member of IEEE, since 2006.

• Incomplete List of Teachers Ranked as Excellent (voted by the students), University of Illinois atUrbana-Champaign, Spring 2001, Fall 2002, and Spring 2006.

• Young Investigator Award (two recipients nation-wide in the division of Mathematical, Computer andInformation Sciences), Office of Naval Research, 2005.

• Longuet-Higgins Best Paper Award (honorable mention) of the European Conference on ComputerVision (one prize winner and one honorable mention out of over 700 papers submitted), 2004.

• Young Faculty CAREER Award, National Science Foundation, 2003.

• David Marr Best Paper Award of the International Conference on Computer Vision (one of two prizewinners out of over 600 papers submitted), 1999.

• Regents Fellowship, University of California at Berkeley, 1995–1996.

• Excellent Student Scholarship – First Prize, Tsinghua University, P. R. China, 1994.

• Champion of the First Mathematical and Computer Modeling Contest, Tsinghua University, P. R. China,1994.

4 KEYNOTES AND DISTINGUISHED LECTURES

• Plenary Talk at Internationl Conference on Pattern Recognitin (ICPR), Japan, November 2012.

• Plenary Talk at International Conference on Distributed Smart Camera, October 2012.

• Keynote Speech at International Conference on Biometrics (BTAS) , Washington DC, September 2012.

• Keynote Speech at Digital Image Computing: Techniques and Applications, Queensland, Australia, De-cember 2011.

• Keynote Speech at the 3rd International Conference on Awareness Science and Technology, Dalian, China,September 2011.

• Plenary Talk at Signal Processing with Adaptive Sparse Structured Representations (SPARS), Edinburg,June 27-30, 2011.

• Distinguished Lecture at Technion Computer Engineering Inauguration Conference, Israel, June 1-6, 2011.

• Keynote Speech at AAAI Symposium on Manifold Learning and its Applications, Arlington, VA. Nov. 11,2010.

• Plenary Speaker at Visual Communications and Image Processing (VCIP), Huangshan, China, July 2010.

• Keynote Speaker at ACCV workshop on Community Based 3D Content and its Applications in MobileInternet Environment, September 24, 2009.

• Plenary Speaker at the 22th IPPR Conference on Computer Vision, Graphics, and Image Processing,Taiwan, August 2009.

• Keynote Speaker at International Workshop on Local and Non-Local Approximation (LNLA) in ImageProcessing, Helsinki, August 2009.

• Plenary Speaker at Picture Coding Symposium (PCS), Chicago, May 2009.

• Fessenden Lecture at ECE Department, the University of Pittsburgh, February 2007.

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5 PUBLICATIONS

• Books Authored:

1. Generalized Principal Component Analysis: Modeling & Segmentation of Multivariate Mixed Data, ReneVidal, Yi Ma, and Shankar Sastry, Springer, expected 2013.

2. An Invitation to 3-D Vision: From Images to Geometric Models, Yi Ma, Stefano Soatto, Jana Kosecka,and Shankar Sastry, Springer Series on Interdisciplinary Applied Mathematics (IAM #26), 526 pages/170illustrations, Springer, New York, November 2003.

• Book Edited:

1. Dynamical Vision, edited by Rene Vidal, Anders Heyden, and Yi Ma, Lecture Notes in Computer Science(LNCS #4358), 329 pages, Springer, 2007.

• Journal Special Issue Edited:

1. Special issue on Real-World Face Recognition, editied with Hua Gang et. al., IEEE Transactions onPattern Analysis and Machine Intelligence, to appear in 2011.

2. Special issue on Dimensionality Reduction via Subspace and Manifold Learning, edited by Yi Ma, ParthaNiyogi, Guillermo Sapiro, and Rene Vidal, IEEE Signal Processing Magazine, March 2011.

3. Special issue on Applications of Sparse Representation and Compressive Sensing, edited by RichardBaraniuk, Emmanuel Candes, Michael Elad, and Yi Ma, Proceedings of IEEE, June 2010.

• Refereed Journal Papers:

1. “Robust Recovery of Subspace Structures by Low-Rank Representation,” Guangcan Liu, Zhouchen Lin,Shuicheng Yan, Ju Sun, Yong Yu, and Yi Ma, accepted by the IEEE Transactions on Pattern Analysisand Machine Intelligence, 2012.

2. “TILT: Transform-Invariant Low-rank Textures,” Zhengdong Zhang, Arvind Ganesh, Xiao Liang, and YiMa, accepted by International Journal of Computer Vision (IJCV), 2012. (Conference version publishedin ACCV 2010.)

3. “RASL: Robust Alignment by Sparse and Low-rank Decomposition for Linearly Correlated Images,”Yigang Peng, Arvind Ganesh, John Wright, Wenli Xu, and Yi Ma, accepted by IEEE Transactionson Pattern Analysis and Machine Intelligence (PAMI), 2012. (Conference version published in CVPR2010.)

4. “Towards a Practical Face Recognition System: Robust Alignment and Illumination by Sparse Repre-sentation,” Andrew Wagner, John Wright, Arvind Ganesh, Zihan Zhou, Hossein Mobahi, and Yi Ma,Volume 34, Issue 2, page 372-386, IEEE Transactions on Pattern Analysis and Machine Intelligence(PAMI), February 2012. (Conference version published in CVPR 2009.)

5. “Segmentation of Natural Images by Texture and Boundary Compression,” Hossein Mobahi, ShankarRao, Allen Yang, Shankar Sastry, and Yi Ma, Volume 95, Number 1, page 86-98, International Journalof Computer Vision (IJCV), October 2011. (Conference version published in ACCV 2009.)

6. “Robust Principal Component Analysis?” Emmanuel Candes, Xiaodong Li, Yi Ma, and John Wright,vol. 58, issue 3, article 11, the Journal of the ACM, May 2011.

7. “Image Super-Resolution via Sparse Representation,” Jianchao Yang, John Wright, Thomas Huang, andYi Ma, IEEE Transactions on Image Processing, vol. 19, page 2861-2873, November 2010.

8. “Motion Segmentation in the Presence of Outlying, Incomplete, and Corrupted Trajectories,” ShankarRao, Roberto Tron, Rene Vidal, and Yi Ma, IEEE Transactions on Pattern Analysis and MachineIntelligence, vol. 32, no. 10, October 2010.

9. “Dense Error Correction via `1 Minimization,” John Wright and Yi Ma, IEEE Transactions on Infor-mation Theory, vol. 56, no. 7, July 2010.

10. “Sparse Representation for Computer Vision and Pattern Recognition,” John Wright, Yi Ma, GuillermoSapiro, Shuicheng Yan, and Thomas Huang, the Proceedings of IEEE, vol. 98, issue 6, June 2010.

11. “On the Role of Sparse and Redundant Representations in Image Processing,” Michael Elad, MarioFigueiredo, and Yi Ma, the Proceedings of IEEE, vol. 98, issue 6, June 2010.

12. “Robust Algebraic Segmentation of Mixed Rigid-Body and Planar Motions,” Shankar Rao, Allen Yang,Shankar Sastry, and Yi Ma, International Journal of Computer Vision, vol. 88, page 425-446, January2010.

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13. “Classification via Minimum Incremental Coding Length (MICL),” John Wright, Yi Ma, Yangyu Tao,Zhouchen Lin, and Heung-Yeung Shum, SIAM Journal on Imaging Science, vol. 2, issue 2, page 367-395,April 2009.

14. “Robust Face Recognition via Sparse Representation,” John Wright, Allen Yang, Arvind Ganesh,Shankar Sastry, and Yi Ma, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI),vol. 31, no. 2, February 2009.

15. “Estimation of Subspace Arrangements with Applications in Modeling and Segmenting Mixed Data,”Yi Ma, Allen Yang, Harm Derksen, and Robert Fossum, SIAM Review, vol. 50, no. 3, August 2008.

16. “Unsupervised Segmentation of Natural Images via Lossy Data Compression,” Allen Yang, John Wright,Yi Ma, and Shankar Sastry, Computer Vision and Image Understanding (CVIU), vol. 110, no. 2, May2008.

17. “Segmentation of Multivariate Mixed Data via Lossy Data Coding and Compression,” Yi Ma, HarmDerksen, Wei Hong, and John Wright, IEEE Transactions on Pattern Analysis and Machine Intelligence,vol. 29, no. 9, pages 1546-1562, September 2007.

18. “Multi-Scale Hybrid Linear Models for Lossy Image Representation,” Wei Hong, John Wright, Yi Ma,and Kun Huang, IEEE Transactions on Image Processing, vol. 15, no. 12, pages 3655-3671, December2006.

19. “A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation and Estimation,” Yi Ma and ReneVidal, Journal Mathematical Imaging and Vision, vol. 25, pages 403-421, November 2006.

20. “Two-View Multibody Structure from Motion,” Rene Vidal, Yi Ma, Stefano Soatto, and Shankar Sastry,International Journal of Computer Vision, special issue on Dynamical Vision, vol. 68, no. 1, pages 7-25,June 2006.

21. “Generalized Principal Component Analysis (GPCA),” Rene Vidal, Yi Ma, and Shankar Sastry, IEEETransactions on Pattern Analysis and Machine Intelligence, vol. 27, no. 12, pages 1945-1959, December2005.

22. “Symmetry-Based 3-D Reconstruction from Perspective Images,” Allen Yang, Kun Huang, Shankar Rao,and Yi Ma, Computer Vision and Image Understanding, vol.99, issue 2, pages 210-240, August 2005.

23. “Symmetry Based Photo Editing,” Kun Huang, Wei Hong, and Yi Ma, the special issue on imageunderstanding for digital photos of Pattern Recognition, vol. 38, no. 6, pages 825-834, 2005.

24. “A Survey of Geometric Vision,” Kun Huang and Yi Ma, book chapter of Robotics and AutomationHandbook, edited by Thomas Kurfess, chapter 22, pages 1-25, CRC press, 2005.

25. “On Symmetry and Multiple View Geometry: Structure, Pose and Calibration from a Single Image,”Wei Hong, Yang Yang, and Yi Ma, International Journal of Computer Vision, vol. 60, no. 3, pages241-265, December, 2004.

26. “Rank Conditions on the Multiple View Matrix,” Yi Ma, Kun Huang, Rene Vidal, Jana Kosecka, andShankar S. Sastry, International Journal of Computer Vision, vol. 59, no. 2, pages 115-137, September2004.

27. “A Differential Geometric Approach to Multiple View Geometry in Spaces of Constant Curvature,” YiMa, International Journal of Computer Vision, vol. 58, no. 1, pages 37-53, 2004.

28. “Optimization Criteria and Geometric Algorithms for Motion and Structure Estimation,” Yi Ma, JanaKosecka, and Shankar S. Sastry, International Journal of Computer Vision vol. 44, no. 3, pages 219-249,2001.

29. “Optimal Motion from Multiple Views by Normalized Epipolar Constraints,” Yi Ma, Rene Vidal, ShawnHsu, and Shankar S. Sastry, Communications in Information and Systems, vol. 1, no. 1, pages 51-73,2001.

30. “Euclidean Reconstruction and Reprojection up to Subgroups,” Yi Ma, Stefano Soatto, Jana Kosecka,and Shankar Sastry, in Proceedings of the 7th IEEE International Conference on Computer Vision(ICCV), Corfu, Greece, September 1999, vol. 2, page 773-780, also in the International Journal ofComputer Vision special issue of the David Marr Best Paper Prize papers, vol. 38, no. 3, pages 217-227,2000.

31. “Linear Differential Algorithm for Motion Recovery: A Geometric Approach,” Yi Ma, Jana Kosecka,and Shankar Sastry, the International Journal of Computer Vision (IJCV), vol. 36, no. 1, pages 71-89,2000.

32. “Landing an Unmanned Aerial Vehicle: Vision Based Motion Estimation and Nonlinear Control,” OmidShakernia, Yi Ma, John Koo, and Shankar Sastry, the Asian Journal of Control, vol. 1, no. 3, pages128-45, 1999.

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33. “Vision Guided Navigation for a Nonholonomic Mobile Robot,” Yi Ma, Jana Kosecka, and ShankarSastry, the IEEE Transactions on Robotics and Automation, vol. 15, no. 3, pages 521-36, 1999.

• Conference Papers:

1. “Compressive Principal Component Pursuit,” John Wright, Arvind Ganesh, Kerui Min, and Yi Ma ,arXiv:1202.4596 In Proceedings of International Symposium on Information Theory, July 2012.

2. “Principal Component Pursuit with Reduced Linear Measurements,” Arvind Ganesh, Kerui Min, JohnWright, and Yi Ma, arXiv:1202.6445 In Proceedings of International Symposium on Information Theory,July 2012.

3. “Non-Negative Low Rank and Sparse Graph for Semi-Supervised Learning,” Liansheng Zhuang, HaoyuanGao, Zhouchen Lin, Yi Ma, and Nenghai Yu. In Proceedings of IEEE Conference on Computer Visionand Pattern Recognition (CVPR), June 2012.

4. “Detecting Texts of Arbitrary Orientations in Natural Images,” Cong Yao, Zhuowen Tu, and Yi Ma. InProceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2012.

5. “Seeing through the Blur,” Hossein Mobahi, Lawrence Zitnick, and Yi Ma. In Proceedings of IEEEConference on Computer Vision and Pattern Recognition (CVPR), June 2012.

6. “Robust Plane-Based Structure From Motion,” Zihan Zhou, Hailin Jin, and Yi Ma. In Proceedings ofIEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2012.

7. “Holistic Reconstruction of Urban Structures from Low-rank Textures,” Hossein Mobahi, Zihan Zhou,Allen Y. Yang, and Yi Ma. Workshop on 3D Reconstruction and Recognition, International Conferenceon Computer Vision (ICCV), October 2011.

8. “Unwrapping Low-rank Textures on Generalized Cylindrical Surfaces,” Zhengdong Zhang, Xiao Liang,and Yi Ma. In Proceedingsof International Conference on Computer Vision (ICCV), October 2011.

9. “Face Recovery in Conference Video Streaming using Robust Principal Component Analysis,” Wai-tianTan, Gene Cheung, and Yi Ma. In Proceedings of IEEE International Conference on Image Processing(ICIP), Finalist for the Best Paper Award (5 out of 2245 submissions), September 2011.

10. “Camera Calibration with Lens Distortion from Low-rank Textures,” Zhengdong Zhang, Yasuyuki Mat-sushita, and Yi Ma. in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition(CVPR), June 2011.

11. “TILT: Transform Invariant Low-rank Textures,” Zhengdong Zhang, Xiao Liang, Arvind Ganesh, andYi Ma. In Proceedings of Asian Conference on Computer Vision, November 2010.

12. “Robust Photometric Stereo via Low-Rank Matrix Completion and Recovery,” Lun Wu, Arvind Ganesh,Boxin Shi, Yasuyuki Matsushita, Yongtian Wang, and Yi Ma. In Proceedings of Asian Conference onComputer Vision, November 2010.

13. “Image Tag Refinement Towards Low-Rank Content-Tag Prior and Error Sparsity,” Guangyu Zhu,Shuicheng Yan, and Yi Ma, ACM Multimedia, 2010.

14. “Decomposing Background Topics from Keywords by Principal Component Pursuit,” Kerui Min, Zheng-dong Zhang, John Wright, and Yi Ma, ACM International Conference on Information and KnowledgeManagement, 2010.

15. “Towards a Robust Face Recognition System Using Compressive Sensing,” Allen Yang, Zihan Zhou, YiMa, and Shankar Sastry, invited paper to InterSpeech, 2010.

16. “Fast L1-Minimization Algorithms and an Application in Robust Face Recognition: A Review,” AllenYang, Shankar Sastry, Arvind Ganesh, and Yi Ma, International Conference on Image Processing, 2010.

17. “Stable Principal Component Pursuit,” Zihan Zhou, Xiaodong Li John Wright, Emmanuel Candes, andYi Ma, International Symposium on Information Theory, June 2010.

18. “Dense Error Correction for Low-Rank Matrices via Principal Component Pursuit,” Arvind Ganesh,John Wright, Xiaodong Li, Emmanuel Candes, and Yi Ma, International Symposium on InformationTheory, June 2010.

19. “Compact Projection: Simple and Efficient Near Neighbor Search with Practical Memory Requirements,”Kerui Min, Linjun Yang, John Wright, Lei Wu, Xian-Sheng Hua, and Yi Ma, in Proceedings of IEEEConference on Computer Vision and Pattern Recognition (CVPR), June 2010.

20. “RASL: Robust Alignment by Sparse and Low-Rank Decomposition for Linearly Correlated Images,”Yigang Peng, Arvind Ganesh, John Wright, and Yi Ma, in Proceedings of IEEE Conference on ComputerVision and Pattern Recognition (CVPR), June 2010.

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21. “Fast Convex Optimization Algorithms for Exact Recovery of a Corrupted Low-Rank Matrix,” ArvindGanesh, Zhouchen Lin, John Wright, Leqin Wu, Minming Chen, and Yi Ma, International Workshop onComputational Advances in Multi-Sensor Adaptive Processing, December 2009.

22. “Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Matrices via ConvexOptimization,” John Wright, Arvind Ganesh, Shankar Rao, and Yi Ma, in Proceedings of the Conferenceon Neural Information Processing Systems (NIPS), December 2009.

23. “Face Recognition with Contiguous Occlusion using Markov Random Fields,” Zihan Zhou, AndrewWagner, Hossein Mobahi, John Wright, and Yi Ma, in Proceedings of the IEEE International Conferenceon Computer Vision (ICCV), 2009.

24. “Learning Topology of Curves with Applications to Clustering,” Hossein Mobahi, Shankar Rao, and YiMa, in Proceedings of AAAI Symposium on Manifold Learning, 2009.

25. “Natural Image Segmentation with Adaptive Texture and Boundary Encoding,” Shankar Rao, HosseinMobahi, Allen Yang, Shankar Sastry, and Yi Ma, the Best Student Paper Award (the Sang Uk LeeAward), in Proceedings of the Asian Conference on Computer Vision, September 2009.

26. “Data-Driven Image Completion by Image Patch Subspaces,” Hossein Mobahi, Shankar Rao, and YiMa, Picture Coding Symposium, 2009.

27. “Distributed Video Coding Using Compressive Sampling,” Josep Prades-Nebot, Yi Ma, Thomas Huang,Picture Coding Symposium, 2009.

28. “Towards a Practical Face Recognition System: Robust Registration and Illumination via Sparse Rep-resentation,” Andrew Wagner, John Wright, Arvind Ganesh, Zihan Zhou, and Yi Ma, in Proceedings ofIEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2009.

29. “Minimum Sum of Distances Estimator: Rubustness and Stability,” Yoav Sharon, John Wright, and YiMa, American Conference on Control, 2009.

30. “Separation of A Subspace-Sparse Signal: Algorithms and Conditions,” Arvind Ganesh, Zihan Zhou,and Yi Ma, in Proceedings of ICASSP 2009.

31. “Dense Error Correction via L1-Minimization,” John Wright and Yi Ma , in Proceedings of ICASSP2009.

32. “Nearest-Subspace Patch Matching for Face Recognition Under Varying Pose and Illumination,” ZihanZhou, Arvind Ganesh, John Wright, Shen-Fu Tsai, and Yi Ma , IEEE Conference on Face and GestureRecognition, 2008.

33. “Face Hallucination via Sparse Coding,” Jianchao Yang, Hao Tang, Yi Ma, and Thomas Huang, Inter-national Conference on Image Processing (ICIP), 2008.

34. “Motion Segmentation via Robust Subspace Separation in the Presence of Outlying, Incomplete, orCorrupted Trajectories,” Shankar Rao, Roberto Tron, Rene Vidal, and Yi Ma , IEEE Conference onComputer Vision and Pattern Recognition (CVPR), June 2008.

35. “Image Super-Resolution as Sparse Representation of Raw Image Patches,” Jianchao Yang, John Wright,Thomas Huang, and Yi Ma, IEEE Conference on Computer Vision and Pattern Recognition (CVPR),June 2008.

36. “Classification via Minimum Incremental Coding Length (MICL),” John Wright, Yangyu Tao, ZhouchenLin, Yi Ma, and Heung-Yeung Shum, Conference on Neural Information Processing Systems (NIPS),December 2007.

37. “Segmentation of Multivariate Mixed Data via Lossy Coding and Compression,” John Wright, WeiHong, Yi Ma, and Harm Derksen, SPIE conference on Visual Communications and Image Processing(VCIP), January 2007.

38. “The Algebra and Statistics of Generalized Principal Component Analysis,” Shankar Rao, Harm Derk-sen, Robert Fossum,Yi Ma, Andrew Wagner, and Allen Yang, SPIE conference on Visual Communica-tions and Image Processing (VCIP), January 2007.

39. “Robust Statistical Estimation and Segmentation of Multiple Subspaces,” Allen Yang, Shankar Rao,and Yi Ma, Workshop on 25 years of RANSAC, IEEE Conference on Computer Vision and PatternRecognition, New York, June 2006.

40. “Homographies and Matching of Ellipses with Applications to Forensic Bloodspatter Reconstruction,”John Wright, Andrew Wagner, Shankar Rao, and Yi Ma, IEEE Conference on Computer Vision andPattern Recognition, New York, June 2006.

41. “Database-Guided Simultaneous Multi-Slice 3-D Segmentation for Volumetric Data,” Wei Hong, BogdanGeorgescu, Xiang Sean Zhou, Sriram Krishnan, Yi Ma, and Dorin Comaniciu, European Conference onComputer Vision (ECCV), Graz, Austria, May 2006.

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42. “A Multi-Scale Hybrid Linear Model for Lossy Image Representation,” Wei Hong, John Wright, and YiMa, in proceedings of the International Conference on Computer Vision (ICCV), 2005.

43. “Hilbert Functions and Applications to the Estimation of Subspace Arrangements,” Allen Yang, Yi Ma,and Robert Fossum, in proceedings of the International Conference on Computer Vision (ICCV), 2005.

44. “Segmentation of Hybrid Motions via Generalized Principal Surface Analysis,” Shankar Rao, AllenYang, Andrew Wagner, and Yi Ma, in proceedings of the International Conference on Computer Vision(ICCV), 2005.

45. “Segmentation of a Piece-Wise Planar Scene from Perspective Images,” Allen Yang, Shankar Rao, An-drew Wagner, and Yi Ma, in proceedings of the IEEE Conference on Computer Vision and PatternRecognition (CVPR), 2005.

46. “A Closed-Form Solution to the Identification of Hybrid ARX Models via the Identification of AlgebraicVarieties,” Rene Vidal and Yi Ma, in Proceedings of the workshop on Hybrid Systems: Control andComputation (HSCC), Switzerland, 2005.

47. “Identification of Hybrid Linear Time-Invariant Systems via Subspace Embedding and Segmentation,”Kun Huang, Andrew Wagner, and Yi Ma, in Proceedings of IEEE Conference on Decision and Control(CDC), Bahamas, 2004.

48. “Large Baseline Matching and Reconstruction from Symmetry Cells,” Kun Huang, Allen Yang Yang,Wei Hong, and Yi Ma, in Proceedings of the International Conference on Robotics and Automation(ICRA), New Orleans, 2004.

49. “Sparse Representations of Images by Hybrid Linear Models,” Kun Huang, Allen Yang and Yi Ma, inProceedings of the International Conference on Image Processing (ICIP), Singapore, 2004.

50. “Clustering Subspaces by Fitting, Differentiating and Dividing Polynomials,” Rene Vidal and Yi Ma, inProceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), WashingtonDC, 2004.

51. “Minimum Effective Dimension for Mixtures of Subspaces: A Robust GPCA Algorithm and its Appli-cations,” Kun Huang, Yi Ma, and Rene Vidal, in Proceedings of the IEEE Conference on ComputerVision and Pattern Recognition (CVPR), Washington DC, 2004.

52. “Reconstruction of 3-D Symmetric Curves from Perspective Images without Discrete Features,” WeiHong, Yi Ma, and Yizhou Yu, in Proceedings of the European Conference on Computer Vision (ECCV),Prague, 2004.

53. “A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation via Polynomial Fitting and Differ-entiating,” Rene Vidal and Yi Ma, Honorable Mention for the Longuet-Higgins Best Paper Award,in Proceedings of the European Conference on Computer Vision (ECCV), Prague, 2004.

54. “An Algebraic Geometric Approach to the Identification of a Class of Linear Hybrid Systems,” ReneVidal, Stefano Soatto, Yi Ma, and Shankar Sastry, Finalist for the Best Paper Award, in Proceedings ofIEEE Conference on Decision and Control (CDC), Hawaii, 2003.

55. “Structure and Pose from Single Images of Symmetric Objects with Applications to Robot Navigation,”Allen Yang Yang, Wei Hong, and Yi Ma, in Proceedings of the International Conference on Roboticsand Automation (ICRA), Taipei, Taiwan, 2003

56. “On Exploiting Occlusions in Multiple-View Geometry,” Paolo Favaro, Alessandro Duci, Yi Ma, andStefano Soatto, International Conference on Computer Vision (ICCV), October, 2003.

57. “Geometric Segmentation of Perspective Images Based on Symmetry Groups,” Yang Yang, ShankarRao, Wei Hong, and Yi Ma, International Conference on Computer Vision (ICCV), October, 2003.

58. “Generalized Principal Component Analysis (GPCA): An Analytic Solution to Segmentation of Mixturesof Subspaces,” Rene Vidal, Yi Ma, and Shankar Sastry, Finalist for the Best Paper Award, IEEEConference on Computer Vision and Pattern Recognition (CVPR), June, 2003.

59. “Introduction to Multiview Rank Conditions and their Applications: A Review,” Jana Kosecka and YiMa, invited paper, 2002 Tyrrhenian International Workshop on Digital Communications (IWDC 2002),Advanced Methods for Multimedia Signal Processing, Palazzo dei Congressi, Capri, Italy, September2002.

60. “Interpretation of Dynamic Scenes from the Multibody Fundamental Matrix,” Rene Vidal, StefanoSoatto, Yi Ma, and Shankar Sastry, in Proceedings of the Workshop on Vision and Modelling of DynamicScenes, the European Conference on Computer Vision (ECCV), Copenhagen, Denmark, May 2002.

61. “Classifications of Rank Conditions for Multiple View Geometry of Dynamical Scenes,” Yi Ma, KunHuang, and Yang Yang, in Proceedings of the Workshop on Vision and Modeling of Dynamic Scenes,the European Conference on Computer Vision (ECCV), Copenhagen, Denmark, May 2002.

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62. “Generalized Rank Conditions in Multiple View Geometry with Applications to Dynamical Scenes,”Kun Huang , Robert Fossum, and Yi Ma, in Proceedings of the European Conference on ComputerVision (ECCV), Copenhagen, Denmark, May 2002.

63. “Rank Deficiency Condition of the Multiple View Matrix for Mixed Point and Line Features,” Yi Ma,Jana Kosecka, and Kun Huang, oral presentation at the fifth Asian Conference on Computer Vision(ACCV), Melbourne, Australia, January 2002.

64. “Multiple View Motion Estimation and Control for Landing an Unmanned Aerial Vehicle,” Omid Shaker-nia, Courtney S. Sharp, Rene Vidal, David H. Shim, Yi Ma, and Shankar Sastry, International Conferenceon Robotics and Automation (ICRA) 2002.

65. “Recognition of Human Gait,” Alessandro Bissocco, Alessandro Chiuso, Yi Ma, and Stefano Soatto,IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Hawaii, December, 2001.

66. “Optimal Motion Estimation from Multiview Normalized Epipolar Constraint,” Rene Vidal, Yi Ma,Jana Kosecka, and Shankar Sastry, oral presentation at International Conference on Computer Vision(ICCV, 45 out of 596 paper submitted), Vancuver, Canada, July 2001.

67. “Kruppa Equation Revisited: its Degeneracy and Renormalization,” Yi Ma, Rene Vidal, Jana Kosecka,and Shankar Sastry, in Proceedings of the 6th European Conference on Computer Vision (ECCV), June2000.

68. “Optimization Criteria, Sensitivity and Robustness of Motion and Structure Estimation,” Yi Ma, JanaKosecka, and Shankar Sastry, in Proceedings of IEEE 7th International Conference on Computer Vision(ICCV) workshop on Vision Theory and Algorithms, Corfu, Greece, September 1999.

69. “Euclidean Reconstruction and Reprojection Up to Subgroups,” Yi Ma, Stefano Soatto, Jana Koseckaand Shankar Sastry, the David Marr Best Paper Award, in Proceedings of the 7th IEEE Interna-tional Conference on Computer Vision (ICCV), 1999.

70. “Vision Guided Landing of an Unmanned Aerial Vehicle,” Omid Shakernia, Yi Ma, John Koo, JoaoHespanha, and Shankar Sastry, in Proceedings of IEEE Conference on Decision & Control (CDC),Phoenix, Arizona, December 1999.

71. “A Lie Theoretic Approach to Structure and Motion in Computer Vision,” Yi Ma, Omid Shakernia, JanaKosecka, and Shankar Sastry, in Proceedings of the 14th World Congress of International Federation ofAutomatic Control (IFAC), Beijing, China, July 1999.

72. “Motion Recovery from Image Sequences: Discrete Viewpoint vs. Differential Viewpoint,” Yi Ma, JanaKosecka, and Shankar Sastry, in Proceedings of European Conference on Computer Vision (ECCV),Freiburg, Germany, June 1998, vol.2, page 337-53.

73. “Motion Estimation from Two Frames as Optimization on Stiefel Manifolds,” Yi Ma, Jana Kosecka, andShankar Sastry, in Proceedings of the 37th IEEE Conferences on Decision & Control (CDC), Tampa,Florida, December 1998.

74. “Free Flight in 2000: Games on Lie Groups,” Claire Tomlin, Yi Ma, and Shankar Sastry, in Proceedingsof the 37th IEEE Conferences on Decision & Control (CDC), Tampa, Florida, December 1998.

75. “Hierarchical Hybrid System Design on Berkeley Unmanned Autonomous Aerial Vehicle,” John Koo,David Shim, Omid Shakernia, Bruno Sinopoli, Yi Ma, Frank Hoffmann, and Shankar Sastry, Interna-tional Aerial Robotics Competition, Richland, Washington, August 1998.

76. “Optimal Motion From Image Sequences: A Riemannian Viewpoint,” Yi Ma, Jana Kosecka, and ShankarSastry, in Proceedings of Mathematical Theory of Networks and Systems (MTNS), Padova, Italy, July1998, page 1047-50.

77. “SmartATMS: A Simulator for Air Traffic Management Systems,” John Koo, Yi Ma, George Pappas,and Claire Tomlin, in Proceedings of Winter Simulation Conference (WSC), Atlanta, Georgia, December1997, page 1199-205.

78. “Vision Guided Navigation for a Nonholonomic Mobile Robot,” Yi Ma, Jana Kosecka, and ShankarSastry, in Proceedings of the 36th IEEE Conferences on Decision & Control (CDC), San Diego, California,December 1997, vol.3, page 3069-74.

• Patents:

1. Camera Calibration with Lens Distortion from Low-rank Textures, 2011.

2. Rectification of Chinese Characters as Transform Invariant Low-Rank Textures, 2011.

3. Transform Invariant Low-rank Textures, December 2010.

4. Recognition via High-Dimensional Data Classification, USPTO No. 61025039, January 31, 2008.

8

6 ACADEMIC ACTIVITIES AND SERVICES

• Invited Lectures:

1. “Transformed and Compressed Principal Component Pursuit,” invited talk at National University ofSingapore, April 5, 2012.

2. “Transformed and Compressed Principal Component Pursuit,” invited talk at Nanyang TechnologyUniversity, Singapore, April 2, 2012.

3. “Transformed and Compressed Principal Component Pursuit,” invited talk at Key Laboratory of Ma-chine Perception, Peking University, March 23, 2012.

4. “Transformed and Compressed Principal Component Pursuit,” invited talk at Statistics Department,Stanford, March 2, 2012.

5. “Transformed and Compressed Principal Component Pursuit,” invited talk at EECS Department, Berke-ley, March 1, 2012.

6. Invited talk at MSRA-NTT joint workshop on speech recognition, Beijing, January 19, 2012.

7. Invited talk at NIPS workshop on “Low-rank Methods for Large-scale Machine Learning,” Sierra Nevada,Spain, December 17, 2011.

8. “Sparse Representation and Low-rank Recovery for High Dimensional Data,” invited talk at Universityof Technology, Sydney, Australia, December 4, 2011.

9. Keynote speech at Digital Image Computing: Techniques and Applications, Queensland, Australia,December 6-8, 2011.

10. Keynote speech at the 3rd International Conference on Awareness Science and Technology, Dalian,China, September 2011.

11. Plenary talk at Signal Processing with Adaptive Sparse Structured Representations (SPARS), Edin-burgh, UK, June 2011.

12. Distinguished lecture at 1st Technion Computer Engineering Conference, Technion, Israel, June 2011.

13. Presentation at Craig Mundie’s Machine Learning Review, May 4, 2011.

14. “For Low-rank Structures in Images and Data,” invited talk at international workshop on InformationTheory and Applications, San Diego, February 9th, 2011.

15. “For Low-rank Structures in Images and Data,” computer vision seminar, UCLA, February 7, 2011.

16. “TILT and RASL: For Low-rank Structures in Images and Videos,” Seminar at Dalian Institute ofScience and Technology, January 7, 2011.

17. Keynote speech at AAAI Symposium on Manifold Learning and its Applications, Arlington, VA. Nov.11, 2010.

18. “For Low-rank Structures in Images and Data,” UIUC DSP Seminar, November 3, 2010.

19. “TILT and RASL: For Low-rank Structures in Images and Videos,” Seminar at National University ofSingapore, October 4, 2010.

20. “TILT and RASL: For Low-rank Structures in Images and Videos,” Seminar at Nanyang TechnologicalUniversity, September 30, 2010.

21. “Microsoft Research Asia Research Overview,” Summer school on Vision, Learning and Pattern Recog-nition (VLPR), Xi’an China, July 25, 2010.

22. “Robust Principal Component Analysis and its Applications,” Invited talk at Pao-Lu Hsu Conference,Xi’an, China, July 20, 2010.

23. “Robust Principal Component Analysis and its Applications,” Plenary talk at Visual Communicationsand Image Processing (VCIP), HuangShan, China, July 13, 2010.

24. “Robust Principal Component Analysis and its Applications,” NGA and DARPA Workshops in Wash-ington DC, June 22 and 23, 2010.

25. “Robust Principal Component Analysis and its Applications,” Invited talk at CAD&CG Lab, ZhejiangUniv., March 31st, 2010.

26. “Robust Principal Component Analysis and its Applications,” Andrew Yao’s Class, CS Department,Tsinghua University, March 26th, 2010.

27. “Robust Principal Component Analysis and its Applications,” UIUC DSP Seminar, March 10th, 2010.

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28. “Robust Principal Component Analysis and its Applications,” Microsoft Research Techfest Lecture,March 3rd, 2010.

29. “Robust Principal Component Analysis via Convex Optimization,” Invited talk at Singapore Manage-ment University, January 29, 2010.

30. “Confluence of Computer Vision and Sparse Representation,” Invited talk at Nanyang Technology Uni-versity, Singapore, January 28, 2010.

31. “Robust Principal Component Analysis via Convex Optimization,” Invited talk at Fusionopolis, Singa-pore, January 27, 2010.

32. “Confluence of Computer Vision and Sparse Representation,” Invited talk at National University ofSingapore, Singapore, January 25, 2010.

33. “Robust Principal Component Analysis via Convex Optimization,” Invited talk at Department of Infor-mation Engineering, Chinese University of Hong Kong, January 8, 2010.

34. “Robust Principal Component Analysis via Convex Optimization,” Invited talk at Computer ScienceDepartment, Hong Kong University of Science and Technology, Hong Kong, January 6, 2010. Year 2009:

35. “Face Recognition via Sparse Representation,” Invited talk at the Third Research Institure of the De-partment of Public Safty, Shanghai, China, December 19, 2009.

36. “Confluence of Computer Vision and Sparse Representation,” Invited talk at University of Science andTechnology of China, Hefei, China, December 14, 2009.

37. “Fast Convex Optimization Algorithms for Exact Recovery of a Low-Rank Matrix,” Invited talk at theInternational Workshop on Computationl Advances in Multi-Sensor Adaptive Processing, Aruba, DutchAntilles, December 13-16, 2009.

38. “Robust Principal Component Analysis via Convex Optimization,” talk at MSRA Technical AdvisoryBoard Review, China, November 2, 2009.

39. “Confluence of Computer Vision and Sparse Representation,” Invited talk at CAD & CG state key lab,Zhejiang University, China, October 22, 2009.

40. “Multiple-View Geometry and Symmetry for Image-Based 3D Reconstruction,” Keynote speech atACCV workshop on Community Based 3D Content and its Applications in Mobile Internet Environment,September 24, 2009.

41. “Confluence of Computer Vision and Sparse Representation,” Invited talk National Taiwan University,Taiwan, August 28, 2009.

42. “Robust Principal Component Analysis via Convex Optimization,” Invited talk Academia Sinica, Insti-tute of Information Science, Taiwan, August 27, 2009.

43. “Robust Principal Component Analysis via Convex Optimization,” Invited talk at National TsinghuaUniversity, Taiwan, August 26, 2009.

44. “Confluence of Computer Vision and Sparse Representation,” Keynote speech at the 22th IPPR Con-ference on Computer Vision, Graphics, and Image Processing, Taiwan, August 24, 2009.

45. Keynote speech at International Workshop on Local and Non-Local Approximation in Image Processing,Finland, August 19-21, 2009.

46. Invited talk at Intl. Conf. Sampling Theory and Applications, Marseillle, France, May 18-22, 2009.

47. Plenary talk at Picture Coding Symposium, Chicago, USA, May 6-8, 2009.

48. “Subspace Arrangements and Manifold Learning,” invited talk at Workshop on Multi-Manifold DataModeling and Applications, Institute for Mathematics and Its Applications, October 27-30 2008.

49. “Compressed Sensing and Its Applications in Pattern Recognition and Computer Vision,” mini-courseat Micorsoft Research Asia, Beijing, August, 2008.

50. “Subspace Segmentation via Lossy Data Compression,” invited talk at SIAM Conference on ImagingScience, Minisymposium on Hybrid Linear and Nonlinear Modeling and its Applications, July 7-9, 2008.

51. “Sparse Representation-based Classification and its Applications,” invited talk at SIAM Conference onImaging Science, Minisymposium on Locally Adaptive Patch-based Image and Video Restoration, July7-9, 2008.

52. “Robust Face Recognition via Sparse Representation,” invited talk at Micorsoft Research, Redmond,March 11, 2008.

53. “Sparse Representation-based Classification and its Applications,” invited talk at Systemes Seminar,Department of Electrical and Computer Engineering, University of Wisconsin at Madison, February 27,2008.

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54. “Face Recognition via Sparse Representation,” invited talk at von Neumann Symposium of AppliedMathematics, Snowbird, Utah, July 8, 2007.

55. “Clustering and Classification via Lossy Data Compression,” Computer Science Department, StanfordUniversity, May 17, 2007.

56. “Face Recognition via Sparse Representation,” Computer Vision Seminar, EECS Department, Universityof California at Berkeley, May 8, 2007.

57. “Face Recognition via Sparse Representation,” Computer Vision Seminar, Computer Science Depart-ment, University of California at San Diego, May 4, 2007.

58. “Clustering and Classification via Lossy Data Compression,” Computer Vision Group Seminar, ElectricalEngineering Department, California Institute of Technology, May 2, 2007.

59. “Clustering and Classification via Lossy Data Compression,” Computer Science Department Seminar,University of California at Los Angeles, May 1, 2007.

60. “Face Recognition via Sparse Representation,” CSAIL Computer Vision Seminar, EECS Department,Massachusetts Institute of Technology, April 25, 2007.

61. “Clustering and Classification via Lossy Data Compression,” LIDS Special Seminar, EECS Department,Massachusetts Institute of Technology, April 25, 2007.

62. “Clustering and Classification via Lossy Data Compression,” GRASP Laboratory Seminar, Universityof Pennsylvania, March 23, 2007.

63. “Clustering and Classification via Lossy Data Compression,” Center for Imaging Science Seminar, JohnsHopkins University, March 20, 2007.

64. “Clustering and Classification via Lossy Data Compression,” Computer Vision Seminar, EECS Depart-ment, University of California at Berkeley, March 7, 2007.

65. “Clustering and Classification via Lossy Data Compression,” Fessenden Lecture and Graduate Seminar,Electrical & Computer Engineering Department, IEEE EMB Society Pittsburgh Chapter, University ofPittsburgh, February 28, 2007.

66. “Clustering and Classification via Lossy Data Compression,” Machine Vision Seminar, Computer ScienceDepartment, Carnegie Mellon University, February 26, 2007.

67. “Clustering and Classification via Lossy Data Compression,” Mathematics Department, University ofMichigan, February 6, 2007.

68. “Clustering and Classification via Lossy Data Compression,” Electrical Engineering and Computer Sci-ence Department, University of Michigan, February 5, 2007.

69. “Clustering and Classification via Lossy Data Compression,” Electrical Engineering and Computer Sci-ence Department, Northwestern University, January 25, 2007.

70. “How Did I Learn to Do Research, or Did I?” Intern Training Seminar, Microsoft Research Asia, Beijing,China, December 8, 2006.

71. “Segmentation of Multivariate Mixed Data via Lossy Data Compression,” Department of Automation,Tsinghua University, China, September 22, 2006.

72. “Segmentation of Multivariate Mixed Data via Lossy Data Compression,” School of Electronics Engi-neering and Computer Science, Beijing University, China, September 18, 2006.

73. “Segmentation of Multivariate Mixed Data via Lossy Data Compression,” Department of Electronics,Tsinghua University, China, August 31, 2006.

74. “Image, Geometry and Symmetry,” international workshop on Current Trends in Computer Vision,panel on ”Geometric Vision,” Lhasa of Tibet, China, August 10, 2006.

75. “Video Segmentation via Lossy Data Compression,” international workshop on Current Trends in Com-puter Vision, panel on ”Dynamical Vision,” Lhasa of Tibet, China, August 10, 2006.

76. “Segmentation of Multivariate Mixed Data,” Computer Sciene Department, Zhejiang University, Hangzhou,China, July 12, 2006.

77. “Segmentation of Multivariate Mixed Data,” Microsoft Research Asia, Beijing China, June 24, 2006.

78. “Modeling and Segmentation of Multivariate Mixed Data,” EECS Department Colloquium, UC Berkeley,April 12, 2006.

79. “Segmentation of Multivariate Mixed Data,” Mathematics Department Graduate Seminar, Universityof Illinois at Urbana-Champaign, April 5, 2006.

80. “Segmentation of Multivariate Mixed Data,” Nonlinear Control Seminar, Coordinated Science Labora-tory, University of Illinois at Urbana-Champaign, March 29, 2006.

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81. “Segmentation of Multivariate Mixed Data,” Statistics Department Seminar, University of Illinois atUrbana-Champaign, March 9, 2006.

82. “Multi-Scale Hybrid Linear Models for Image Representation,” Robotics Lab Seminar, EECS Depart-ment, University of California at Berkeley, June 14, 2005.

83. “Vision, Geometry, and Symmetry,” Institute of Computer Science, Sichuan University, Chendu, China,May 30, 2005.

84. “Multi-Scale Hybrid Linear Models for Lossy Image Representation,” Automation Department Seminar,Tsinghua University, Beijing, China, May 19, 2005.

85. “Motion-Based Image Segmentation,” Microsoft Research in Asia, Beijing, China, May 19, 2005.

86. “Multi-Scale Hybrid Linear Models for Lossy Image Representation,” Microsoft Research inAsia, Beijing,China, May 18, 2005.

87. “Generalized Principal Component Analysis and Its Applications,” Computer Science Department, Ts-inghua University, Beijing, China, May 17, 2005.

88. “Motion-Based Image Segmentation,” Human/Computer Vision Symposium, Beckman Institute, May13, 2005.

89. “Multi-Scale Hybrid Linear Models for Lossy Image Representation,” vision/graphics/HCI day, Com-puter Science Department, University of Illinois, April 15, 2005.

90. “Identification of Hybrid ARX Systems,” Control Seminar, Coordinated Science Laboratory, Universityof Illinois, February 2, 2005.

91. “Vision, Geometry, and Symmetry,” the Center for Imaging Science, Johns Hopkins University, Novem-ber 16, 2004.

92. “Generalized Principal Component Analysis and its Applications,” the ITG forum of Beckman Institute,UIUC, September 21, 2004.

93. “Generalized Principal Component Analysis and its Applications,” Control and Robotics Seminar,EECS, UC Berkeley, August 2004.

94. “Geometric Vision,” invited one-day lectures, World Congress on Intelligent Control and Automation,Hangzhou, China, June 14-18, 2004.

95. “Generalized Principal Component Analysis,” DSP seminar, ECE UIUC, April 2004.

96. “Vision, Geometry, and Symmetry,” the Center for Automation Research, University of Maryland, May9th, 2003.

97. “Image and Geometry,” the Applied Mathematics Seminar, Mathematics Department, UIUC, March 3,2003.

98. “Image and Geometry,” the DSP seminar, UIUC, December 11, 2002.

99. “Group Symmetry and Multiple View Geometry,” Berkeley AI/ Robotics/Vision Seminar, RoboticsGroup, September 19, 2002.

100. “Multiple-View Multibody Structure from Motion,” Center for Intelligent and Networked Systems, Au-tomation Department, Tsinghua University, Beijing (China), May 24, 2002.

101. “Multiple-View Multibody Structure from Motion,” Microsoft Research in Asia, Beijing (China), May22, 2002.

102. “Multiple-View Multibody Structure from Motion,” Microsoft Research, Redmond, May 17, 2002.

103. “Multiple-View Multibody Structure from Motion,” Special computer vision seminar, UIUC, May 8,2002.

104. “Computer and Robot Vision,” ECE Department Explorations Seminar, UIUC, February 20th, 2002.

105. “Rank Conditions in Multiple View Geometry,” Visual Computation Group Seminar, Microsoft Researchin Asia, Beijing, February 4th, 2002.

106. “Recognition of Human Gait,” Image Formation and Processing Group, Beckman Institute, January 18,2002.

107. “Overview of Multiple View Geometry,” Math & ECE RAP program, Beckman Institute, UIUC, January18, 2002.

108. “Rank Conditions in Multiple View Geometry,” GRASP Lab Seminar, University of Pennsylvania,November 2, 2001.

109. “Rank Conditions in Multiple View Geometry,” EECS Department, AI Lab Colloquium, MIT, November1, 2001.

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110. “Rank Conditions in Multiple View Geometry,” Robotics Lab, DEAS, Harvard University, November 1,2001.

111. “Multiple View Geometry Unified,” EE Department, Stanford University, May 17, 2001.31.

112. “Multiple View Geometry Unified,” EECS Department Computer Vision Seminar, UC Berkeley, May16, 2001.

113. “Multiple View Geometry Unified,” CSL Nonlinear Control Seminar, UIUC, May 10, 2001.

114. “Vision Based Control,” ECE Department Graduate Seminar, UIUC, November 2, 2000.

• Workshops, Tutorials, Seminars, and Projects (as Organizer):

1. Lecturer for a half-day tutorial on ”Low-rank Models: Theory, Algorithm, and Applications,” CCFADL27, China, May 18, 2012.

2. Organizer and lecturer for a half-day tutorial on “Low-rank Methods for Computer Vision,” ICIG, Hefei,China, August 11, 2011.

3. Organizer and lecturer for a half-day tutorial on “Sparse and Low-rank Methods for Computer Visionand Image Processing,” VLPR summer school, Chendu, China, August 9, 2011.

4. Organizer of a half-day tutorial on Low-Rank Matrix Recovery, ICIP, Hongkong, Sept. 26, 2010.

5. Organizer of a half-day tutorial on Subspace Learning at CVPR, San Francisco, June 14, 2010.

6. Organizer of a one-day workshop on Dynamical Vision at International Conference on Computer Vision,Kyoto, Japan, September 29, 2009.

7. Organizer of a half-day tutorial on Sparse Representation and Its Applications in High-DimensionalPattern Recognition at International Conference on Computer Vision and Pattern Recognition, Miami,USA, June 20, 2009.

8. Organizer of a half-day tutorial on Generalized Principal Component Analysis at the International Con-ference on Computer Vision and Pattern Recognition, June 23, 2008.

9. Organizer of a half-day tutorial on Computational Symmetry at the International Conference on Com-puter Vision and Pattern Recognition, June 23, 2008.

10. Organizer of a one-day workshop on Dynamical Vision at the International Conference on ComputerVision, October 2007.

11. Organizer of a half-day tutorial on Generalized Principal Component Analysis at IEEE InternationalConference on Computer Vision and Pattern Recognition, Minneapolis, June 18, 2007.

12. Coorganizer of a three-day workshop on the Current Trends in Computer Vision, Tibet, China, August2006.

13. Organizer of a one-day workshop on Dynamical Vision at the European Conference on Computer Vision,May 2006.

14. Organizer of a one-day workshop on Dynamical Vision at the International Conference on ComputerVision, October 2005.

15. Organizer of a half-day tutorial on Multiple-View Geometry for Image-Based Modeling at the Interna-tional Conference on Image Processing, September 11, 2005.

16. Co-organizer of the invited session: Hybrid Systems Identification at the IEEE Conference on Decision& Control, Bahamas, December 2004.

17. Organizer of a one-day course: Multiple-View Geometry for Image-Based Modeling at SIGGRAPH’03,San Diego, July 2003, and at SIGGRAPH’04, Los Angeles, August 2004.

18. Co-organizer (with Jana Kosecka) of a one-day course: 3-D Reconstruction and Motion Analysis atICRA’03, Taipei, Taiwan, September 2003, and at ICRA’04, New Orleans, April 2004.

19. Co-chair of Geometry and Algebra of Computer Vision, the Research Among Peers (RAP) program withProfessor Robert Fossum, Mathematics Department, UIUC, 2002–Present.

20. Organizer and chair of the invited session: Dynamical Vision and Control at the Allerton Conference,Illinois, October 2002.

21. Co-organizer and co-chair of the invited session: Feedback and Control in Biological Systems at theAllerton Conference, Illinois, October 2001.

22. Co-organizer of the tutorial: A Geometric Viewpoint to Recovery of Structure and Motion from ImageSequences at IEEE International Conference on Robotics and Automation (ICRA), San Francisco, April2000.

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• Research Grants

1. NSF IIS: A Holistic Approach to Reconstructing Urban Scenes, PI, $400,000, 2011 - 2014.

2. DARPA KECoM: Scene and Task Aware Knowledge Enhanced Compressive Sensing, co-PI, $300,000,DARPA, 2011-2013.

3. NSF CCF: Advances in the Theory and Practice of Low-Rank Matrix Recovery and Modeling, PI,$950,000, National Science Foundation, 2010-2014.

4. ONR: Harnessing Sparse and Low-Dimensional Structures for Robust Clustering of Visual Data, PI,$600,000, Office of Naval Research, 2009-2012.

5. NSF IIS: SGER: Explorations of Robust Image Classification, PI, $100,000, National Science Foundation,2008-2009.

6. NSF CISE: PHYSNET: Physical Interaction Using the Internet, co-PI, $150,000, National Science Foun-dation, 2007-2010.

7. NSF ECCS: Control and Sensing under Limited Information, co-PI, $270,000, National Science Foun-dation, 2007-2010.

8. ONR YIP: Estimation of Hybrid Models in Computer Vision, PI $300,000, Office of Naval Research,2005-2008.

9. NSF CRS-EHS: Collaborative Research: An Algebraic Geometric Approach to Hybrid Systems Identi-fication, PI, $350,000, National Science Foundation, 2005-2008.

10. NSF CCF-TF: Estimation of Hybrid Models as Algebraic Sets, PI, $230,000, National Science Founda-tion, 2005-2008.

11. NSF CAREER IIS: Identifying Spatial and Dynamical Patterns from Images, PI, $400,000, NationalScience Foundation, 2004-2008.

12. Vision Based Control, PI, $23,000, UIUC Research Board, 2000.

13. Co-founder of the BErkeley Aerial Robot (BEAR) project, funded by DARPA, ONR, and NSF. EECSDepartment, U. C. Berkeley, 1997–2000.

• Professorional Services & Activities:

– Associate Editor of the Information and Inference: a Journal of the Institute of Mathematics and itsApplications, since 2011.

– Associate Editor of International Journal of Computer Vision, since 2010.

– Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007 – 2011.

– Associate Editor of IEEE Control Systems Society Conference Editorial Board (CEB), 2000 – 2004.

– Guest Editor for a special issue on Real-World Face Recognition, with Hua Gang et. al., IEEE Transac-tions on Pattern Analysis and Machine Intelligence, to appear in 2011.

– Chief Guest Editor for a special issue on Dimensionality Reduction via Subspace and Manifold Learning,with Partha Niyogi, Guillermo Sapiro, and Rene Vidal, IEEE Signal Processing Magazine, March 2011.

– Chief Guest Editor for a special issue on Sparse Representation and Compressive Sensing, with Em-manuel Candes, Richard Baraniuk, and Michael Elad, the Proceedings of IEEE, June 2010.

– Journal Paper Reviews: CVIU, JMIV, IJCV, Automatica, IEEE Transactions on Information Theory,Image Processing, PAMI, and Robotics & Automation.

– General Chair, International Conference on Computer Vision, 2015.

– Program Chair, International Conference on Computer Vision, 2013.

– Award Committee, IEEE International Conference on Computer Vision and Pattern Recognition, 2012.

– Award Committee, International Conference on Computer Vision, 2011.

– Area Chair and Program Board, International Conference on Computer Vision, 2011.

– Area Chair, Neural Information Processing Systems (NIPS), 2011.

– NSF CISE III panel review, 2008.

– NSF CISE CNS panel review, 2008.

– NSF ECCS PCAN panel review, June 2007.

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– NSF CISE IIS panel review, March 2007.

– NSF CISE CRI panel review, November 2, 2005.

– NSF-IIS CAREER award panel review, November 12, 2004.

– Affiliated with the Applied Mathematics Program, Mathematics Department, University of Illinois atUrbana-Champaign, since 2002.

– Affiliated with the Computer Science Department, University of Illinois at Urbana-Champaign, since2008.

– Visiting Researcher at Microsoft Research Asia, Beijing, China, summer of 2002 and 2005.

– Visiting Senior Researcher at Microsoft Research Asia, Beijing, China, fall 2006.

• Professional Societies:

1. Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).

2. Member of Association for Computing Machinery (ACM).

3. Member of SIAM and ASEE.

• Teaching Activities:

1. Faculty member in the Department of Electrical & Computer Engineering, University of Illinois atUrbana-Champaign, 2000-Present. Courses Taught:

(a) Sparse Representation and High-Dimensional Geometry(b) Estimation and Segmentation of Hybrid Models(c) Advanced Geometric Approach to Computer Vision(d) Control Systems Theory and Design(e) Nonlinear System Analysis and Control(f) Optimum Control Systems(g) Random and Stochastic Processes(h) Analogue Signal Processing

Three times on the Incomplete List of Teachers Ranked as Excellent (voted by the students) ofthe University of Illinois at Urbana-Champaign, Spring 2001, Fall 2002, and Spring 2006.

2. Teaching Associate, Advanced Topics in Robotics: Computer Vision, EECS, University of California atBerkeley, Spring 1999.

3. Teaching Assistant, Stochastic and Random Process Systems, EECS, University of California at Berkeley,Fall 1997.

4. Teaching Assistant, Electronic Techniques for Engineering, EECS, University of California at Berkeley,Spring 1997.

• Doctoral Students (Graduated):

1. Kun Huang, PhD in Electrical Engineering, Thesis: Geometric Principles of Multiple Visual Sensors,August 2004. Now an associate professor at the Ohio State University.

2. Wei Hong, PhD in Electrical Engineering, Thesis: Hybrid Models for Representation of Imagery Data,May 2006. Now a researcher at Texas Instruments Research Lab.

3. Allen Yang Yang, PhD in Electrical Engineering, Thesis: Estimation of Subspace Arrangements: ItsAlgebra and Statistics, May 2006. Now a research scientist at UC Berkeley.

4. John Wright, PhD in Electrical Engineering, Thesis: High-Dimensional Data Analysis with Applicationsin Computer Vision, May 2009. Now a researcher at Microsoft Research Asia.

5. Shankar Rao, PhD in Electrical Engineering, Thesis: Harnessing Low-Dimensional and Sparse Structuresfor High-Dimensional Data Clustering, May 2009. Now a researcher at HRL Laboratories, LLC, Malibu,California.

6. John Wright, Ph.D. in Electrical Engineering, Thesis: Error Correction for High-Dimensional Data viaConvex Optimization, May 2009, now an Assistant Professor at Columbia University.

7. Yoav Sharon, Ph.D. in Electrical Engineering, Thesis: Vision Based Control with Limited and QuantizedInformation, May 2010, now a postdoc researcher at MIT.

8. Andrew Wagner, Ph.D. in Electrical Engineering, Thesis: Fast and Robust Face Recognition via Paral-lelized L1 Minimization, August 2011, now a postdoc researcher in Belgium.

9. Arvind Ganesh Balasubramanian, Ph.D. in Electrical Engineering, Thesis: Low-rank Matrix Recoveryand Its Applications in Computer Vision, May 2012, now a researcher at IBM Research, India.

15

Venkatesh Saligrama

A. Education

Ph.D, Massachusetts Institute of Technology, Cambridge, MA, 1997

B. Professional Experience

2011- present, Professor, ECE, Boston University, Boston, MA

2005 – 2010, Associate Professor, ECE, Boston University, Boston, MA

2008 – present, Research Affiliate, LIDS, MIT, Cambridge, MA

2001 – 2005, Assistant Professor, ECE, Boston University, Boston, MA

1997 – 2001, Research Scientist, United Technologies Research Center, Hartford, CT

C. Research Interests

Machine Learning, Statistical Signal Processing, Information and Control theory, Computer

Vision, Sensor Networks

D. Professional Service

Lead Guest Editor, Anomalous Pattern Discovery for Spatial, Temporal, Networked and High-

Dimensional Signals, IEEE Journal on Selected Topics in Signal Processing, 2012

IEEE Senior Member, 2009 – present

Regional Officer, IEEE Signal Processing Society, (2010 - present)

Demonstration Chair, IEEE Advanced Video and Signal Based Surveillance, 2010

Member: IEEE Signal Processing Theory and Methods Board, 2009-present

Program Committee Member: IFAC Symp. On System Identification, 2009, 2011

Program Committee Member: IEEE Statistical Signal Processing Workshop, Aug. 2007

General Chair: NSF International Workshop on Networked Sensing, Boston, May 25/26, 06

Invited Session Organizer: Statistical Signal Processing in Sensor Networks, ICASSP 2005

Associate Editor, IEEE Transactions on Signal Processing, 2004-2008

Associate Editor, Control Conference Editorial Board, 2003 - 2005.

Program Committee Member, IEEE Decision and Control Conference, 2002

Invited Session Organizer, Large Scale Optimization and Control, 2001

E. Honors

Marquis Who's Who in America, 2011

Featured Speaker, Homeland Security Summit, March, 2009

Keynote Speaker, RICC, Northeastern University, Oct. 2008

Plenary Speaker, Northeast Control Conference, MIT, Cambridge, MA 2006

Crossbow Sensor Network Challenge Competition, Finalist, 2005

NSF CAREER Award, 2005

Presidential Early Career Award, 2003

Office of Naval Research Young Investigator Award, 2002

Plenary Speaker, LIDS Student Conference, MIT, 2001

Outstanding Achievement Award, United Technologies, 1998

Student Best Disssertation Runner-Up, ACM/IEEE ICDSC, 2008

Best Presentation Award, American Control Conference 1996

Publications. Books:

1) V. Saligrama Eds, ``Networked Sensing, Information and Control,’’ Springer Verlag 2008,

in Lecture Notes in Electrical Engineering

Book Chapters:

2) E. Ermis, V. Saligrama, P. Jodoin, ``Information Fusion and Anomaly Detection with

Uncalibrated Cameras in Surveillance,’’ in Multimedia Information Extraction, M.

Maybury (eds), IEEE Computer Society Press, 2010

3) Y. Benezeth, P. Jodoin, V. Saligrama, `` Modeling Patterns of Activity and Detecting

Abnormal Events with Low Level Co-occurrence of activity,’’ in Distributed Video

Sensor Networks, Bir Bhanu et. al. (eds), Springer 2010

4) Alanyali, M., Saligrama, V., “In-Network Decision Making via Local Message Passing,”

in Advances in Pervasive Computing and Networking, Pages. 119-133, Szymanski et. al.

(eds) Kluwer Academic Publishers, 2004

5) Martins, N. C.; Venkatesh, S.; Dahleh M.A., “Resource Allocation in Large-Scale

Systems: A Block Decoupling Approach,” Pages 41-48, Filipe et. al. (eds), Enterprise

Information Systems, Kluwer Academic Publishers, 2002.

Journal:

6) V. Saligrama, Deterministic Designs with Deterministic Guarantees: Toeplitz Compressed

Sensing Matrices, Sequence Designs and System Identification, IEEE Transactions on

Information Theory, to appear.

7) E. Chan, S. Jaggi, V. Saligrama, S. Agnihotri, Non-adaptive Group Testing: Explicit bounds

and novel algorithms, IEEE Trans. on Information Theory, submitted.

8) G. Atia, V. Saligrama, ``Boolean Compressed Sensing and Noisy Group Testing,’’ IEEE

Trans. on Information Theory, March 2012.

9) M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, ``Graph Constrained Group

Testing,’’ IEEE Trans. on Information Theory, Jan. 2012.

10) V. Saligrama, M. Alanyali, ``Token Based Algorithms for Distributed Computation,’’ IEEE

Journal of Selected Areas in Signal Processing, Aug. 2011

11) V. Saligrama, M. Zhao, ``Thresholded Basis Pursuit: A Linear Programming Approach to

Optimal Support Recovery of Compressed Sparse Signals,’’ IEEE Transactions on

Information Theory, March 2011

12) Y. Benezeth, P. Jodoin, V. Saligrama, ``Abnormality Detection Using Low-Level Co-

occurring Events,’’ Pattern Recognition Letters, 2011

13) S. Aeron, V. Saligrama, M. Zhao, ``Information Theoretic Analysis for Compressed

Sensing,’’ IEEE Trans. on Information Theory, Oct. 2010

14) S. Aeron, S. Bose, H. P. Valero, V. Saligrama, Broadband Dispersion Extraction Using

Simultaneous Sparse Penalization, IEEE Transactions on Signal Processing, 2011

15) P.M. Jodoin, V. Saligrama, ``Behavior Subtraction,’’ IEEE Trans. on Image Processing,

Revised Jan 2012

16) E. Ermis, P. Jodoin, V. Saligrama, ``Activity Based Matching in Multi-Camera Networks,’’

IEEE Trans. on Image Processing, Nov. 2010.

17) V. Saligrama, J. Konrad, V. Saligrama, `` Video Anomaly Identification,’’ IEEE Signal

Processing Magazine, pages: 18-33, Sept. 2010.

18) E. Ermis, V. Saligrama, ``Distributed Detection for Multi-Modal Limited Range Sensors,’’

IEEE Transactions on Signal Processing, pages 843-858, Jan 2010

19) J. McHugh, J. Konrad, V. Saligrama, and P.-M. Jodoin, ``Foreground-adaptive background

subtraction,'' IEEE Signal Process. Lett., pages 390-393, Sep. 2009.

20) A. Sahai, K.Woyach, G. Atia, and V. Saligrama, “A technical perspective on light-handed

regulation for cognitive radios,” pages 96-102, IEEE Communications Magazine, Jan 2009

21) S. Aeron, V. Saligrama, D. Castanon, ``Energy efficient policies for distributed target

tracking in multi-hop sensor networks'', IEEE Transactions on Signal Processing,’’ Vol. 56,

pages: 2562 – 2574, 2008

22) Y. Wang, P. Ishwar, V. Saligrama, ``One-Bit Distributed Sensing and Coding for Field

Estimation in Sensor Networks,’’ vol. 56, pages: 4433 – 4445, IEEE Transactions on Signal

Processing, 2008

23) G. Atia, M. Sharif, V. Saligrama, “On Optimal Outage in Relay Channels with General

Fading Distributions,” vol. 53., Pages 3786 – 3797, IEEE Transactions on Information

Theory, 2007.

24) S. Aeron, V. Saligrama, “Wireless Ad-hoc networks: Strategies and scaling laws in Fixed

SNR regime,” vol. 53, pages: 2044 – 2059, IEEE Transactions on Information Theory, 2007

25) R. Rahman, M. Alanyali, V. Saligrama, ``Distributed Tracking in Multi-hop Sensor

Networks with Communication Delays,’’ vol. 55, pages 4656 – 4668, IEEE Transactions in

Signal Processing, 2007

26) V. Saligrama, M. Alanyali, O. Savas, “Distributed Detection in Sensor Networks with Finite

Capacity Links and Packet Losses,” vol. 54, pages: 4118 – 4132, IEEE Transactions on

Signal Processing, Nov. 2006

27) E. Ermis, M. Alanyali, V. Saligrama, “Search and Discovery in an Uncertain Networked

World” IEEE Signal Processing Magazine, vol. 23, pages: 107 – 118, July 2006

28) V. Saligrama, “A Convex Analytic Approach to System Identification,” IEEE Transactions

on Automatic Control, vol. 50, no. 10, Pages 1550-1567, Oct. 2005

29) S. Venkatesh, “Necessary Conditions for Identification of Uncertain Systems,” Systems and

Control Letters, vol. 53, No. 2, Pages 117-125, Oct. 2004

30) V. Borkar, S. Mitter, S. Venkatesh, “Variations on a Neyman Pearson Theme,” Journal of

the Indian Statistical Institute, vol. 66, Part I, Pages 1-14 pages, May 2004

31) S. Venkatesh, S. Narayanan and D. Polak, “A new beamforming algorithm for Jet Noise

Imaging”, AIAA Journal, vol. 41, No. 7A, Pages 1238-1246, August. 2003

32) S. Venkatesh, Y. Cho and J. Kim, “Robust control of vertical motions in ultra-high rise

elevators,” Control Engineering Practice, vol. 10, Pages 121-132, Feb. 2002

33) S. Venkatesh and Y. Cho, “Identification, Validation and Control for High-Speed-High-Rise

Elevators,” ASME Journal of Measurement, Instrumentation and Control, vol. 123, Pages

687-690, Dec. 2001.

34) S. Venkatesh and M. A. Dahleh, “On the sample complexity of Hinfty Identification,”

Journal of Robust and Non-linear Control, vol. 11, Pages 621-632, June 2001.

35) S. Venkatesh and M. A. Dahleh, “On System-Identification of Complex-Systems with Finite

Data,” IEEE Transactions on Automatic Control, vol. 46, No. 2, Pages 235-257, Feb 2001.

36) S. Venkatesh and M. Dahleh, “On Learning the Input/Output behavior of Non-linear Fading

Memory System from Finite Data,” Journal of Robust and Non-linear Control, vol. 10,

Pages 931-959, Oct. 2000.

37) S. Venkatesh, A. Megretski and M. Dahleh, “Robust Control and Analysis on a Hilbert

Space,” Systems and Control Letters, vol. 39, Pages 1-12, Jan 2000.

38) S. Venkatesh and M. A. Dahleh, “Identification in the presence of classes of unmodeled

dynamics and noise,” IEEE Transactions on Automatic Control, vol. 42, no. 12, Pages 1620-

1635, Dec. 1997.

39) S. Venkatesh and M. A. Dahleh, “Extreme Cases in L1 and H∞ Optimization,” System and

Control Letters, vol. 23, Pages 229-236, Feb. 1994

Refereed Conferences:

1) V. Saligrama, M. Zhao, Local Anomaly Detection, AISTATS 2012

2) V. Saligrama, Z. Chen, Video Anomaly Detection Based on Local Statistical Aggregates,

IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2012

3) P. Jones, S. Mitter, V. Saligrama, Bayesian Filtering without an Observation Model, IEEE

Conference on Decision and Control, 2012, submitted.

4) E. Chan, S. Jaggi, V. Saligrama, S. Agnihotri, Non-adaptive Group Testing: Explicit

bounds and novel algorithms, ISIT 2012, submitted

5) J. Wang, V. Saligrama, D. Castanon, Structural Similarity and Distance in Learning,

Allerton 2011

6) B. Orten, P. Ishwar, W. Karl, V. Saligrama, Sensing Structure in Learning-Based Binary

Classification of High-Dimensional Data: Opportunities and Perils, Allerton 2011

7) C. L. Park, S. Jaggi, V. Saligrama, Non-adaptive probabilistic group testing with noisy

measurements: Near-optimal bounds with efficient algorithms, Allerton 2011

8) B. Orten, P. Ishwar, V. Saligrama, H. Pien, Sensing-aware classification with high-

dimensional data, ICASSP 2011

9) K. Trapeznikov, V. Saligrama, D. Castanon, “Active Boosted Learning,” AISTATS 2011

10) P. Jones, V. Saligrama, S. Mitter, Probabilistic Belief Revision with Structural Constraints,

NIPS 2010

11) J. Wang, V. Saligrama, D. Castanon, “Markov and Hidden Markov Model Group Testing,”

Allerton UIUC 2010

12) D. Motamedvaziri, V. Saligrama, D. Castanon, ``Decentralized Compressive Sensing,”

Allerton UIUC 2010

13) P. Jones, S. Mitter, V. Saligrama, “Revision of Marginal Probability Assessments,” Fusion

2010, Edinburgh, UK

14) R. Kumar, D. Castanon, E. Ermis, V. Saligrama, “A new algorithm for outlier rejection in

particle filters,” Fusion 2010, Edinburgh, UK

15) M. Zhao, V. Saligrama, “ Noisy Filtered Processes: Reconstruction and

Compression,” IEEE Conference on Decision and Control, Atlanta, Dec. 2010

16) M. Zhao, V. Saligrama, ``Compressed Blind Deconvolution,’’ ICASSP 2010

17) M. Cheraghchi, A. Karbasi, S. Mohajer, V. Saligrama, ``Graph Constrained Group

Testing,’’ ISIT. 2010.

18) S. Aeron, S. Bose, H.P. Valero, V. Saligrama, `` Sparsity Penalized Reconstruction

Framework for Broadband Dispersion Extraction,’’ ICASSP 2010

19) M. Zhao, V. Saligrama, ``Anomaly Detection with Score Functions on K Nearest Neighbor

Graphs,’’ NIPS 2009, (Spotlight Presentation)

20) G. Atia, V. Saligrama, ``Information Theoretic Approach to Noisy Group Testing,’’

Allerton, UIUC 2009

21) Jodoin P-M, Saligrama V. Konrad J., Implicit Active-Contouring with MRF,

International Conference on Image Analysis and Recognition (ICIAR), 2009

22) Y. Benezeth, P. M. Jodoin, and V. Saligrama, and C. Rosenberger, ``Abnormal Events

Detection Based on Spatio-Temporal Co-occurences,'' in IEEE Computer Society

Conference on Computer Vision and Pattern Recognition(CVPR), Jun. 2009

23) E. Ermis, P. Clarot, P. M. Jodoin, and V. Saligrama, ``Unsupervised Camera Network

Structure Estimation Based on Activity,'' in ICDSC 2009

24) M. Zhao, V. Saligrama, Outlier detection via localized p-value estimation, Allerton 2009

25) P.-M. Jodoin, V. Saligrama, and J. Konrad, ``Behavior subtraction,'' in Proc. SPIE Visual

Communications and Image Process., vol. 6822, Jan. 2008, pp. 10.1--10.12.

26) E.~Ermis, V. Saligrama, P.-M. Jodoin, and J. Konrad, ``Motion segmentation and abnormal

behavior detection via behavior clustering,'' in Proc. IEEE Int. Conf. Image Processing, pp

769-772, Oct. 2008.

27) P.-M. Jodoin, J. Konrad, V. Saligrama, and V. Veilleux-Gaboury, ``Motion detection with

an unstable camera,'' in Proc. IEEE Int. Conf. Image Processing, Oct. 2008.

28) J. McHugh, J. Konrad, V. Saligrama, P.-M. Jodoin, and D. Castanon, ``Motion detection

with false discovery rate control,'' in Proc. IEEE Int. Conf. Image Processing, Oct. 2008.

29) E. Ermis, V. Saligrama, P.-M. Jodoin, and J. Konrad, ``Abnormal behavior detection and

behavior matching for networked cameras,'' in ACM/IEEE Int. Conf. Distributed Smart

Cameras, Sep. 2008. (Best Dissertation runner up)

30) P.-M. Jodoin, J. Konrad, and V. Saligrama, ``Modeling background activity for behavior

subtraction,'' in ACM/IEEE Int. Conf. Distributed Smart Cameras, Sep. 2008.

31) S. Aeron, M. Zhao, V. Saligrama, ``Algorithms and Bounds for Sensing Capacity and

Compressed Sensing with Applications to Learning Gaussian Graphical Models,’’

Information Theory and Applications Workshop, UCSD, Jan 2008

32) O. Savas, M. Alanyali and V. Saligrama, ``Efficient In-Network Processing through Local

Ad-hoc Information Coalescence,’’ International Distributed Computing in Sensing

Systems (DCOSS) 2006, San Fransisco, CA.

33) G. Atia, V. Saligrama and A. Sahai, ``Codes to Unmask Spectrum Violators in Cognitive

Radio Systems," in Proceedings of Asilomar Conference on Signals, Systems and

Computers, Pacific Grove, CA Oct. 2008.

34) G. Atia, A. Sahai, V. Saligrama, ``Spectrum Enforcement and Liability Assignment in

Cognitive Radios", in Proceedings of IEEE Dynamic Spectrum Access Networks (DySpan),

October 2008.

35) K. Woyach, A. Sahai, G. Atia, V. Saligrama, ``Crime and punishment for Cognitive

Radios", 46th Annual IEEE Allerton Conference on Communication, Control and

Computing, Monticello IL, Sep. 2008.

36) G. Atia, S. Aeron, E. Ermis, V. Saligrama, ``On Throughput Maximization and

Interference Avoidance in Cognitive Radios," Fifth IEEE Consumer Communications and

Networking Conference CCNC, 2nd IEEE Workshop on Cognitive Radios, Las Vegas, Jan.

2008

37) M. Zhao, S. Aeron, V. Saligrama, ``Sensing Capacity and Compressd Sensing: Bounds and

Algorithms,” Allerton 2007

38) S. Aeron, M. Zhao and V. Saligrama, ``Sensing Capacity, Diversity and Sparsity:

Fundamental Tradeoffs,’’ ITA UCSD Workshop, Feb. 2007

39) E. Ermis, V. Saligrama, `` Robust Detection Strategies for Non-Ideal Sensing Models,”

ICASSP, 2007

40) S. Aeron, M. Zhao and V. Saligrama, ``Fundamental Tradeoffs: Limited Sensing, Sensing

Diversity and Sensing Capacity,'' 40th Asilomar Conference on Signals, Systems and

Computers, Oct. 2006

41) E. Ermis, V. Saligrama, ``Detection and Localization in Sensor Networks Using Distributed

FDR,’’ Conference on Information Sciences and Systems, May 2006

42) E. Ermis, V. Saligrama, ``Detection and Localization in Sensor Networks Using

Distributed FDR,’’ Conference of Information Sciences and Systems, Princeton, NJ 2006

43) M. Alanyali, V. Saligrama and O. Savas, A Random-Walk Model for Distributed

Computation in Energy-Limited Networks," Information Theory and its Applications, San

Diego, CA, 2006.

44) O. Savas, M. Alanyali and V. Saligrama, Efficient In-Network Processing through Local

Ad-hoc Information Coalescence, DCOSS 2006, San Fransisco, CA.

45) V. Saligrama, D. Starobinski “On the Macroscopic Effects of Local Interactions in Wireless

multi-hop networks,” Intl. Symposium on Modeling and Optimization in Mobile, Ad Hoc,

and Wireless Networks, pages 1-8, Boston, MA, April, 2006

46) O. Savas, M. Alanyali, V. Saligrama, ``Randomized Sequential Algorithms for Data

Aggregation in Sensor Networks,’’ Conference of Information Sciences and Systems,

Princeton, NJ 2006

47) S. Aeron, V. Saligrama, Wireless ad-hoc networks: Cooperative Strategies and Scaling

Laws for fixed SNR regime, CTW, Puerto Rico, 2006

48) G. Atia, M. Sharif, V. Saligrama, ``Effect of Geometry on the Diversity-Multiplexing

Tradeoff in Relay Channels,’’ Globecom, Nov 2006, San Francisco, CA

49) G. Atia, M. Sharif, V. Saligrama, ``On Optimal Outage in Relay Channels in the Low SNR

Regime,’’ Forty-Fourth Annual Allerton Conference, Sept. 2006, Allerton House, UIUC,

Illinois, USA

50) G. Atia, M. Sharif, V. Saligrama, ``Outage Capacity of Relay Channels in Low SNR: An

Adaptive Strategy,’’ Communication Theory Workshop, May 2006, Puerto Rico

51) Y. Wang, N. Ma, M. Zhao, P. Ishwar, V. Saligrama ``On Universal Distributed Estimation

of Noisy Fields with One-Bit Sensors,’’ Forty-Fourth Annual Allerton Conference, Sept.

2006, Allerton House, UIUC, Illinois, USA

52) V. Saligrama, D. Castanon, ``Reliable Tracking over unreliable communication links,''

ICASSP, Toulouse, France, 2006

53) V. Saligrama, D. Castanon, ``Reliable Distributed Estimation with Intermittent

Communications,'' IEEE Control and Decision Conference, San Diego, CA, 2006

54) S. Aeron, V. Saligrama, D. Castanon, ``Energy Efficient Policies for Distributed Target

Tracking in Multihop Sensor Networks,'' IEEE Control and Decision Conference, San

Diego, CA, 2006

55) S. Aeron, V. Saligrama, D. Castanon, ``Distributed Target tracking and localization in

multi-hop networks,” Conference of Information Sciences and Systems, Princeton, NJ 2006

56) M. Alanyali, V. Saligrama, ``Distributed Tracking in Multi-hop Networks,’’ IEEE

Statistical Signal Processing Workshop, Bordeaux, France, 2005

57) E. Ermis, V. Saligrama, Adaptive Statistical Sampling Methods for Decentralized

Estimation and Detection of Localized Phenomena, Information Processing in Sensor

Networks, Los Angeles, CA, April 2005

58) E. Ermis, V. Saligrama, Decentralized Detection and Estimation of localized phenomena,

International Conference on Acoustics Speech and Signal Processing, March 2005

59) S. Venkatesh, M. Alanyali, O. Savas, S. Aeron, Classification in Sensor Networks,

Proceedings of the International Symposium on Information Theory, Page 251, July 2004,

Chicago, IL, USA

60) M. Alanyali, S. Venkatesh, S. Aeron and O. Savas, Distributed Bayesian Hypothesis

Testing, Proceedings of American Control Conference, Boston, MA, June 2004

61) S. Venkatesh, Y. Shi, W. Karl, Performance Guarantees in Sensor Networks, Proceedings

of the IEEE International Conference On Acoustics, Speech, and Signal Processing, Pages

269-272, May 2004, Montreal, Canada

62) S. Venkatesh, M. Alanyali, M-Ary Hypothesis Testing in Sensor Networks, Conference on

Information Sciences and Systems, Feb. 2004, Princeton, NJ 2004

63) S. Aeron, S. Venkatesh, Capacity Scaling in Wireless Networks with O(n-1/3

) scaling,

Proceedings of the International Symposium on Information Theory, Page 469, July 2004,

Chicago, IL, USA

64) S. Aeron, S. Venkatesh, Scaling Laws in Large Wireless Networks, IEEE Statistical Signal

Processing Workshop, Pages 367-370, Sept. 2003, St. Louis, MO, USA

65) S. Venkatesh, P. Voulgaris, C. Hadjicostis, A systems approach to channel equalization,

Proceedings of the 42nd

IEEE Conference on Decision and Control, Pages 3155-3160, Dec.

2003, Hawaii, USA

66) S. Venkatesh, Identification of Systems described by Linear Fractional Transforms,

Proceedings of the IEEE Conference on Decision and Control, Pages 5532 – 5537, Dec.

2003, Hawaii, USA

67) S. Venkatesh and W.C. Karl, A Semi-Definite Programming Approach to Inverse Problems,

37th

Annual Asilomar Conference on Signals, Systems, and Computers, Pages 1943-1947,

Nov. 2003, ASILOMAR, CA

68) S. Venkatesh, Echo-Cancellation in a rapidly time-varying environment, IEEE Statistical

Signal Processing Workshop, Pages 222-225, Sept. 2003, St. Louis, MO, USA

69) S. Venkatesh, System Identification of Rapidly Varying Systems, Proceedings of the IEEE

Conference on Decision and Control, Pages 264-268, Dec. 2002, Las Vegas, NV

70) S. Venkatesh, S. Mitter, Statistical Modeling and Estimation from Finite Data, Proceedings

of the International Symposium on Information Theory, Page 130, July 2002, Lausanne,

Switzerland.

71) C. Kao and S. Venkatesh, Stabilization of Linear Systems with Limited Information,

Proceedings of the American Control Conference, Pages 2406-2411, May 2002,

Anchorage, Alaska,

72) S. Gentry, S. Venkatesh and E. Feron, System Identification via Inverse Dynamic

Optimization, 5th

SIAM Conference on Control and its Applications, Dec. 2001, San Diego,

CA

73) N. Martins, S. Venkatesh and M. Dahleh, Controller Design and Implementation for Large-

scale systems: A block de-coupling approach, Proceedings of the American Control

Conference, Pages 4728-4733, June 2001, Arlington, VA

74) S. Gentry, S. Venkatesh and E. Feron, Dynamic Inverse Optimal Control, Proceedings of

the American Control Conference, Pages 4722-4727, June 2001, Arlington, VA.

75) N. Martins, S. Venkatesh and M. Dahleh, Block De-coupling of LTI Systems, Proceedings

of the IEEE Conference on Decision and Control, Pages 4162-4163, Dec. 2000, Sydney

76) S. Gentry, S. Venkatesh and E. Feron, Identifying Constrained Receding Horizon

Controllers, Allerton Conference on Communication, Control and Computing, Urbana, IL,

Oct. 2000

77) S. Venkatesh and M. Dahleh, Input Sequences with Uniformly Decaying Auto-Correlation

Properties, International Federation of Automatic Control Symposium on System

Identification (SYSID2000), Santa Barbara, CA, June 2000.

78) S. Venkatesh, D. Polak, S. Narayanan, Phased Array Design, Validation, and Measurement

of Jet Noise, AIAA Aeroacoustics Conference, Paper 2000-1934, June 2000, Hawaii

79) S. R. Venkatesh, System Identification and Control on Hardy-Sobolov Spaces, Proceedings

of the American Control Conference, Pages 948-952, June 1999, San Diego, California.

80) S. Venkatesh and Y. Cho, Identification and control of high-rise elevators, Proceedings of

the American Control Conference, Pages 3860-3864, June 1998, Philadelphia, Pennsylvania

81) S. Venkatesh, M. A. Dahleh, System Identification of Complex Systems: Problem

Formulation and Results, IEEE Conference on Decision and Control, Pages 2441-2446,

Dec. 1997, San Diego, California

82) S. R. Venkatesh, M. A. Dahleh, Multivariable Identification: A Controls Perspective,

Proceedings of the International Federation on Automatic Control, Pages 31-36, June 1996,

San Francisco, California

83) S. Venkatesh and M. A. Dahleh, Classical Identification in a Deterministic Setting!,

Proceedings of the 34th

IEEE Conference on Decision and Control, Pages 2921-2926, Dec.

1995, New Orleans, LA

84) S. Venkatesh, I. Chen, M. A. Dahleh, J. Tsitsiklis, Identification in the presence of bounded

low correlated noise, Proceedings of the American Control Conference, Page 3070, June

1995, Seattle, Washington

85) S. Venkatesh and M. A. Dahleh, Does Star Norm Capture L1 Norm ?, Proceedings of the

American Control Conference, Pages 944-945, June 1995, Seattle, Washington

86) S. Venkatesh and M. Dahleh, Examples of extreme cases in L1 and H∞ optimization,

Proceedings of the 32nd Conference on Decision and Control, Pages 2188-2193, Dec. 1993,

San Francisco, CA

H. Patents Awarded

87) S. Venkatesh, A. M. Finn, R. Reich, Automatic volume control for communication

system, US Patent No. 6674865

88) S. Venkatesh, A. M. Finn, Cabin-Communication System without Acoustic Echo

Cancellation, US Patent No. 6748086

89) S. R. Venkatesh and A. M. Finn, Adaptive Filter for Speech Intelligibility and

Enhancement in a Noisy Environment, US Patent Serial No. 7,117,145

90) M. Finn, S. R. Venkatesh, M. Davis, R. Reich, P. LeMay, Jim Dattolo, Mike Maass,

Steve Learman, User Interface for a Cabin-Communication System, US Patent Serial No.

7039197

91) S. R. Venkatesh and A. M. Finn, A Robust and Reliable Acoustic Echo and Noise

Cancellation System, US Patent Serial No. 09/692,531 (pending)

92) M. Finn, S. R. Venkatesh and R. Reich, Transient Processing for Cabin Communication

System, US Patent Serial No. 09/692,556 (pending)

93) S. Aeron, S. Bose, H. P. Valero, V. Saligrama, ``Automatic Dispersion Extraction of

Multiple Time Overlapped Acoustic Signals,” US Patent Filed, Dec 2009

DEVAVRAT SHAH Laboratory for Information and Decision Systems

Department of EECS Massachusetts Institute of Technology

Education:

Degree School Date

BTECH Indian Institute of Technology 1999 PhD Stanford University 2004

Principal Fields of Interest:

Networks; message-passing algorithms; statistical inference; network information theory

Awards Received Award Date

President of India Gold Medal 1999 IEEE Infocom best paper award 2004

INFORMS George B. Dantzig Best Dissertation Award 2005 NSF CAREER 2006 ACM Sigmetrics best paper award 2006 First ACM Sigmetrics Rising Star Award 2008 NIPS outstanding paper award (supervised) 2008 ACM Sigmetrics best student paper award (supervised) 2009 INFORMS Erlang Prize from Applied Probability Society 2010 INFORMS MSOM best student paper award (supervised) 2010

Professional Service:

Activity Beginning Ending

Technical Program Committee, IEEE DCOSS (distributed computation) March 2006 Nov. 2006 Technical Program Committee, IEEE Inter-Perf (inter-disciplinary workshop in performance evaluation communication systems) March 2006 July 2006 Technical Program Committee, IEEE Infocom March 2006 May 2009 Technical Program Committee, ACM Sigmetrics March 2007 present INFORMS Applied Probability Meeting, Session Organizer March 2007 August 2007 INFORMS Annual Meeting, Session Organizer May 2007 Nov. 2007 INFORMS Applied Probability Meeting, Session Organizer March 2009 June 2009 Associate Editor of INFORMS Operations Research Oct. 2009 present INFORMS Annual Meeting, Session Organizer May 2010 Nov. 2010 Chair, Technical Program Committee, ACM Mobihoc May 2010 May 2011 Technical Program Committee, INFORM Applied Probability Meeting June 2010 June 2011 Chair, Organizing Committee, Workshop at IPAM, UCLA Dec. 2010 Feb. 2012

Current Organization Membership: Organization Offices Held

ACM, IEEE, INFORMS, IMS and SIAM Member Patents and Patent Applications Pending:

“Network Coding for Transport Layer”, approved, February 2012. “Rateless wireless architecture”, filed February 2011. “Searching influential agents in a network”, filed June 2011. “New methodology for persionalized recommendation”, filed August 2011. “Method for finding mood-dependent top lists”, filed August 2011.

Publication

1. Books

1. Shah D., “Gossip algorithms”, Foundations and Trends in Networking, Vol. 3, No. 1, pages: 1-125, 2008.

2. Papers in Refereed Journals

1. Giaccone P., B. Prabhakar and D. Shah, “Randomized scheduling algorithms for high-aggregate bandwidth switches,” IEEE JSAC on high-performance electronic switches/ routers for high-speed internet, 21(4), pp. 546-559, 2003.

2. Giaccone P., E. Leonardi, B. Prabhakar and D. Shah, “Delay bounds for combined input-output queued switches with low speedup,” Performance Evaluation, Vol. 55, pp. 113-128, 2004.

3. Ganjali Y., A. Keshavarzian and D. Shah, “Cell switching versus packet switching in input queued switches,” IEEE/ACM Transactions on Networking, 13(4), pp. 782-789, 2005.

4. Boyd S., A. Ghosh, B. Prabhakar and D. Shah, “Randomized Gossip Algorithms,” In special joint issue of IEEE Transaction on Information Theory and IEEE/ACM Transaction on Networking, Vol. 52, No. 6, pp. 2508- 2530, 2006.

5. El Gamal A., J. Mammen, B. Prabhakar and D. Shah, “Throughput and Delay in wireless networks -- Part I: Fluid case,” In special joint issue of IEEE Transaction on Information Theory and IEEE/ACM Transaction on Networking, Vol. 52, No. 6, pp. 2568- 2592, 2006.

6. El Gamal A., J. Mammen, B. Prabhakar and D. Shah, “Throughput and Delay in wireless networks -- Part II: Constant-size packet,” IEEE Transaction on Information Theory, Vol. 52, No. 11, pp. 5111-5116, 2006.

7. Giaccone P., E. Leonardi and D. Shah, “Throughput Region in Finite-Buffered Networks,” IEEE Transactions on Parallel and Distributed Systems, Vol. 18, No. 2, pp. 251-263, February 2007.

8. Mammen J. and D. Shah, “Throughput and Delay in Random Wireless Networks with Restricted Mobility,” IEEE Transaction on Information Theory, Volume 53, No. 3, pp. 1108-1116, March 2007.

9. Bayati M., D. Shah, and M. Sharma, “Max-Product for Maximum Weight Matching: Convergence, Correctness, and LP Duality,” IEEE Transaction on Information Theory, Volume 54, No. 3, pp. 1241-1251, March 2008.

10. Madan R., D. Shah and O. Leveque, “Product multi-commodity flow in wireless networks,” IEEE Transaction on Information Theory, Volume 54, No. 4, pp. 1460-1476, April 2008.

11. Mosk-aoyama D. and D. Shah, “Fast gossip algorithm for computing separable function,” IEEE Transaction on Information Theory, Volume 54, No. 7, pp. 2997-3007, July 2008.

12. Niesen U., D. Shah, and G. Wornell, “Adaptive alternating minimization algorithm,” IEEE Transactions on Information Theory, Volume 55, No. 3, pp. 1423-1429, 2008.**

13. Waisanen H., D. Shah and M. Dahleh, “A Dynamic Pickup and Delivery Problem in Mobile Networks under Information Constraints,” IEEE Transactions on Automatic Control, Volume 53, No. 6, pp. 1419-1433, 2008.**

14. Shah D., and J. N. Tsitsiklis, “Bin packing with queues,” Journal of Applied Probability, Volume 45, pp. 922-939, 2008.

15. Niesen U., P. Gupta and D. Shah, “On capacity scaling in arbitrary wireless networks,” IEEE Transactions on Information Theory, Volume 55, No. 9, pp. 3959-3982, 2009.**

16. Sanghavi S., D. Shah and A. Willsky, “Message Passing for Maximum Weight Independent Set,” IEEE Transactions on Information Theory, Volume 55, No. 11, pp. 4822-4834, 2009.

17. Jung K., D. Shah, and J. Shin, “Distributed averaging via lifted Markov chains,” IEEE Transactions on Information Theory, Volume 56, No. 1, pp. 634-647, 2009.

18. Salez J. and D. Shah, “Belief propagation: optimal algorithm for random assignment problem,” Mathematics of Operations Research, Volume 34, No. 2, pp. 468-480, 2009.

19. Niesen U., P. Gupta and D. Shah, “The balanced unicast and multicast capacity regions of large wireless networks,” IEEE Transactions on Information Theory, Volume 56, No. 5, pp. 2249-2271, 2010.**

20. Doshi V., D. Shah, M. Medard and M. Effros, “Functional compression through graph coloring,” IEEE Transactions on Information Theory, Volume 56, No. 8, pp. 3901-3917, 2010.**

21. Ayaso, O., D. Shah and M. Dahleh, “Information theoretic bounds for distributed computation over networks of point-to-point channels,” IEEE Transactions on Information Theory, Volume 56, No. 12, pp. 6020-6039, 2010.**

22. Jiang L., D. Shah, J. Shin and J. Walrand, “Distributed random access algorithm: scheduling and congestion control,” IEEE Transactions on Information Theory, Volume 56, No. 12, pp. 6182-6207, 2010.

23. Mosk-Aoyama D., T. Roughgarden and D. Shah, “Fully distributed algorithms for convex optimization problems,” SIAM Journal on Optimization, Volume 20, No. 6, pp. 3260-3279, 2010.

24. Eryilmaz, A., A. Ozdaglar, D.Shah and E. Modiano, “Distributed Cross-Layer Algorithms for the Optimal Control of Multihop Wireless Networks,” IEEE/ACM Transactions on Networking, Volume 18, No.2, pp.638-651, 2010.

25. Chandrasekaran V., M. Chertkov, D. Gamarnik, D. Shah and J. Shin, “Counting independent sets using Bethe approximation,” Accepted to appear in SIAM Journal on Discrete Mathematics, pages 30, 2011.

26. Jagabathula S. and D. Shah, “Fair scheduling in networks through packet election,” IEEE Transactions on Information Theory, Volume 57, No. 3, pp.1368-1381, 2011.**

27. Rajagopalan S., and D. Shah, “Distributed averaging in dynamic networks,” IEEE Journal of Selected Topics in Signal Processing, Volume 5, No. 4, pp. 845-854, 2011.**

28. Sunderarajan J., D. Shah, M. Medard, S. Jakubczak, M. Mitzenmacher, J. Barros, “Network coding meets TCP: Theory and application,” Proceedings of IEEE, Volume 99, No. 3, pp. 490-512, 2011.

29. Drego N., A. Chandrakasen, D. Boning and D. Shah, “Reduction of variation-induced energy overhead in multi-core processors,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Volume 30, No. 6, pp. 891-904, June 2011.

30. Shah D., and Zaman T., “Rumors in a network: who’s the culprit?,” IEEE Transactions on Information Theory, Volume 57, No. 8, pp. 5163-5181, 2011.**

31. Jagabathula S. and D. Shah, “Inferring rankings under constrained sensing,” Accepted to appear in IEEE Transactions on Information Theory, pages 18, 2011.**

32. Shah D., and D. Wischik, “Switched networks with maximum weight policies: fluid approximation and multiplicative state space collapse,” Accepted to appear in The Annals of Applied Probability, pages 60, 2011.

33. Shah D., D. N. C. Tse and J. N. Tsitsiklis, “Hardness of low delay scheduling,” Accepted to appear in IEEE Transactions on Information Theory, pages 9, 2011.

34. Shah D., and D. Wischik, “Congestion collapse in overloaded networks,” Accepted to appear in Queuing Systems, pages 18, 2011.

35. Shah D., and J. Shin, “Randomized scheduling algorithm for queueing networks,” Accepted to appear in The Annals of Applied Probability, pages 47, 2011.**

36. Gamarnik D., D. Shah and Y. Wei, “Belief propagation for min-cost network flow: convergence & correctness,” Accepted to appear in Operations Research, 34 pages, 2011.

3. Proceedings of Refereed Conferences

1. Shah D., Laks V. S. Lakshmanan, K. Ramamritham and S. Sudarshan, “Interestingness and Pruning of Mined Patterns,” in Proceedings of ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 7 pages, 1999.

2. Shah D. and P. Gupta, “Fast Updating Algorithms for TCAMs,” in Proceedings of Hot Interconnects IX, Stanford, CA, pp. 36-47, 2000.

3. Shenoy P., J. R. Haritsa, S. Sudarshan, G. Bhalotia, M. Bawa and D. Shah, “Turbo-charging Vertical Mining of Large Databases,” in Proceedings of ACM SIGMOD, pp. 22-33, 2000.

4. Giaccone P., B. Prabhakar and D. Shah, “An efficient randomized algorithm for input-queued switch scheduling,” in Proceedings of Hot Interconnects IX, Stanford, CA, 6 pages, 2001.

5. Giaccone P., B. Prabhakar and D. Shah, “An implementable parallel scheduler for input-queued switches,” in Proceedings of Hot Interconnects IX, Stanford, 6 pages, 2001.

6. Shah D., “Stable algorithms for input-queued switches,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2001.

7. Shah D., S. Iyer, B. Prabhakar and N. McKeown, “Maintaining Statistics Counters in Router Line Cards,” in Proceedings of Hot Interconnects IX, Stanford, CA, 6 pages, 2002.

8. Giaccone P., E. Leonardi, B. Prabhakar and D. Shah, “Delay performance of high-speed packet switches with low-speedup,” in Proceedings of IEEE Globecom, Taiwan, pp. 2629-2633, 2002.

9. Mitzenmacher M., B. Prabhakar and D. Shah, “Balls and Bins with Memory,” in Proceedings of the 43rd Annual IEEE Symposium on Foundations of Computer Science, Vancouver, pp. 799-808, 2002.

10. Giaccone P., B. Prabhakar and D. Shah, “Towards simple high-performance schedulers for high-aggregate switches,” in Proceedings of IEEE INFOCOM, New York, pp., 1160-1169, 2002.

11. Shah D. and M. Kopikare, “Delay bounds for approximate maximum weight matching algorithms for input-queued switches,” in Proceedings of IEEE INFOCOM, New York, pp. 1024-1031, 2002.

12. Shah D., “Maximal matching is good enough,” in Proceedings of IEEE Globecom, San Francisco, CA, pp. 3009-3013, 2003.

13. Aggarwal G., R. Motwani, D. Shah and A. Zhu, “Switch scheduling via edge coloring,” in Proceedings of IEEE FOCS, Boston, MA, 10 pages, 2003.

14. Ganjali Y., A. Keshavarzian and D. Shah, “Input queued switches: cell switching v/s packet switching,” in Proceedings of IEEE INFOCOM, San Francisco, CA, pp. 1651-1658, 2003.

15. El Gamal A., J. Mammen, B. Prabhakar and D. Shah, “Throughput-Delay tradeoff in wireless network,” in Proceedings of IEEE INFOCOM, Hong Kong, 10 pages, 2004. (Best paper award)

16. Kumar N., R. Pan, and D. Shah, “Fair scheduling in input-queued switches under inadmissible traffic,” in Proceedings of IEEE Globecom, Dallas, TX, pp. 1713-1717, 2004.

17. Boyd S., A. Ghosh, B. Prabhakar and D. Shah, “Mixing Times for Random Walks on Geometric Random Graphs,” in Proceedings of workshop on Analytic Algorithms and Combinatorics (ANALCO), Vancouver, pp. 240-249, 2005.

18. El Gamal A., J. Mammen, B. Prabhakar and D. Shah, “Throughput-delay scaling in wireless network with constant-size packets,” in Proceedings of IEEE ISIT, Australia, 5 pages, 2005.

19. Bayati M., D. Shah, and M. Sharma, “Maximum weight matching via max-product belief propagation,” in Proceedings of IEEE ISIT, Australia, pp. 1763-1767, 2005.

20. Giaccone P., E. Leonardi, and D. Shah, “On the maximal throughput of networks with finite buffers and its application to buffered crossbars,” in Proceedings of IEEE INFOCOM, Miami, FL, pp. 971- 980, 2005.

21. Boyd S., A. Ghosh, B. Prabhakar and D. Shah, “Gossip algorithm: design, analysis and application,” in Proceedings of IEEE INFOCOM, Miami, FL, pp. 1653- 1664, 2005.

22. Waisanen H., D. Shah, and M. Dahleh, “Minimal Delay in Controlled Mobile Relay Networks,” in Proceedings of IEEE Conference on Decision and Control, San Diego, CA, pp. 1918-1922, 2006.**

23. Shah D. and D. Wischik, “Optimal Scheduling Algorithms for Input-Queued Switches,” in Proceedings of IEEE INFOCOM, Spain, pp. 1-11, 2006.

24. Mosk-Aoyama D. and D. Shah, “Computing Separable Functions via Gossip,” in Proceedings of IEEE PODC, Denver, CO, pp. 113-122, 2006.

25. Modiano E., D. Shah and G. Zussman, “Maximizing throughput in wireless networks via Gossip,” in Proceedings of ACM SIGMETRIC/Performance, Nice, France, pp. 27 - 38, 2006. (Best paper award)

26. Leveque O., R. Madan and D. Shah, “Capacity Scaling in Wireless Networks with Gaussian Channels,” in Proceedings of IEEE ISIT, Seattle, WA, 5 pages, 2006.

27. Mosk-Aoyama D. and D. Shah, “Information Dissemination via Network Coding,” in Proceedings of IEEE ISIT, Seattle, WA, pp. 1748-1752, 2006.

28. Bayati M., D. Shah and M. Sharma, “A Simpler Max-Product Maximum Weight Matching Algorithm and The Auction Algorithm,” in Proceedings of IEEE ISIT, Seattle, WA, pp. 557-561, 2006.

29. Waisanen H., D. Shah and M. Dahleh, “Optimal Delay in Networks with Controlled Mobility,” in Proceedings of Mathematical Theory of Networks and Systems, Japan, 6 pages, 2006.**

30. Niesen U., U. Erez, D. Shah and G. Wornell, “Rate-less Codes for Multi-Access Channels,” in Proceedings of IEEE Globecom, San Francisco, CA, 8 pages, 2006.**

31. Niesen U., D. Shah and G. Wornell, “Source Coding with Mismatched Distortion Measures,” in Proceedings of Allerton Conference on Computation, Communication and Control, Urbana, IL, 8 pages, 2007.**

32. Ayaso O., D. Shah and M. Dahleh, “Lower Bounds on Information Rates for Distributed Computation via Noisy Channels,” in Proceedings of Allerton Conference on Computation, Communication and Control, Urbana, IL, pages: 8, 2007.**

33. Doshi V., D. Shah, and M. Medard, “Source coding with distortion through graph coloring,” in Proceedings of IEEE ISIT, France, pp. 1501-1505, June 2007.**

34. Jung K. and D. Shah, “Low delay scheduling in wireless networks,” in Proceedings of IEEE ISIT, France, pp. 1396-1400, 2007.**

35. Niesen U., D. Shah and G. Wornell, “Adaptive Alternative Minimization Algorithm,’’ in Proceedings of IEEE ISIT, France, 5 pages, 2007.**

36. Bayati M., B. Prabhakar, D. Shah and M. Sharma, “Iterative Scheduling Algorithms,” in Proceedings of IEEE INFOCOM, pp. 445-453, 2007.

37. Shah D. and S. Shakkottai, “Oblivious Routing with Mobile Fusion Centers over a Sensor Network,” in Proceedings of IEEE INFOCOM, pp. 1541-1549, 2007.

38. Sunderarajan J., M. Medard, M. Kim, A. Eryilmaz, D. Shah and R. Koetter, “Network coding in a multi-cast switch,” in Proceedings of IEEE INFOCOM, pp. 1145-1153, 2007.**

39. Doshi V., D. Shah, M. Medard and S. Jaggi, “Distributed functional compression through graph coloring,” in Proceedings of Data Compression Conference, pp. 93-102, France, 2007.**

40. Montanari A. and D. Shah, “Counting Good Truth Assignment in Random k-SAT,” in Proceedings of ACM-SIAM SODA, New Orleans, LA, pp. 1255 - 1264, 2007.

41. Mosk-aoyama D., T. Roughgarden and D. Shah, “Fully Distributed Algorithms for Convex Optimization Problems,” in Proceedings of International symposium on distributed computing (Lecture Notes in Computer Science), Volume 4731, pp. 492-499, September 2007.

42. Jung K. and D. Shah, “Local approximate inference algorithms for minor excluded graphs,” in Advances in Neural Information Processing Systems, 8 pages, December 2007.**

43. Sanghavi S., D. Shah and A. Willsky, “Max-product for maximum weight independent set,” Advances in Neural Information Processing Systems, 8 pages, December 2007.

44. Waisanen H., D. Shah and M. Dahleh, “Lower Bounds for Multi-Stage Vehicle Routing,” in Proceedings of IEEE Conference on Decision and Control, New Orleans, LA, pp. 4570-4575, December 2007.**

45. Ayaso O., D. Shah and M. Dahleh, “Counting bits for distributed computation,” in Proceedings of IEEE ISIT, 5 pages, 2008.**

46. Niesen U., P. Gupta and D. Shah, “Hierarchical co-operation for arbitrary wireless networks,” in Proceedings of IEEE ISIT, 5 pages, 2008.**

47. Sundararajan J., D. Shah and M. Medard, “ARQ for network coding,” in Proceedings of IEEE ISIT, 5 pages 2008.**

48. Jagabathula S. and D. Shah, ``Optimal delay scheduling in networks with arbitrary constraints,” in Proceedings of ACM SIGMETRIC/Performance, 12 pages, 2008.**

49. Jung K., Y. Lu, D. Shah, M. Sharma and M. Squillante, “Revisiting stochastic loss networks: structures and algorithms,” In Proceedings of ACM SIGMETRIC/Performance, 12 pages, 2008.**

50. Jagabathula S., V. Doshi and D. Shah, “Fair scheduling through packet election,” in Proceedings of IEEE INFOCOM, 9 pages, 2008.**

51. Dolecek L., M. Qazi, A. Chandrakasen and D. Shah, “Breaking the Simulation Barrier: SRAM Evaluation Through Norm Minimization,” in Proceedings of IEEE/ACM ICCAD, pp. 322-329, November 2008.

52. Gummadi R., K. Jung, D. Shah and R. Sreenivas, “Feasible rate allocation in wireless networks,’’ in Proceedings of IEEE INFOCOM, 9 pages, 2008.**

53. Niesen U., P. Gupta and D. Shah, “The capacity region of large wireless networks,” in Proceedings of Allerton Conference on Computation, Communication and Control, Urbana, IL, 8 pages, 2008.

54. Jagabathula S. and D. Shah, “Inferring ranking under constrained sensing,’’ Advances in Neural Information Processing Systems, 8 pages, 2008.** (Best student paper award)

55. Sundararajan J., D. Shah, M. Medard, M. Mitzenmacher and J. Barros, “Network coding meets TCP,” in Proceedings of IEEE INFOCOM, pp. 280-288, 2009.

56. Dolecek L. and D. Shah, “Influence in a large society: Interplay between information dynamics and network structure,” in Proceedings of IEEE ISIT, pp. 1574-1578, 2009.

57. Rajagopalan S., D. Shah and J. Shin, “Network adiabatic theorem: an efficient randomized protocol for contention resolution,” in Proceedings of ACM SIGMETRICS/Performance, pp. 133-144, June 2009.** (Best student paper award)

58. Shah D. and T. Zaman, “Rumor in the network: Who’s the Culprit?,” in Proceedings of NIPS Workshop, pages 6, December 2009.**

59. Jagabathula S. and D. Shah, “Conditions for recoverability of rankings from partial information,” in Proceedings of NIPS Workshop, pages 6, December 2009.**

60. Jung K., P. Kohli and D. Shah, “Local rules for global MAP: when do they work?,” in Advances in Neural Information Processing Systems, pp. 871-879, December 2009.**

61. Farias V., S. Jagabathula and D. Shah, “A data driven approach to modeling choice,” in Advances in Neural Information Processing Systems, pp. 504-512, December 2009.**

62. Gamarnik D., D. Shah and Y. Wei, “Belief propagation for min-cost network flow: convergence & correctness,” in Proceedings of ACM/SIAM SODA, January 2010.

63. Niesen, U., P. Gupta and D. Shah, “Balanced Unicast and Multicast Capacity Regions of Large Wireless Networks,” in IEEE INFOCOM, May 2010.

64. Qazi M., M. Titekar, L. Dolecek, D. Shah and A. Chandrakasen, “Loop flattening and spherical sampling: highly efficient model reduction technique for SRAM yield analysis,” in Proceedings of DATE, pp. 801-806, March 2010.

65. Shah D., J. N. Tsitsiklis and Y. Zhong, “Qualitative properties of alpha weighted scheduling policies,” in Proceedings of ACM SIGMETRICS, pp. 239-250, 2010.**

66. Shah D. and J. Shin, “Dynamics in congestion games,” in Proceedings of ACM SIGMETRICS, pp.71-82, 107-118, 2010.**

67. Moallemi C. and D. Shah, “On the flow level dynamics of packet-switched network,” in Proceedings of ACM SIGMETRICS, pp. 83-94, 2010.

68. Chandar V., D. Shah and G. Wornell, “A simple message-passing algorithm for compressed sensing,” in Proceedings of IEEE ISIT, pp. 1968-1972, 2010.

69. Shah D. and T. Zaman, “Detecting Sources of Computer Viruses in Networks: Theory and Experiment,” in Proceedings of ACM SIGMETRICS, pp. 203-214, 2010.**

70. Shah D. and T. Zaman, “Community detection in networks: the leader-follower algorithm,” in Proceedings of NIPS Workshop, pages 6, December 2010.**

71. Bodas S. and D. Shah, “Fast averaging,” in Proceedings of IEEE ISIT, pages 6, July 2011.

72. Shah D., J. Shin and P. Tetali, “Efficient medium access using queues,” in Proceedings of IEEE FOCS, pages 9, October 2011.

73. Bodas S., D. Shah and D. Wischik, “Interference is not noise,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2011.

74. Karger D., S. Oh and D. Shah, “Budget optimal task allocation for crowd-sourcing,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2011.

75. Varshney L., and D. Shah, “Information limits of neural circuits,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2011.

76. Ammar A., and D. Shah, “Compare, don’t score,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2011.

77. Karger D., S. Oh and D. Shah, “Iterative crowd-sourcing,” Advances in Neural Information Processing System (NIPS), 2011.

4. Other Major Publications

1. Giaccone P., B. Prabhakar and D. Shah, “Efficient randomized algorithms for input-queued switch scheduling,” IEEE Micro, 22(1), pp. 10-18, 2002.

2. Giaccone P., B. Prabhakar and D. Shah, “An implementable parallel scheduler for input-queued switches,” IEEE Micro, 22(1), pp. 19-25, 2002.

3. El Gamal A., J. Mammen, B. Prabhakar and D. Shah, “Throughput delay trade-off wireless networks: constant packet-size,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2004.

4. Waisanen H., D. Shah and M. Dahleh, “Control reduces delay in mobile wireless networks,” In proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2005.

5. Madan R. and D. Shah, “Capacity scaling for arbitrary wireless networks,” in Proceedings of Allerton Conference on Communication, Control, and Computing, Urbana, IL, 8 pages, 2005. (Invited paper)

6. Jung K. and D. Shah, “On Computationally Bounded Adversarial Capacity,” in Proceedings of the Information Theory and Applications (ITA) workshop, University of California, San Diego, 5 pages, February 2006 (Invited paper).

7. Jung K. and D. Shah, “Fast Gossip via Non-reversible Random Walks,” in Proceedings of the Information Theory Workshop, Uruguay, pp. 67-71, March 2006 (Invited Paper).

8. Doshi V., D. Shah, M. Médard, and S. Jaggi, “Graph Coloring for Computing,” in Proceedings of the Asilomar Conference, Pacific Groove, CA, 5 pages, 2006 (Invited paper).

9. Chiang M., D. Shah and A. Tang, “Fair Bandwidth Allocation under General File-Size Distribution,” in Proceedings of Allerton Conference on Computation, Communication and Control, Urbana, IL, 8 pages, 2006 (Invited paper).

10. Niesen U., D. Shah and G. Wornell, “Sampling Distortion Measures,” Invited Paper at the Allerton Conference on Computation, Communication and Control, Urbana, IL, 8 pages, 2006.

11. Deb S., D. Shah and S. Shakkottai, “Fast matching algorithms for repetitive optimization: an application to switch scheduling,” in Proceedings of CISS, Princeton, NJ, pp. 1266-1271, 2006 (Invited paper).

12. Niesen U., P. Gupta and D. Shah, “On capacity scaling in arbitrary wireless networks,” In proceedings of the Information Theory and Applications (ITA) workshop, University of California, San Diego, CA, 5 pages, February 2007 (Invited paper).

13. Shah D. and D. Wischik, “On optimality of MWM-0+ scheduling algorithm,” In proceedings of the Information Theory and Applications (ITA) workshop, University of California, San Diego, 5 pages, February 2007 (Invited paper).

14. Jung K. and D. Shah, “Local approximate inference algorithms,” in Proceedings of Allerton Conference on Computation, Communication and Control, 8 pages, Urbana, IL, 2007 (Invited paper).

15. Jung K., D. Shah and J. Shin, “Fast gossip through lifted Markov chains,” In proceedings of Allerton Conference on Computation, Communication and Control, 8 pages, Urbana, IL, 2007 (Invited paper).

16. Sunderarajan J., D. Shah and M. Medard, “On queuing in coded networks - queue size follows degrees of freedom,” in Proceedings of Information Theory Workshop, Norway, pp. 1-6, July, 2007 (Invited paper).

17. Shah D. and D. Wischik, “On optimality of MWM-0+ scheduling algorithm,” In proceedings of the Information Theory and Applications (ITA) workshop, University of California, San Diego, CA, 5 pages, 2007. (Invited paper)

18. Shah D., “Network scheduling and message-passing,” Book chapter in Performance Modeling and Engineering, Editors Z. Liu and C. Xia, a collection of tutorials from ACM Sigmetrics/Performance, 2008.

19. Shah D. and D. Wischik, “Lower bound and optimality in switched networks,” in Proceedings of Allerton Conference on Computation, Communication and Control, Urbana, IL, 8 pages, 2008. (Invited paper)

20. Shah D., D. Tse and J. N. Tsitsiklis, “Hardness of low delay scheduling,” in Proceedings of Information Theory Workshop, Cairo, 2 pages, 2010. (Invited paper)

21. Farias V., S. Jagabathula and D. Shah, “A non-parametric approach to choice modeling,” Submitted, (under rounds of reviews since October 2009), 2011.

22. Shah D., J. Shin and P. Tetali, “Efficient medium access using queues,” Submitted, July 2011.

23. Farias V., S. Jagabathula and D. Shah, “Sparse Choice Models,” Preprint.

5. Invited Lectures May 2005, “Max-product algorithm for combinatorial problems,” Mathematics Center, Bell Labs, New Providence, NJ. June 2005, “Randomization and heavy traffic theory: approaches for switch scheduling algorithms,” Summer research school, d’information et de communication, Ecole Polytechnique de Federale Laussane, Laussane, Switzerland.

June 2005, “Randomized gossip algorithms,” Random GRAALS, workshop on random graphs and algorithms, Bertinoro, Italy. Also, July 2005 at Department of EE, Politechnico di Torino, Italy. July 2005, “Heavy traffic analysis of switch scheduling,” INFORMS applied probability meeting, Ottawa, Canada. October 2005, “Efficient algorithms for three problems in networks,” Information System Lab, EE Department, Stanford University. Also, Oct. 2005, DSP seminar, EECS Department, University of California, Berkeley, CA.

October 2005, “Message passing through self-avoiding walk,” Operations research seminar, MS&E Department, Stanford University, Palo Alto, CA.

January 2006, “Capacity-delay scaling in arbitrary wireless scaling,” ECE department seminar, Boston University, Boston, MA.

February 2006, “Gossip algorithms,” Center for wireless systems and applications seminar series, department of ECE, Purdue University, West Lafayette, IN.

June 2006, “Message-passing for network scheduling,” Seventh Stochastic networks conference, University of Illinois, Urbana, IL.

June 2006, “Approximate message-passing algorithms for independent set,” SIAM conference on discrete mathematics, Victoria, Canada.

October 2006, “Message-passing algorithms,” Information science and technology seminar series, California Institute of Technology, Los Angeles, CA.

November 2006, “Message-passing algorithms for network scheduling,” College of computer and information science, Northeastern University, Boston, MA.

April 2007, “Message-passing algorithms for network scheduling,” ECE department seminar series, Carnegie Mellon University, Pittsburg. PA.

April 2007, “Message-passing algorithms for network scheduling,” Advanced network colloquium series, ECE department, University of Maryland, College Park, MD.

May 2007, “Max-product for maximum weight independent set,” Algorithm, Inference and Statistical Physics workshop organized by Los Alamos National Laboratory, Santa Fe, NM.

June 2007, “Algorithmically efficient networks,” workshop on mathematical modeling and analysis of computer networks, Ecole Normale Superior, Paris, France.

July 2007, “Algorithmic independence and duality,” Common concepts in statistical physics and computer science, STATPHYS, International Center for Theoretical Physics, Trieste, Italy.

July 2007, “Approximate stability in flow level model under arbitrary file-size distribution,” INFORMS Applied Probability Meeting, Eindhoven, Netherlands.

July 2007, “Fair scheduling through packet election,” INFORMS Applied Probability Meeting, Eindhoven, Netherlands.

August 2007, “Belief propagation and network scheduling,” Los Alamos National Laboratory, Los Alamos, NM.

August 2007, “Belief propagation for maximum weight independent set,” Mathematics center, IBM T. J. Watson Research Center, Yorktown, New York.

August 2007, “Network scheduling algorithms,” Short course, Advanced networking school, department of ECE, University of California, San Diego, CA.

October 2007, “Implementable network algorithms: randomization and message-passing,” Plenary speaker, workshop on stochastic networks, INTERPERF, France.

November 2007, “Optimal network scheduling algorithms,” INFORMS Annual Meeting, Seattle, WA.

November 2007, “Message-passing algorithms for network scheduling,” INFORMS Annual Meeting, Seattle, WA.

December 2007, “Gossip algorithms: design, optimization and applications,” Short course at Scuola Normale Superiore di Pisa, Pisa, Italy.

March 2008, “Reversible networks, distributed optimization, and network scheduling: what do they have in common?” CISS, Princeton University, Princeton, NJ.

March 2008, “What do I know about Belief Propagation?” Combinatorics seminar, Department of Mathematics, Georgia Institute of Technology, Atlanta, GA.

June 2008, “Understanding maximum weight scheduling,” Eight Stochastic Networks Conference, Paris, France.

June 2008, “Belief propagation for random instances,” Phase transitions, hard combinatorial problems and message passing algorithms, Banff International Research Station (BIRS), Banff, Canada. June 2008, “Scheduling in communication networks,” ACM Sigmetrics/Performance Tutorial, ACM Sigmetrics/Performance conference, Annapolis, MD. November 2008, “Aloha, that works,” DSP Seminars, University of California, Berkeley, CA. November 2008, “Aloha, that works,” ISL Seminars, Stanford University, Palo Alto, CA.

February 2009, “Inferring popular rankings under constrained sensing,” Information Theory and Applications, University of California, San Diego, CA.

March 2009, “Network algorithms: decentralization and efficiency,” GRASP Research Laboratory Seminars, University of Pennsylvania, Philadelphia, PA.

June 2009, “Aloha, that works,” School of Computer and Communication Sciences, EPFL, Laussane, Switzerland.

July 2009, “Lower bounds for switched networks,” INFORMS Applied Probability Conference, Cornell University, Ithaca, NY.

September 2009, “Network Algorithms Made Distributed,” Plenary Speaker at IFAC Workshop on Estimation and Control of Networked System (NecSys), Venice, Italy.

September 2009, “Inferring Rankings,” Physics of Algorithms, Santa Fe, New Mexico. October 2009, “Gossip Algorithms,” Tutorial at the Annual Retreat of Universities of Texas, Communications, Winedale, Texas. November 2009, “Belief Propagation and Combinatorial Optimization,” Workshop on Natural Algorithms, Intractability Center, Princeton University, Princeton, NJ. November 2009, “Network Algorithms Made Distributed,” Plenary Speaker at Network Optimization and Control (NETCOOP), EURANDOM, Eindhoven, Netherland. December 2009, “Rankings,” EE department colloquium, Princeton University, Princeton NJ. January 2010, “Hardness of low delay network scheduling,” Information theory workshop, Cairo, Egypt. February 2010, “Message passing networks,” Workshop on frontiers of Networks science, control and games, University of Texas at Austin, TX. March 2010, “Message passing networks,” Department Colloquium, Computer Science Department, New York University, New York, NY. March 2010, “Message passing networks,” Department Colloquium, Industrial Engineering and Operations Research, Columbia University, New York, NY. April 2010, “Medium Access using Queues,” Spatial Networks Model for Wireless Communication, Stochastic Processes in Communication Sciences Program at Newton Institute, Cambridge UK.

June 2010, “Capacity, Queues and Computation in Stochastic Networks,” Applied Probability Day 2010, Columbia University, New York, NY.

October 2010, “Three performance metrics in stochastic processing networks,” Mathematical Aspects of Stochastic Networks, Oberwolfach, Germany.

November 2010, “Overloaded queueing network,” Stochastic Networks, INFORMS Annual Meeting, Austin, Texas.

January 2011, “Rank aggregation and inference,” Recent trends in social networks, Tata Institute of Fundamental Research, Mumbai, India.

January 2011, “Rank aggregation and inference,” Department Colloquium, Computer Science and Automation Department, Indian Institute of Science, Bangalore, India.

February 2011, “Ranking, Medium Access and Multiplicative Weight Update,” Information Theory and Applications Workshop, University of California, San Diego, CA.

February 2011, “Information spreading for computation and inference,” Invited Speaker at Complex Networks Lab, Northeastern University, Boston, MA.

April 2011, “On complexity and correctness of Bethe Approximation,” Invited talk at the conference of Int’l Indian Statistical Association (IISA) (held once every two years), Raleigh, North Carolina.

April 2011, “Reversible networks and network algorithms,” Invited Fellows and Speaker at Stochastics Activity Month at EURANDOM, Eindhoven, Netherland.

June 2011, “Product-form and network algorithms,” Plenary talk at conference on Matrix Analytics Method (MAM) (held once every three years), Columbia University, New York City, New York. July 2011, “Rumor in a network: who’s the culprit?,” Invited talk at conference on Foundations of Computation Mathematics (FoCM)(held once every three years), Budapest, Hungary.

July 2011, “Information diffusion: computation, detection and search,” Invited talk at DoD tech-transfer meeting, Stanford University, Palo Alto, CA.

July 2011, “Medium access using queues,” Invited talk at Microsoft Research Theory Colloquium, Cambridge, USA.

August 2011, “Influential agents in social networks,” Invited talk at Lincoln Lab GraphEx Symposium, Endicott House, MA.

September 2011, “People’s choice,” Department Colloquium, ECE department, Syracuse University, Syracuse, NY.

January 2012, “Gossip algorithms,’’ Short course in the workshop on Network Science, Indian Institute of Science, Bangalore, India.

February 2012, “Spinal Codes,” International Zurich Seminar, Switzerland.

Aaron B. WagnerSchool of Electrical and Computer Engineering

331 Frank H.T. Rhodes HallCornell University

Ithaca, NY 14853-6701Email: wagner@cornell.edu

Tel: 607.255.1017 Fax: 607.255.9072

Education:

University of California, Berkeley

Ph.D., Electrical Engineering and Computer Sciences 2005

M.S., Electrical Engineering and Computer Sciences 2002

University of Michigan, Ann Arbor

B.S., Summa Cum Laude, Electrical Engineering 1999

Professional Experience:

Assistant Professor, School of ECE, Cornell University 2006 –

Visiting Assistant Professor, School of ECE, Cornell University 2005 – 2006

Postdoctoral Research Associate, Coordinated Science Lab,University of Illinois at Urbana-Champaign 2005 – 2006

Personal and Group Honors/Awards:

2011 Merrill Presidential Teacher

2010 Cornell ECE Ph.D. Thesis Research Award Finalist (Benjamin Kelly)

2010 IEEE Information Theory Society Student Paper Award [C30]

2009 Michael Tien ’72 College of Engineering Teaching Award

2009 IEEE Information Theory Society Paper Award Nominee [J5]

2007 NSF CAREER Award

2006 UC Berkeley EECS Dept. David J. Sakrison Memorial Prize

2005 UC Berkeley Bernard Friedman Memorial Prize in Applied Mathematics

Professional Activities and Service:

Technical Program Committee:

2010 and 2012 IEEE Intl. Symposium on Information Theory (ISIT)

2010 IEEE Information Theory Workshop (ITW), Cairo

1

2010 IEEE Information Theory Workshop (ITW), Dublin

2009 and 2010 IEEE Intl. Conference on Distributed Computing in Sensor Systems(DCOSS)

2006 IEEE Globecom Conference

Other Organizational Committees:

General co-chair, 2012 North American School of Information Theory

Organizing Committee, Banff International Research Station (BIRS) invited workshopon “Information theory and statistics for large alphabets,” 2011

Program and Applications Committee, 2011 North American School of Information The-ory

Reviewer for:

NSF: Computer and Communication Foundations (both CAREER and regular panels)

Air Force Office of Scientific Research

IEEE Transactions on Information Theory

IEEE Transactions on Networking

IEEE Transactions on Signal Processing

IEEE Transactions on Communications

IEEE Transactions on Sensor Networks

European Transactions on Telecommunications

EURASIP Journal on Advances in Signal Processing

IEEE International Symposium on Information Theory

IEEE Globecom Conference

External lectures: see list after publications

Miscellaneous:

IEEE Information Theory Society Awards Committee (2012-2013)

Invited panelist, IEEE Information Theory Society Student Committee meeting, “How togive a good talk,” 2010.

Session chair, 2004, 2008, 2009, 2010 IEEE International Symposium on InformationTheory (ISIT)

Session chair, 2005, 2009, 2010 Annual Allerton Conference

Membership:

IEEE

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Eta Kappa Nu

Cornell graduate fields: ECE and Applied Math

External Funding:

NSF Grant CCF-1117128 (2011-2014): “Algorithms and Information-Theoretic Limits forData-Limited Inference,” (PI, co-PI: Alon Orlitsky, UCSD). $500,000. My component:$240,000.

NSF Grant CCF-1065352 (2011-2015): “Toward a General Theory of Information Transfervia Timing,” (PI, co-PIs: Todd Coleman, UCSD and Negar Kiyavash, UIUC). $1,100,000. Mycomponent: $500,000.

Intel, Cisco, and Verizon (2011-2014): “Meeting the Video Traffic Demand of 2014: Oppor-tunities, Strategies, and Prototypes,” (PI: Salman Avestimehr, Co-PIs: Tsuhan Chen, SheilaHemami, Aaron Wagner). $850,000. My component: $225,250.

NSF Grant CCF-0830496 (2008-2011): “Information Theory for the Rare-Events Regime,”(PI, co-PI: Pramod Viswanath, UIUC). $600,000. My component: $375,000.

AFOSR Grant FA9550-08-1-0060 (2008-2011): “Distributed Information Processing for Bat-tlespace Awareness: Ergodic and Non-Ergodic Interplay,” (sole PI). $360,000.

NSF Grant CCF-0642925 (2007-2011): “CAREER: A New Look at the Fundamental Limits ofLossy Network Compression,” (sole PI). $400,000.

Teaching at Cornell:

ECE 3100: Introduction to Probability and Inference for Random Signals and Systems (alsoENGRD 3100)

Fall 2011: 63 students

Fall 2010: 79 students

Fall 2009: 101 students

ECE 4110: Random Signals in Communications and Signal Processing

Fall 2008: 30 students

Fall 2007: 20 students

Fall 2006: 38 students

ECE 5620: Fundamental Information Theory

Spring 2011: 12 students

Spring 2010: 11 students

Spring 2009: 17 students

Spring 2008: 10 students

Spring 2007: 32 students

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University Service:

ECE Policy Committee, 2011-2014

ECE IT Committee, 2011-2012

ECE “Data” Strategic Planning Group, 2010-2012

Co-chair, ECE Colloquium Committee, 2009-2011

ECE Staff Recognition Award Committee, 2009-2011

ECE Leadership Roundtable, 2009

ECE Graduate Committee, 2007-2009

ECE Phillips Hall Master Planning Committee, 2007

ECE Faculty Search Committee, 2006-2007

Students Advised:

Graduated Ph.D. Students

Benjamin Kelly, Ph.D., August 2011, “Information theory with large alphabets and sourcecoding error exponents” (now a researcher with the Knowledge Discovery Lab, GE GlobalResearch, Niskayuna, NY)

Current Ph.D. Students

Amine Laourine (Ph.D. expected Dec. 2011), “Secrecy in point-process and timing chan-nels”

Ebad Ahmed (Ph.D. expected May 2012), “Codes and protocols for peer-to-peer systems”

Md. Saifur Rahman (Ph.D. expected May 2012), “Distributed compression of vectorsources”

Yucel Altug (Ph.D. expected May 2013), “Moderate deviations and exact asymptotics ininformation theory”

Yuguang Gao (Ph.D. expected May 2016)

Sinem Unal (Ph.D. expected May 2016)

M.S. and M.Eng. Students

David Dunn (M.Eng. expected Dec. 2012), TBA

Yan Cao (M.Eng. expected May 2012), TBA

Liuyuan Chen (M.Eng. expected May 2012), TBA

Zhenzhen Ding (M.Eng. expected May 2012), TBA

CJ Halabi (M.Eng. expected Dec. 2011), “Coding for asynchronous multicast of video”

Bill Stubler, M.Eng., Dec. 2009, “Automatic detection of right whale calls”

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Xiyao Jiang, M.Eng., Aug. 2009, “Compress audio file using Karhunen-Loeve transform”

Anita Venkitarayan, M.Eng., Aug. 2009, “Erasure compression codes”

Narayanan Sitaraman Aier, M.Eng., Aug. 2009, “Distributed compression using latticecodes”

Thitidej (Nong) Tularak, M.Eng., May 2008, “Applications and simulations of a betterGood-Turing Estimator for sequence probabilities”

Zhixin Li, M.Eng., May 2007, “Introduction to SVM (support vector machines) and sim-ulation to estimators for the sequence probabilities”

Aggelos Vamvatsikos, M.S., Dec. 2006, “On the Wagner-Anantharam outer bound andachievable Gaussian source coding exponents”

Journal Publications in Press or in Print:

[J16] B. G. Kelly and A. B. Wagner, “Reliability in source coding with side information,” IEEE Trans.Inf. Theory, accepted.

[J15] Y. Altug and A. B. Wagner, “Source and channel simulation using arbitrary randomness,”IEEE Trans. Inf. Theory, to appear.

[J14] M. S. Rahman and A. B. Wagner, “Rate region of the Gaussian scalar-help-vector source-coding problem,” IEEE Trans. Inf. Theory, accepted.

[J13] B. G. Kelly and A. B. Wagner, “Improved source coding exponents via Witsenhausen’s rate,”IEEE Trans. Inf. Theory, accepted Mar. 2011.

[J12] E. Ahmed and A. B. Wagner, “Erasure multiple descriptions,” IEEE Trans. Inf. Theory, ac-cepted Feb. 2011.

[J11] A. B. Wagner, B. G. Kelly, and Y. Altug, “Distributed rate-distortion with common compo-nents,” IEEE Trans. Inf. Theory, vol. 57, no. 7, pp. 4035–4057, July 2011.

[J10] A. B. Wagner, P. Viswanath, and S. R. Kulkarni, “Probability estimation in the rare-eventsregime,” IEEE Trans. Inf. Theory, vol. 57, no. 6, pp. 3207–3229, June 2011.

[J9] E. Ahmed and A. B. Wagner, “Optimal delay-reconstruction tradeoffs in peer-to-peer net-works,” IEEE J. Select. Areas Commun., vol. 29, no. 5, pp. 1055–1063, May 2011.

[J8] A. B. Wagner, “On distributed compression of linear functions,” IEEE Trans. Inf. Theory,vol. 57, no. 1, pp. 79–94, Jan. 2011.

[J7] S. Tavildar, P. Viswanath, and A. B. Wagner, “The Gaussian many-help-one distributed sourcecoding problem,” IEEE Trans. Inf. Theory, vol. 56, no. 1, pp. 564–581, Jan. 2010.

[J6] R. W. Yeung, N. Cai, S.-W. Ho, and A. B. Wagner, “Reliable communication in the absence ofa common clock,” IEEE Trans. Inf. Theory, vol. 55, no. 2, pp. 700–712, Feb. 2009.

[J5] A. B. Wagner, S. Tavildar, and P. Viswanath, “Rate region of the quadratic Gaussian two-encoder source-coding problem,” IEEE Trans. Inf. Theory, vol. 54, no. 5, pp. 1938–1961, May2008.

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[J4] A. B. Wagner and V. Anantharam, “An improved outer bound for multiterminal source cod-ing,” IEEE Trans. Inf. Theory, vol. 54, no. 5, pp. 1919–1937, May 2008.

[J3] A. B. Wagner and V. Anantharam, “Zero-rate reliability of the exponential-server timing chan-nel,” IEEE Trans. Inf. Theory, vol. 51, no. 2, pp. 447–465, Feb. 2005.

[J2] A. B. Wagner and V. Anantharam, “Designing a contact process: The piecewise-homogeneousprocess on a finite set with applications,” Stochastic Process. Appl., vol. 115, no. 1, pp. 117–153, Jan. 2005.

[J1] S. Ruegsegger, A. Wagner, J. S. Freudenberg, and D. S. Grimard, “Feedforward control forreduced run-to-run variation in microelectronics manufacturing,” IEEE Trans. Semiconduct.Manufact., vol. 12, no. 4, pp. 493–502, 1999.

Journal Publications under Review:

[R6] Md. S. Laourine and A. B. Wagner, “Rate Region of the Vector Gaussian One-Helper Source-Coding Problem,” IEEE Trans. Inf. Theory, submitted Dec. 2011.

[R5] A. Laourine and A. B. Wagner, “The degraded Poisson wiretap channel,” IEEE Trans. Inf.Theory, under revision.

[R4] B. G. Kelly, A. B. Wagner, T. Tularak, and P. Viswanath, “Classification of homogeneous datawith large alphabets,” IEEE Trans. Inf. Theory, under revision.

[R3] P. Grover, A. B. Wagner, and A. Sahai, “Information embedding meets distributed control,”IEEE Trans. Inf. Theory, under revision.

[R2] M. S. Rahman and A. B. Wagner, “Optimality of binning for distributed hypothesis testing,”IEEE Trans. Inf. Theory, submitted Dec. 2010.

[R1] R. Soundararajan, A. B. Wagner, and S. Vishwanath, “Sum rate of the vacationing CEO prob-lem,” IEEE Trans. Inf. Theory, submitted Dec. 2010.

Journal Publications in Preparation (Working Papers):

[P7] E. Ahmed and A. B. Wagner, “Lossy source coding with Byzantine adversaries,” IEEE Trans.Inf. Theory, in preparation.

[P6] Y. Altug and A. B. Wagner, “Sphere-Packing Refinement, Part II: Asymmetric Channels,” IEEETrans. Inf. Theory, in preparation.

[P5] Y. Altug and A. B. Wagner, “Sphere-Packing Refinement, Part I: Symmetric Channels,” IEEETrans. Inf. Theory, in preparation.

[P4] A. Laourine and A. B. Wagner, “Compressing neighbors in a Gauss-Markov tree,” IEEE Trans.Inf. Theory, in preparation.

[P3] B. G. Kelly and A. B. Wagner, “Universal near-lossless compression of large-alphabet sources,”IEEE Trans. Inf. Theory, in preparation.

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[P2] Y. Altug and A. B. Wagner, “Moderate deviations in channel coding,” IEEE Trans. Inf. Theory,in preparation.

[P1] A. Laourine and A. B. Wagner, “Secrecy capacity of the exponential-server timing channel,”IEEE Trans. Inf. Theory, in preparation.

Conference Publications:

[C37] Y. Altug and A. B. Wagner, “Refinement of the Random Coding Bound,” in Proc. Intl. ZurichSeminar (IZS), 2012, to appear. (Invited Paper).

[C36] E. Ahmed and A. B. Wagner, “Lossy source coding with Byzantine adversaries,” in Proc. IEEEInf. Theory Workshop (ITW), 2011, to appear.

[C35] A. Laourine and A. B. Wagner, “Compressing neighbors in a Gauss-Markov tree,” in Proc.Ann. Allerton Conf. on Comm., Control, and Computing, 2011, to appear.

[C34] Y. Altug and A. B. Wagner, “Refinement of the sphere-packing bound for symmetric chan-nels,” in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2011, to appear.

[C33] M. S. Rahman and A. B. Wagner, “Rate region of the vector Gaussian one-helper source-coding problem,” in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2011, toappear. (Invited Paper).

[C32] M. S. Rahman and A. B. Wagner, “Optimality of binning for distributed hypothesis testing,”in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2010, pp. 828–835. (InvitedPaper).

[C31] A. Laourine and A. B. Wagner, “Secrecy capacity of the degraded Poisson wiretap channel,”in Proc. IEEE Int. Symp. Inf. Theory (ISIT), June 2010, pp. 2553–2557.

[C30] B. Kelly, T. Tularak, A. B. Wagner, and P. Viswanath, “Universal hypothesis testing in thelearning-limited regime,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), June 2010, pp. 1478–82.

[C29] R. Soundararajan, A. B. Wagner, and S. Vishwanath, “Sum rate of the vacationing CEOproblem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2010, pp. 26–30.

[C28] M. S. Rahman and A. B. Wagner, “Rate region of the Gaussian scalar-help-vector source-coding problem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2010, pp. 56–60.

[C27] Y. Altug and A. B. Wagner, “Moderate deviation analysis of channel coding: Discrete memo-ryless case,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), June 2010, pp. 265–269.

[C26] P. Grover, A. B. Wagner, and A. Sahai, “Information embedding meets distributed control,”in Proc. IEEE Inf. Theory Workshop (ITW), 2010, pp. 1–5.

[C25] A. B. Wagner, B. G. Kelly, and Y. Altug, “The lossy one-helper conjecture is false,” in Proc.Ann. Allerton Conf. on Comm., Control, and Computing, 2009, pp. 716–723. (Invited Paper).

[C24] Y. Altug and A. B. Wagner, “Source and channel simulation using arbitrary randomness,” inProc. Ann. Allerton Conf. on Comm., Control, and Computing, 2009, pp. 558–65.

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[C23] E. Ahmed and A. B. Wagner, “Binary erasure multiple descriptions: Worst-case distortion,”in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2009, pp. 55–59.

[C22] M. S. Rahman and A. B. Wagner, “Vector Gaussian hypothesis testing and lossy one-helperproblem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2009, pp. 968–972.

[C21] B. Kelly and A. B. Wagner, “Improved Slepian-Wolf exponents via Witsenhausen’s rate,” inProc. IEEE Int. Symp. Inf. Theory (ISIT), 2009, pp. 874–878.

[C20] E. Ahmed and A. B. Wagner, “Binary erasure multiple descriptions: Average-case distortion,”in Proc. IEEE Inf. Theory Workshop (ITW), 2009, pp. 166–170.

[C19] A. B. Wagner, “On distributed compression of linear functions,” in Proc. Ann. Allerton Conf.on Comm., Control, and Computing, 2008, pp. 1546–1553. (Invited Paper).

[C18] J. Chen and A. B. Wagner, “A semicontinuity theorem and its application to network sourcecoding,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2008, pp. 429–433.

[C17] B. Kelly, A. B. Wagner, and A. Vamvatsikos, “Error exponents and test channel optimizationfor the Gaussian Wyner-Ziv problem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2008, pp.414–418.

[C16] A. B. Wagner, “An outer bound for distributed compression of linear functions,” in Proc. Conf.Inf. Sci. and Sys. (CISS), 2008, pp. 435–440. (Invited Paper).

[C15] B. Kelly and A. B. Wagner, “Error exponents and test channel optimization for the Wyner-Zivproblem,” in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2007, pp. 510–517.(Invited Paper).

[C14] A. B. Wagner, P. Viswanath, and S. R. Kulkarni, “A better Good-Turing estimator for sequenceprobabilities,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), June 2007, pp. 2356–60.

[C13] S. Tavildar, P. Viswanath, and A. B. Wagner, “The Gaussian many-help-one distributed sourcecoding problem,” in Proc. IEEE Inf. Theory Workshop (ITW), 2006, pp. 596–600.

[C12] A. B. Wagner, S. Tavildar, and P. Viswanath, “Rate region of the quadratic Gaussian two-encoder source-coding problem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2006, pp. 1404–8.

[C11] A. B. Wagner, P. Viswanath, and S. R. Kulkarni, “Strong consistency of the Good-Turingestimator,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), July 2006, pp. 2526–30.

[C10] A. B. Wagner and V. Anantharam, “An improved outer bound for the multiterminal source-coding problem,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2005, pp. 1406–1410.

[C9] A. B. Wagner and V. Anantharam, “Information theory of covert timing channels,” in Aspects ofNetwork and Information Security, D: Information and Communications Security, E. Kranakis,E. Haroutunian, and E. Shahbazian, Eds., vol. 17. IOS Press, pp. 292–296.

[C8] A. B. Wagner and V. Anantharam, “Feedback, queueing, and the reliability of the ideal Poissonchannel above capacity,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT), 2004, p. 445.

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[C7] A. B. Wagner and V. Anantharam, “A pairwise error probability bound for the exponential-server timing channel,” in Proc. Int. Conf. Comm., vol. 5, 2003, pp. 3472–3476.

[C6] A. B. Wagner and V. Anantharam, “Wireless sensor network design via interacting particles,”in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2002. (Invited Paper).

[C5] A. B. Wagner and V. Anantharam, “On the zero-rate error exponent of the exponential-servertiming channel,” in Proc. Ann. Allerton Conf. on Comm., Control, and Computing, 2002.

[C4] A. B. Wagner and V. Anantharam, “Designing an interacting particle system: optimization ofthe piecewise-homogeneous contact process,” in Proc. Conf. Inf. Sci. and Sys. (CISS), 2002.

[C3] A. B. Wagner, S. M. Ruegsegger, J. S. Freudenberg, and D. S. Grimard, “Interprocess run-to-run feedforward control for wafer patterning,” in Proc. IEEE Intl. Conf. Control Appl., Aug.1999, pp. 789–795.

[C2] S. M. Ruegsegger, A. B. Wagner, J. S. Freudenberg, and D. S. Grimard, “Feedforward recipeselection control design software,” in Process, Equipment, and Materials Control in IntegratedCircuit Manufacturing IV, vol. 3507, Sept. 1998, pp. 69–80.

[C1] S. M. Ruegsegger, A. B. Wagner, J. S. Freudenberg, and D. S. Grimard, “Optimal feedfor-ward recipe adjustment for CD control in semiconductor patterning,” in Proc. InternationalConference on Characterization and Metrology for ULSI Technology, Mar. 1998.

External Lectures:

MIT, Sept. 2011

University of Illinois at Urbana-Champaign, Sept. 2011

Banff International Research Station (BIRS) invited workshop on “Algebraic Structure in Net-work Information Theory,” Aug. 2011

Tel-Aviv University, Jul. 2011

Technion-Israel Institute of Technology, Jul. 2011

University of California, Los Angeles, Jun. 2011

Stanford University, May 2011

Caltech, May 2011

University of Waterloo, Mar. 2011

University of Texas at Austin, Dec. 2010

Queen’s University, Nov. 2010

American Institute of Mathematics, Palo Alto, Sept. 2009

University of Texas at Austin, Apr. 2008

Syracuse University, Jan. 2008

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IBM T. J. Watson Research Labs, Jun. 2007

Stanford University, May 2007

UC Berkeley, Apr. 2007

University of Maryland, College Park, Feb. 2007

Yale University, Oct. 2006

Northwestern University, May 2006

University of Notre Dame, Apr. 2006

University of Illinois at Urbana-Champaign, Mar. 2006

Cornell University, Apr. 2005

MIT, Apr. 2005

University of Michigan, Ann Arbor, Apr. 2005

Boston University, Apr. 2005

University of Massachusetts, Amherst, Apr. 2005

Purdue University, Apr. 2005

University of Illinois at Urbana-Champaign, Apr. 2005

University of Illinois at Urbana-Champaign, Nov. 2004

Oakland University, Jul. 2004

UC Berkeley, Mar. 2004

UC Berkeley, Oct. 2002

UC Berkeley, Sept. 2000

4/1/12

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