faculty research projects & opportunities for students
DESCRIPTION
Faculty Research Projects & Opportunities for Students. Department of Computing Sciences September 16, 2013. Overview. Faculty are full-time and part-time members Interests range from theoretical foundations to practical applications - PowerPoint PPT PresentationTRANSCRIPT
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Faculty Research Projects & Opportunities for Students
Department of Computing Sciences September 16, 2013
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Faculty are full-time and part-time members Interests range from theoretical foundations
to practical applications Some research is sponsored – funding for
assistantships sometimes available Actively seeking external sponsorship and
partnership Interdisciplinary research promoted Student involvement is welcome and
encouraged!
Overview
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Grand Challenges of Computing
CSC 9025
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CSC 9025 – Often called “Independent Study” Mandatory for graduate students Conduct independent research under
guidance of a faculty advisor Encouraged to tackle topics in our discipline
that interest you AND your advisor Intended for completion in a single semester Extension to second semester possible Keep your eyes open for interesting topics!
What is the “Grand Challenges of Computing” course?
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Faculty Research Interests & Activities
Listen for opportunities to get involved in research
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Prof. Barbara Zimmerman
Projects
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• Software Project Management • Web Design• Database Systems• Inter-discipline applications of database
- Manchester Mummy project - Egypt- Alaska- South America
Current Interest
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DRA ABU el-NAGA – Thebes, Egypt
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St. Lawrence Island mummy
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THE CHURCH – 400AD
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Flow from Mummy to Slides
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MANCHESTER MUMMY DATABASEUPDATE
2013 Status
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DATABASE Database designed and implemented Programs to enter data completed
2012 Documentation begun Egyptian data entered into database
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REMAINING WORK Update database with Alaskan
mummies Update database with North and South
American mummies Transfer the database to Manchester
England Train the researchers in England to use
and update the database Coordinate with researchers using the
database
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RESEARCHERS USING OUR DATA 2013 Dr. Frank Ruhli, Head of Centre of
Evolutionary Medicine in Zurich Searched the Database and found specimens
for DNA studies Collected the Paraffin blocks from
Manchester and have found DNA evidence in our mummy tissues
Dr. Randall Thompson, Saint Luke’s Ancient Mummy Research Searched the database for diagnosis of
Atherosclerosis He will confirm using CT scans, tissue
samples and microscopic slides
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Dr. Robert BeckProjects
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Web Site Design Categories of web sites Design principles for a particular category Systematic evaluation against design
principles Automatic measurements
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Web Site Renovation Help nonprofit corporations, usually small
ones, upgrade their web sites Student works with “technical” person at
nonprofit Gather data for web site evaluation Challenges
◦ Communicating with the representatives◦ Developing with a variety of tools◦ Navigating the politics of the nonprofit
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Web Site Renovation (2) Current requests include:
◦ Nancy’s House, a one-person corporation that arranges respite for caregivers
◦ Brain Injury Association of Pennsylvania Video based educational material on the site Improved web site design Marketing strategies to drive users to the site
◦ College of Liberal Arts and Sciences Better navigation
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Social Network Analysis Mesh models of conflict resolution with
models of systems thinking for applications to◦ Nation building◦ Co-opetition in SOA system building
Examine and model social network strategies for promoting a cause◦ Flash mob◦ Philanthropy◦ “Pipeline” maintenance
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Computing in Context Computing and music through inquiry-based
learning (IBL)◦ More generally, IBL for computing◦ More specifically, strategies for using ChucK, the
language of the laptop orchestra
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Packing Problems Pack n equally sized spheres into the unit
sphere and calculate the radius of the small spheres as a function of n.◦ Alternatively, use an ellipsoid of revolution instead
of the unit sphere◦ Alternatively, solve the problems in two dimensions◦ Use a heuristic approach◦ Use a genetic algorithm
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Mathematical Structures on the Web Strategies for calculating, storing, and
viewing mathematical structures such as:◦ Finite rings◦ Small Lie algebras◦ Lie algebra representations
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Dr. Lillian (Boots) Cassel
Projects
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Dr. Lillian CasselResearch interests:
Digital LibrariesComputing OntologyInformation and the
WebInterdisciplinary
ComputingSome Current Projects
Computing PortalConnecting Computing Educators
A large digital library project for computing education, funded by NSF.
Computing Ontology A complete definition of the computing disciplines, in collaboration with ACM
www.computingportal.org
www.distributedexpertise.org/computingontology
Just startingEarlier and Broader Access to Machine Learning
With Dr. Way, Dr. Matuszek, and help from Dr. Papalaskari, funded by NSFWe will hire undergraduate help
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Dr. Mirela DamianProjects
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Research Topics (9) Constructing and maintaining wireless
network topologies.
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Research Topics (10) Folding and unfolding polyhedra.
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DNA Computing: How can DNA molecules solve computational problems?
Research Topics (11)
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Dr. James DulleaProjects
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Information Management Data Modeling Data Warehousing Data Mining Information Metrics
Interests and Projects
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Dr. William Fleischman
Projects
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Ethics Research topics related to ethical issues and
themes Electronic voting Outreach activities
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Dr. Vijay GehlotProjects
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Healthcare Applications
“…degradation of service can have serious consequences, especially when the medical device relies heavily on the wireless connection. Such situations can compromise the wireless transmission of high-priority medical device alarms, …” FDA, August 13, 2013
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CPN Model of WMDN
Alarms
Alarms
NursesNurses
NetworkNetwork
ResetQS1`[]
ALIST
AlarmQR1`[]
ALIST
ResetQR1`[]
ALIST
AlarmQS1`[]
ALIST
Network NursesAlarms
DataGenDataGen
Patient10Patient10
Patient9Patient9
Patient8Patient8
Patient7Patient7
Patient6Patient6
Patient5Patient5
Patient4Patient4
Patient3Patient3
Patient2Patient2
Patient1Patient1
AlarmQSOut
1`[]
ALIST
ResetQRIn
1`[]
ALISTIn
Out
Patient1Patient2Patient3Patient4Patient5Patient6Patient7Patient8Patient9Patient10DataGen
e @+ delD()e
numD`D(1)
a
a @+ delA(a)
q
a1::q
(a, t)
(a, getCurrTime())
a
SendWaveData
ConnectToAPConnectToAP
ResetAlarm
[a=a1]
GenAlarm
WaveDataFusion 2
E_T
AlarmAndData
ALARM_T
StatusNOkALARMxTIME
StatusOKFusion 1ALARM_T
ResetQRIn ALIST
AlarmQSOut ALISTOut
In
Fusion 1
Fusion 2
ConnectToAP
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Results and ImplicationsHeart Alarm Max Delay
0
5000
10000
15000
20000
25000
30000
35000
1 2 3 4 5 6 7 8
Number of Patients Monitored
Sim
ulat
ion
Tim
e U
nits
Non QoS Max DelayQoS Max Delay
Need for QoS requirement for medical applicationsSimilar situation in other application domains
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Bio-Technology Applications
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Model Components
F ill B a tch PF ill B a tc h P T
S hared PS hared P T
S hared ES hared E T
Typ eType
C o nditio n P oo lsC ond itionP oo ls T
C onditionedP o o ls
P oo lL is txN ode ID T imed
ToT ype
P L N ID L s tT ime d
ToEP L N ID L s tT im ed
To PP L N ID L s tT imed
T oR o ute rO ut
P oo lL is txN od e ID T ime d
ToTIn P oo lL is txN od e ID T ime dIn
O ut
C ond itionP oo ls T
Type
S hared E T
S hared P T
F ill B a tc h P T
m plmp l
p n
b atc hP oo lL is t(pn, B atS izeM a x_ E )
p n
pn1
()
[pn1]
(if m pl=[] then 1 (̀) e lse e mp ty)@ +T im er_ P
m pl1[]
[]
()m pl1
m pl
m pl
mp l
pn::m pl
M o ve T oS hared P
L imit B a tch
C anc e lT ime r
P a ssThro ugh
[L is t.leng th(#1(pn1)) > B a tS izeM in_ E ]
F orwardT ime dout
B atch
[m pl1<>[]]
P _ H IG H
F orwardR eadyB atch
[m plL ength(mp l) >= B atS izeM in_ E ]
A dd toB atch
[m plL ength(m pl) + L is t.length(#1 (pn)) <= B atS izeM ax_ E ]
P _ L O W
T o PO ut P L N ID L s tT im ed
R ead y T oB a tch
F us io n 3P oo lL is txN ode ID T imed
T im erF us io n 6
U N ITT im ed
Ho ldF us io n 4
1`[]
P L N ID L s t
C o nd itionedP oo lsIn
P oo lL is txN ode ID T imed
C o m binedB atched
P o o lsF us io n 5 P L N ID L s tT im edF us io n 5
In
F us io n 4F us io n 6
F us io n 3
O ut
1 1 [̀]
()
()i
L im it_ R
i-1
mpnls t@ +(procT ime (20,10)+150)
mpnls t (mpl,il)::mpnls t
[]mpnls t
pn1lis t2ms (getM P L (mpnls t))
mpnls t
pn2
(mpl,i l)
i
i
i
S ta rt R
[mpnls t<>[]]
U n B a tch D one R
input (pn1);output (pn2);actio nproce s s T ype (pn1);
A c ce pt
[L is t.length(mpnls t) < L imit_ R , i > 0]
P _ H IG H
S etup R
@ +pro cT ime(40 ,20)
Ins tument F re e
1 (̀)
U N IT
A ccepte d[]
P L N ID L s txIntL is tL s tT ime d
U nba tche dP oo ls
P o o lL is txN ode ID T imed
A ctive RP L N ID L s txIntL is tL s tT ime d
R R ea dy1 L̀ imit_ R
IN T
R S e tupIN TT ime d
C ombinedA mplico n
P o o ls to RIn
P L N ID L s txIntL is tT imed
ToR oute rO ut
P o o lL is txN ode ID T imedO ut
In
11 (̀)
11 [̀]@ 0
1 1`12
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ResultsNumber of samples = 16where Sample Set = [[(1,[]),(2,[]),(3,[]),(4,[12])],[(1,[]),(2,[]),(3,[9]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[])],[(1,[]),(2,[]),(3,[]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[])],[(1,[]),(2,[]),(3,[8]),(4,[])],[(1,[]),(2,[]),(3,[8]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[12])],[(1,[]),(2,[]),(3,[]),(4,[])],[(1,[]),(2,[]),(3,[9]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[12])],[(1,[]),(2,[]),(3,[]),(4,[12])],[(1,[]),(2,[]),(3,[]),(4,[11])],[(1,[]),(2,[]),(3,[]),(4,[12])],[(1,[]),(2,[]),(3,[]),(4,[12])]]Number of unique requests = 3where Request Set = [[(3,[8])],[(4,[12])],[(4,[12])],[(3,[8]),(4,[11,12])]]Number of matched samples = 8where Matched Samples = [([13],[(4,[12])]),([15],[(4,[12])]),([16],[(4,[12])]),([8],[(4,[12])]),([7],[(3,[8]),(4,[11])]),([6],[(3,[8])]),([1],[(4,[12])]),([12],[(4,[12])])]Number of pantry samples = 5where Pantry Samples = [([14],[(4,[11])]),([4],[(4,[11])]),([2],[(3,[9]),(4,[11])]),([10],[(3,[9]),(4,[11])]),([11],[(4,[11])])]Number of hold samples = 0where Hold Samples = []Number of discarded samples = 3where Discarded Samples = [([([9],[])],12),([([5],[]),([3],[])],12)]Number of unique assigned requests to samples = 2where Assigned Samples = [([(4,[12])],[([13],[(4,[12])]),([15],[(4,[12])]),([16],[(4,[12])])]),([(4,[12])],[([13],[(4,[12])]),([15],[(4,[12])]),([16],[(4,[12])])]),([(3,[8])],[([7],[(3,[8]),(4,[11])]),([6],[(3,[8])])]),([(4,[12])],[([8],[(4,[12])]),([1],[(4,[12])])]),([(4,[12])],[([8],[(4,[12])]),([1],[(4,[12])])]),([(4,[12])],[([12],[(4,[12])])]),([(4,[12])],[([12],[(4,[12])])])]Number of unique possibly unmatched requests = 2where Possibly Unmatched Requests = [([(3,[8])],[]),([(3,[8]),(4,[11,12])],[]),([(3,[8]),(4,[11,12])],[]),([(3,[8])],[]),([(3,[8]),(4,[11,12])],[])]Number of actual unmatched requests = 1where Actual Unmatched Requests = [[(3,[8]),(4,[11,12])]]
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Network Data Analysis and Modeling
Develop a set of tools and techniques for Network Performance Management and Service Assurance.
Create a generalized and extensible framework to accommodate future needs and expansion.
Build a unified dashboard that facilitates the understanding of the relationships between network resources, customer services and their respective performance indicators.
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Results
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Tools
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Dr. Don GoelmanProjects
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Databases for Many Majors: A Student-Centered Approach (Dietrich & Goelman) – through 2/2013
Expansion of the Project (? – keep your fingers crossed - !)
Update 5/2013 – not enough crossed fingers for funding, but interest continues in using and customizing animations to bring database appreciation to the world
Funded Projects (Sort of)
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Collaborative research with Prof. S. Dietrich, Arizona State University
Calendar: March, 2010 – February, 2013 Curriculum development for database
education to diverse majors Software development: two animations
◦ Advantages of (normalized) database technology over loser (I mean non-normalized) alternatives
◦ Introduction to querying
Funded Project (NSF DUE): Databases for Many Majors
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Technical issues◦ Programming in FLASH/FLEX◦ Porting to mobile devices◦ Customization of the animations to majors
Driven by producers (Goelman/Dietrich) and consumers
XML-based Rollout of animations - pretty mature Home page:
http://databasesmanymajors.faculty.asu.edu/
Databases for Many Majors (continued)
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Databases: conceptual modeling Databases: schema integration Databases: XML for non-majors Databases: NoSQL databases Data Science and Big Data
Other Interests and Projects
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◦Ramya Numboori: NOSQL Data Stores◦Hao Zhang: Database Querying in C#◦Takashi Binns: DB Systems for Geographical
Applications◦Shishir Kaushik: Online Marketing◦Sruthi Cherukuri: Utilities for Data
Warehouses◦Kartheek Chiluka: Rapid Application
Development Frameworks◦Sudha Palivela: NoSQL Databases,
Exemplified by MongoDB
Current and Recent Independent Studies
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Prof. Catherine Helwig
Projects
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Develop algorithm visualizations along with mini-tutorials for computer aided instruction in Data Structure and Algorithm classes.
Visualizations as a mini-tutorial with animations portraying different parts of the algorithm.
Sample of five animations of ADT’s (and looking for more) http://www.csc.villanova.edu/~helwig/index1.html
Graph algorithms at http://algoviz.org/fieldreports AlgoViz.org is supported by the National Science
Foundation under a grant
Algorithm Visualizations for Teaching and Learning
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J2 Micro Edition (J2ME) which is the version of the Java 2.1 platform that is designed for use with smaller devices such as PDA’s, mobile phones etc.
Since the size of small devices varies greatly, there are two profiles provided by the J2ME. The first,CLDC configuration , has a unique profile for Mobile Information Device Profile (MIDP toolkit).
Lab for Data Structures and Algorithms III developing a small app for the Blackberry.
Developing applications (games) on Mobile Phones and Small Devices
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Dr. Giorgi JaparidzeProjects
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Computational Theory Artificial Intelligence Logic Projects
◦ Computability Logic◦ Interactive Computation
Interests and Projects
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Dr. Daniel JoyceProjects
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Interests and Projects Department Web Team Lead Programming Team Coach Graduate Independent Study / Grand Challenges Coordinator
◦ http://csc.villanova.edu/academics/gradIS ◦ have contacts/ideas BEFORE your final semester starts
Research Interests◦ Software development/engineering◦ Web programming◦ Security◦ Computer Science Education
Research Project Ideas◦ Collecting and analyzing data related to the software development process◦ Report on the use of a new technology to create a system, perhaps
comparing it to use of a different technology Development Project Ideas
◦ Camp Registration Site◦ Use of Kinnects
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Dr. Frank KlassnerProjects
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AI, Robotics & Simulation
Virtual Reality◦ CAVEs◦ Immersive Video◦ Web-based Experiences
Mobile Apps
Interests and Projects
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Dr. Anany LevitinProjects
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Anany LevitinAlgorithm design techniques are general strategies for
algorithmic problem solving (e.g., divide-and-conquer, decrease-and-conquer, greedy, etc.)
paramount for designing algorithms for new problems provide a framework for classifying algorithms by design idea
Algorithmic puzzles are puzzles that requires design or analysis of an algorithm
illustrate algorithm design and analysis techniques as general problem solving tools (computational thinking)
some puzzles pose interesting and still unanswered questions entertainment technical job interviews
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Anany Levitin (cont.)
Algorithm design techniques projects thinking backward; design by cases how to solve it (G. Polya) vs.
how to solve it by an algorithm
Algorithmic puzzles projects a few specific puzzles (research and visualization) taxonomies of algorithmic puzzles
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63
Dr. Paula MatuszekProjects
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• Artificial Intelligence– knowledge-based systems– ontologies and the semantic web– knowledge capture and sharing– Machine learning
• Natural Language Processing/Text Mining– Computer understanding of natural (human) languages– Finding, extracting, summarizing, visualizing information from
unstructured text• Project
– Broader and Earlier Access to Machine Learning: NSF project to develop machine learning materials for non-computer science students.
Interests and Projects
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Prof. Najib NadiProjects
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Systems Programming Systems Administration
◦ Linux◦ Solaris◦ Mac OS X
Web Application Development Current projects:
◦ Systems setup for upcoming programming contest◦ IBM ThinkPad Linux configuration for cityteam ministries◦ Thin Client performance analysis◦ VU community Dropbox
Interests and Projects
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Dr. Mary-Angela Papalaskari
Projects
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Artificial Intelligence: - Augmented reality - Conversational agents - Reasoning with incomplete information - Machine learning - Computer Vision
Computer Science Education: - Teaching and learning computer science through service to the community - Computing for non-CS majors - Computer science through media computation - PACSE: Philadelphia Area Computer Science Educators
Interests and Projects
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Dr. James SolderitschProjects
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Cyber Security◦ Adaptive Network Defense◦ Data Protection and Privacy◦ Security within the Smart Grid◦ Ethical Hacking
Modeling and Simulation◦ Software Architectures as Executable Models◦ Security Modeling for Service Oriented
Architectures◦ Discrete Event Simulation
Interests and Projects
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Dr. Tom WayProjects
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Department of Computing Sciences 72
Active ProjectsParsing & Translation Nanocompilers & Nanocomputers (Nanotech) Sentiment Analysis & Tracking (AI) Tremor Filtering Wii Pointer (Rehab Engr) SNITCH plagiarism analyzer (Sim & Tools)
CS Education Distributed Expertise learning modules (CS Ed) Machine Learning modules (CS Ed) ACT Lab (CS Education)
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Department of Computing Sciences 73
ACT Lab Research GroupsApplied Computing Technology Laboratory
Director of Research
Dr. Tom Way
Com. Sci.
Education
High Perf.
Computing
Rehab. Engineeri
ng
Simulation & Tools
Information
Fluency
Databases
Other Groups..
.
Nanotech
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Department of Computing Sciences 74
Back-burner Projects Using Magic to Teach CS (CS Education) Green Computing (Green Comp.) Speech Recog. for note-taking (Rehab Engr) Info. literacy using science satire (Info. Fluency) Many other ideas
actlab.csc.villanova.edu
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Department of Computing Sciences 75
Student –Ready Projects Sentiment Analysis Sentiment Tracking Tremor Filtering Wii Pointer Plagiarism detection ACT Lab web site renovation Machine Learning education modules SMS question answerer