department of computing sciences september 19, 2011
TRANSCRIPT
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An Introduction and Orientation to Faculty
Projects & InterestsDepartment of Computing Sciences
September 19, 2011
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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
Overview
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LIKES (Beck) Ensemble (Cassel) Distributed Expertise (Cassel, Way) Proximity Structures (Damian) SHAPE (Gehlot, Way) ViCS: The Sequel (Beck, Klassner) Robotics and Embedded Programming
(Peyton-Jones, Klassner) Databases for Many Majors: A Student-
Centered Approach (Goelman)
Examples of Funded Projects
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Grand Challenges of Computing
CSC 9025
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CSC 9025 - Replaces old CSC 9020 “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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Research Topics and Projects Sampler
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Research Topics (1) Programming languages and systems
control for Mindstorm robots.
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Research Topics (2) Contexts for optimum web search
strategies.
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Research Topics (3) Algorithm taxonomy: examples from
traditional games.
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Research Topics (4) Web site taxonomy and focused design
principles.
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Research Topics (5) Packing spheres into an ellipsoid: heuristic
search strategies.
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Research Topics (6) Code optimization: 20Kb vs. 20Mb program
space.
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Research Topics (6) Non-visual interfaces.
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Research Topics (7) Virtual reality in interdisciplinary projects.
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Research Topics (8) Web services: development, description,
deployment.
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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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Research Topics (11) Programming games and applications for
the Droid, iPhone and iPod Touch.
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Dr. Robert BeckProjects
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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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Program for Website Creation and Evaluation (PCWE)
• Funding for non-profit organization website renovation• Requested changes become data• Systematic evaluation against design principles• Automatic measurements
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Digital Humanities
A broad topic with many research threads:• Applications of location awareness—guided tours
• Models in social networks—pipelines, agents, transactions
• Systems thinking, computational thinking, X thinking• Text as data
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Dr. Lillian (Boots) Cassel
Projects
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Networks Information Retrieval Digital Libraries Image Management Distributed Expertise (w/ Dr. Way) Recent projects
◦ NSDL◦ Ontology◦ CPATH
Interests and Projects
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NSF- Fund and set direction- Outreach & communications to stakeholders
Projects Pathways- Provide resources, - Provide user services, services, research content stewardship
Core Integration - Integrate Projects - Partner with Pathways- Operations- Outreach & communications
Policy Committee NVC- Represent community - Strategic advice- Prioritize issues with CI to NSF and CI
Standing Committees- Content, Evaluation, Sustainability, Technology- Coordinate/engage community
FUND
BUILD
ADVISE
NSDL
Users- Students, Faculty- K-12- Undergraduate, Graduate- Researchers- Librarians- Anyone interested in STEM
Stakeholders
Resources, Services
Feedback, AskNSDL, Annotations
Standards, Services
Resources, Services
Information
Feedback, Funds
Contributors- Publishers- Universities- Libraries & Museums- Government- Corporations- Anyone interested in DLs
Sponsors/Funders- Government / Legislative- Corporations- Foundations- Anyone interested in NSDL
NSDL overview
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Ensemble The Pathway for Computing Education Broadening the role to encompass all that a
modern library is◦ Repository◦ Preservation center◦ Meeting place for project teams◦ Place to think, explore ideas, browse …
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The Components and the Issues Fedora repository Drupal front end Federated search Group work support Merged calendars Fine grained access More…
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The Computing Ontology A comprehensive representation of all
of the computing discipline(s) All relevant terms and the relationships
between and among them Applications
◦Curriculum development◦Curriculum description◦Research classification◦Browsing the field as a whole
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An example of a small section of the ontology for use in demonstrating the place of “hashing” in many areas of computing.
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Dr. Mirela DamianProjects
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Research TopicsMirela Damian
Research Area: Ad Hoc Wireless Networks
A
B
A
B
Topology
Control
Omnidirectional
Topology Control: reduce overall power consumption and interference while maintaining network connectivity.
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Research TopicsMirela Damian
Research Topic: Smart Antennas
A
B
A
B
Topology
Control
Directional
Energy proportional to the area covered.Benefits: reduced interference, reduced energy consumption.
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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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Electronic Voting Machines How is it that five software engineering
teams, working independently for five companies, ‘conspired’ to produce, in every case, electronic voting devices that are uniformly prone to malfunction and vulnerable to malicious attack?
Is this a technology that we really need? Or is it a solution to a non-existent problem?
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Outreach Activities
Since 1998, we have maintained a collaboration with students and teachers at Julia de Burgos Elementary School in North Philadelphia
Designed to redress some of the obstacles to learning new technologies affecting children from low income neighborhoods
This involvement began with Lance Rougeux, a 1998 graduate and alumnus of my first Ethical Issues class, who began his career as a 6th grade teacher at Julia de Burgos
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Lance Rougeux
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Dr. Vijay GehlotProjects
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SYSTEMS MODELING, SIMULATION, AND ANALYSIS
Vijay Gehlot
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Blood Samples Typing/Matching
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Blood Samples: Modeling/Computer Science View
Before:[([1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96],[])]
After:[([62],[]),([69],[]),([73],[]),([80],[]),([88],[]),([2],[]),([4],[]),([6],[]),([9],[]),([11],[]),([15],[]),([20],[]),([22],[]),([24],[]),([25],[]),([26],[]),([32],[]),([34],[]),([37],[]),([38],[]),([39],[]),([42],[]),([94],[(4,[11,12])]),([95],[(4,[11])]),([96],[(4,[11])]),([84],[(4,[11])]),([83],[(4,[11,12])]),([82],[(4,[12])]),([81],[(4,[12])]),([79],[(4,[11,12])]),([78],[(4,[11])]),([77],[(4,[11])]),([76],[(4,[11])]),([65],[(4,[10,12])]),([64],[(4,[12])]),([63],[(4,[12])]),([61],[(4,[11,12])]),([60],[(4,[12])]),([59],[(4,[11,12])]),([58],[(4,[12])]),([57],[(4,[11])]),([93],[(4,[11])]),([92],[(4,[11])]),([91],[(4,[11])]),([90],[(4,[11])]),([89],[(4,[11,12])]),([87],[(4,[11,12])]),([86],[(4,[11,12])]),([85],[(4,[12])]),([75],[(4,[12])]),([74],[(4,[12])]),([72],[(4,[10])]),([71],[(4,[12])]),([70],[(4,[11,12])]),([68],[(4,[11,12])]),([67],[(4,[11,12])]),([66],[(4,[12])]),([27],[(4,[11,12])]),([23],[(4,[12])]),([21],[(4,[12])]),([19],[(4,[11,12])]),([18],[(4,[12])]),([17],[(4,[11])]),([16],[(4,[11])]),([14],[(4,[12])]),([40],[(4,[11])]),([36],[(4,[11])]),([35],[(4,[11,12])]),([33],[(4,[12])]),([31],[(4,[12])]),([30],[(4,[11])]),([29],[(4,[11])]),([28],[(4,[11])]),([41],[(4,[12])]),([43],[(4,[12])]),([44],[(4,[11,12])]),([53],[(4,[12])]),([54],[(4,[12])]),([55],[(4,[11])]),([56],[(4,[12])]),([13],[(4,[12])]),([12],[(4,[11,12])]),([10],[(4,[12])]),([8],[(4,[11])]),([7],[(4,[11,12])]),([5],[(4,[11])]),([3],[(4,[12])]),([1],[(4,[11,12])]),([45],[(4,[11,12])]),([46],[(4,[11])]),([47],[(3,[9])]),([48],[(4,[11,12])]),([49],[(4,[11,12])]),([50],[(4,[11,12])]),([51],[]),([52],[(3,[9]),(4,[12])])]
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Model Components
runC o nfig s (["r1 c 1 ","r1 c 2 ","r1 c 3 ","r1 c 4 ","r2 c 1 ","r2 c 5 ","r2 c 6 ","r3 c 1 ","r3 c 7 ","r3 c 7 e ","r5 c 1 ","r5 c 2 ","r5 c 3 ","r5 c 4 ","r8 c 1 ","r8 c 8 ","r8 c 8 e "], 1 0 )
A p p ly E va l M L to o l to the e xp re s s io nb e lo w to run s im la tio n re p lic a tio ns w ithd iffe re nt ro uting a nd a trrib ute ta b le ss p e c ifie d a s lis t o f fi le ind e x va lue s .
A p p ly E va l M L to o l to the e xp re s s io nb e lo w to run a s e t o f s im la tio n re p lic a tio ns .C ha ng e the p a ra m e te rs to s p e c ify thenum b e r o f re p lic a tio ns to b e run a nd thenum b e r o f tim e s to re p e a t.
runN re p lic a tio ns M tim e s (2 0 ,1 0 )
A p p ly E va l M L to o l to the e xp re s s io nb e lo w to run s im la tio n re p lic a tio ns .C ha ng e the p a ra m e te r to s p e c ify thenum b e r o f re p lic a tio ns to b e run.
C P N 'R e p lic a tio ns .nre p lic a tio ns 1 0 0()
ss
(if s tP =S the n (if #1 (p lnT o P )<>[] the n 1 `p lnT o P e ls e e m p ty) e ls e e m p ty) ++ (if s tN =S the n (if #1 (p lnT o N )<>[] the n 1 `p lnT o N e ls e e m p ty) e ls e e m p ty)
[initP o o l()]
true
p
p 1
(p ,~1 )
p
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(if s tP =T the n (if #1 (p lnT o P )<>[] the n 1 `p lnT o P e ls e e m p ty) e ls e e m p ty) ++ (if s tN =T the n (if #1 (p lnT o N )<>[] the n 1 `p lnT o N e ls e e m p ty) e ls e e m p ty)
(p ,no d e F r)
Initia lize S a m p le S e tR o ute T a b le a ndN o d e A ttr T a b le
inp ut ();o utp ut (s );a c tio n(init_ ro uting (!rt_ file _ na m e ); s e tC urS a m p le S e t(g e nS a m p le S e t(9 6 )); g e tC urS a m p le S e t())
c he c k
[c he c k (s ,p )]
T
T
S
S
Inje c to r
R o ute r
inp ut (p , no d e F r);o utp ut (p lnT o P , p lnT o N , s tP , s tN );a c tio nro ute (p ,no d e F r);
S ta rt
1 `()
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S a m p le s
S a m p le S e t
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A va ila b le P o o lL is t
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1
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1 `[([1 ,2 ,3 ,4 ,5 ,6 ,7 ,8 ,9 ,1 0 ,1 1 ,1 2 ,1 3 ,1 4 ,1 5 ,1 6 ,1 7 ,1 8 ,1 9 ,2 0 ,2 1 ,2 2 ,2 3 ,2 4 ,2 5 ,2 6 ,2 7 ,2 8 ,2 9 ,3 0 ,3 1 ,3 2 ,3 3 ,3 4 ,3 5 ,3 6 ,3 7 ,3 8 ,3 9 ,4 0 ,4 1 ,4 2 ,4 3 ,4 4 ,4 5 ,4 6 ,4 7 ,4 8 ,4 9 ,5 0 ,5 1 ,5 2 ,5 3 ,5 4 ,5 5 ,5 6 ,5 7 ,5 8 ,5 9 ,6 0 ,6 1 ,6 2 ,6 3 ,6 4 ,6 5 ,6 6 ,6 7 ,6 8 ,6 9 ,7 0 ,7 1 ,7 2 ,7 3 ,7 4 ,7 5 ,7 6 ,7 7 ,7 8 ,7 9 ,8 0 ,8 1 ,8 2 ,8 3 ,8 4 ,8 5 ,8 6 ,8 7 ,8 8 ,8 9 ,9 0 ,9 1 ,9 2 ,9 3 ,9 4 ,9 5 ,9 6 ],[])]
11 `[]
F ill B a tch P
F ill B a tch P S
S ha red P
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S creen
S creen
S ha red E
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C o nd itio n P o o ls
C o nd itio nP o o ls S
C o nd itio nedP o o ls
P o o lL is txN o de ID T imed
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P L N ID L s tT imed
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C o nd itio nP o o ls S
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F ill B a tch P
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C onditionedP oo ls
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P oo lL is txN ode ID T im ed
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m plm pl
pn
ba tchP o o lL is t(pn, B a tS ize M a x_ E )
pn
pn1
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[pn1]
(if m p l=[] the n 1`() e ls e e m pty)@ +T im e r_ P
m pl1[]
[]
()
m p l1
m pl
m pl
m pl
pn::m p l
M o ve T oS ha re d P
L im it B a tch
C a nce lT im e r
P a s sT hro ugh
[L is t.le ngth(#1(pn1)) > B a tS ize M in_ E ]
F o rwa rdT im e do ut
B a tch
[m pl1<>[]]
P _ H IG H
F o rwa rdR e a dyB a tch
[m plL e ngth(m pl) >= B a tS ize M in_ E ]
A dd toB a tch
[m plL e ngth(m pl) + L is t.le ngth(#1(pn)) <= B a tS ize M a x_ E ]
P _ L O W
T o PO ut
P L N ID L s tT im e d
R e a dy T oB a tch
F us io n 3P o o lL is txN o de ID T im e d
T im e rF us io n 6
U N IT T im e d
H o ldF us io n 4
1`[]
P L N ID L s t
C o nd itio ne dP o o lsIn
P o o lL is txN o de ID T im e d
C o m bine dB a tche d
P o o lsF us io n 5
P L N ID L s tT im e dF us io n 5
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mpnls t
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i
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i
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[mpnls t<>[]]
U n B a tch D one R
input (pn1);output (pn2);ac tionproces s Type (pn1);
A ccept
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P _ H IG H
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@ +procT ime(40,20)
Ins tument F ree
1 (̀)
U N IT
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P L N ID L s txIntL is tL s tT imed
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Tools and Techniques
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Dr. Don GoelmanProjects
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Collaborative research with Prof. S. Dietrich, Arizona State University
Calendar: March, 2010 – February, 2012 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◦ Customization of the animations to majors
Driven by producers (Goelman/Dietrich) and consumers
XML-based Rollout of animations at workshop at CCSCE 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 Current Independent Studies
◦ Suseel Baldwa: Object-Relational Databases◦ Keerthi Chiluka: Distributed Database Systems◦ Satvik Mandava: Spring-MVC Framework◦ Krishna Nallamothu: Business Intelligence and
Data Warehousing◦ Ramya Numboori: NOSQL Data Stores
Other Interests and Projects
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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 Teaching Senior Projects Course
◦ http://www.csc.villanova.edu/~joyce/csc4790/f11/index.html Research Interests
◦ Software development/engineering◦ Web programming◦ Security◦ Computer Science Education
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◦ Investigating the status of the “good guys” vs “bad guys” situation in
computer security◦ Classifying “classes” based on the signatures of their methods ...◦ What “types” of learners learn X best when approach Y is used
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Dr. Frank KlassnerProjects
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Web-Based Software Systems Artificial Intelligence Signal Processing Robotics iPhone Applications Virtual Reality
Interests and Projects
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Dr. Anany LevitinProjects
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Anany Levitin
Algorithm 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
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 - Neural nets - 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. Thomas WayProjects
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Collaboration when expertise is distributed
Develop an interactive interface to the computing ontology to support this work
Host workshops to develop, collaborate, and disseminate this work
CPATH: Distributed Expertise
Faculty A
Faculty B
Expert
FacilitatorRemote expert is A
Remote expert is BCooperating experts
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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
Active Projects Distributed Expertise learning modules (CS
Ed) Internet Perception Analysis (AI)
Tremor Filtering Wii Pointer (Rehab Engr)
Green Computing (Green Comp.)
Nanocompilers & Nanocomputers (Nanotech)
SNITCH plagiarism analyzer (Sim & Tools)
Using Magic to Teach CS (CS Education)
Speech Recog. for note-taking (Rehab Engr)
Info. literacy using science satire (Info. Fluency)
ACT Lab (CS Education)
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Department of Computing Sciences 75
Back-burner Projects Underrepresentation of advantaged
women in Computer Science (CS Educ)
Talking picture frame (Entert. Tech)
Internet safety for parents (Info. Fluency)
Automatic image description (Rehab. Engr.)
Many other ideas
actlab.csc.villanova.edu
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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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Current Graduate Students – Villanova University
• Sukeerthi Shaga• Pavitra Kaveri Ramnath