Faculty Research Projects & Opportunities for Students

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Faculty Research Projects & Opportunities for Students Department of Computing Sciences September 16, 2013

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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 Presentation

Transcript of Faculty Research Projects & Opportunities for Students

Page 1: Faculty Research Projects & Opportunities for Students

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

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P oo lL is txN ode ID T imed

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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

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ToTIn P oo lL is txN od e ID T ime dIn

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Type

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m plmp l

p n

b atc hP oo lL is t(pn, B atS izeM a x_ E )

p n

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[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

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mpnls t (mpl,il)::mpnls t

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pn1lis t2ms (getM P L (mpnls t))

mpnls t

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[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

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A ccepte d[]

P L N ID L s txIntL is tL s tT ime d

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A ctive RP L N ID L s txIntL is tL s tT ime d

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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