Degree:

• Ph.D., Arizona State University

Research Interests:

• Big Data Analytics
• Data Mining / Web Mining / Social Media Mining
• Social Network Analysis / Social Computing
• Large-Scale Information Networks
• Behavior Analysis

Current Research:

My research lies in the intersection of data mining, machine learning, social sciences, and theory. A common pattern in my research is to collect and analyze large scale data to glean actionable patterns. I often employ theories from social sciences, psychology, or anthropology, in addition to developing and using advanced mathematical, statistical, and machine learning machinery to prove the validity of such patterns.

Courses Taught:

• Data Mining
• Social Media Mining

Selected Publications:

Reza Zafarani and Huan Liu, Evaluation without Ground Truth in Social Media Research, Communications of the ACM, June 2015

Reza Zafarani, Mohammad Ali Abbasi, and Huan Liu, Social Media Mining: An Introduction, Cambridge University Press, 2014

Degree:

• Ph.D. in Computer Science, Syracuse University

Research Interests:

• Text Mining
• Social Networks
• Social Media Mining
• Information Retrieval
• Multi-Agent Systems

Current Research:

Current research involves the development of algorithms for measuring the emotional contents in tweets, contained not only in words, but also in emoticons, punctuation marks and hashtags; for event prediction based on social media data; and for extending sentiment analysis to multiple languages. Current research also involves continuing work on building autonomous agent-based information gathering system for decision support.

Courses Taught:

• Social Media Mining
• Software Specification and Design
• Software Implementation
• Principles of Software Engineering
• Web Systems

Recent Publications:

A. Panasyuk, E.S. Yu & K. Merhrotra, “Controversial Topic Discovery on Members of Congress with Twitter,” Complex Adaptive Systems, 2014.

M. Rahman, Qinyun Zhu, & E.S Yu, “TRECT: A Hashtag Recommendation System for Twitter,” 2nd International Workshop on Recommender Systems meet Big Data & Semantic Technologies, 2013.

E.S. Yu, “Social Media Marketing and Mining,” Social Media Strategies Seminar, Panama City, Panama, January 17, 2013.

E.S Yu, “From Knowledge Exchange to Knowledge Discovery,” Capstone Conference, Chicago, July 14, 2010.

Degrees:

• BA of Electrical & Computer Engineering, Central South University, China
• MS of Computer Science, Louisiana Tech University

Research Interests:

• Intelligent Systems (Data Mining & Network Analysis)
• Big Data Analytics
• System Security

Courses Taught:

• CSE 581 Introduction to Database Management System
• CIS 342 Introduction to System Programming
• CIS 223 Statistical Reasoning & Practice
• CPS 196 Introduction to Programming
• CPS 181 Introduction to Computing

Degree(s):

• Ph. D. (Illinois) 1976

Lab/Center Affiliation(s):

• CASE, Director

Research Interests:

• Distributed sensor networks and data fusion
• Detection and estimation theory
• Wireless communications
• Radar signal processing
• Physical layer security

Current Research:

There are two broad areas of current research. First deals with fusion of information from a variety of heterogeneous sources. Novel fusion and sensor management algorithms are being developed that enhance system performance as well as conserve system resources such as bandwidth and energy. Typical signal processing tasks are detection, localization, tracking and classification of objects and events. Distributed algorithms based on compressive sensing for these signal processing tasks are also being developed. The second area deals with cognitive networks where network throughput is to be maximized via active sensing and control under a number of system constraints. Security threats such as Byzantines and jamming are being investigated. Mitigation approaches are being developed using game theoretic concepts.

Courses Taught:

• Detection and estimation theory

Honors:

• IEEE Fellow 1997
• Third Millennium Medal IEEE 2000
• Judith A. Resnik Award IEEE 2012
• President International Society of Information Fusion 2001.
• Honorary Doctorate Degree, Drexel University, 2014
• Distinguished Alumni Award, ECE Department, Univ. of Illinois, 2015

Selected Publications:

Books

K. Varshney, Distributed Detection and Data Fusion, Springer-Verlag, 1997.

L. Foresti, C. S. Regazzoni, and P. K. Varshney (eds.), Multisensor Surveillance Systems: The Fusion Perspective, Kluwer Academic Press, 2003.

K. Varshney and M. K. Arora (eds.), Advanced Image Processing Techniques for Remotely Sensed Hyperspectral Data, Springer Verlag, 2004.

Journal Papers

Cao, N., Brahma, S. K., and Varshney, P. K., “Target Tracking via Crowdsourcing: A Mechanism Design Approach,” IEEE Trans. Signal Process., vol. 63, no. 6, pp. 1464-1476, Mar. 15, 2015.

Vempaty, A., He, H., Chen, B., and Varshney, P. K., ” On Quantizer Design for Distributed Bayesian Estimation in Sensor Networks,” IEEE Trans. Signal Process., vol. 62, no. 20, pp. 5359-5369, Oct. 15, 2014.

Chen, H., Varshney, L. R., and Varshney, P. K., ” Noise-Enhanced Information Systems,” Proc. IEEE, vol. 102, no. 10, pp. 1607-1621, Oct. 2014. (Invited)

Wimalajeewa, T., and Varshney, P. K., “OMP Based Joint Sparsity Pattern Recovery Under Communication Constraints,” IEEE Trans. Signal Process., vol. 62, no. 19, pp. 5059-5072, Oct. 1, 2014

Vempaty, A., Tong, L. and Varshney, P. K., “Distributed Inference with Byzantine Data: State-of-the-Art Review on Data Falsification Attacks,” IEEE Signal Process. Mag., vol.30, no.5, pp.65-75, Sept. 2013

Vempaty, A., Varshney, L. R., and Varshney, P. K., “Reliable Crowdsourcing for Multi-Class Labeling using Coding Theory,” IEEE J. Sel. Topics Signal Process., vol. 8, no. 4, pp. 667-679, Aug. 2014

Chen, H., Chen, B. and Varshney, P. K., “A New Framework for Distributed Detection with Conditionally Dependent Observations,” IEEE Trans. Signal Process., vol. 60, no. 3, pp. 1409-1419, Mar. 2012

S. Rawat, P. Anand, H. Chen and P. K. Varshney, “Collaborative Spectrum Sensing in the Presence of Byzantine Attacks in Cognitive Radio Networks,” IEEE Trans. on Signal Process., vol.59, no.2, pp.774-786, Feb. 2011

Masazade, R. Rajagopalan, P. K. Varshney, C. Mohan, G. K. Sendur, and M. Keskinoz, “A Multi-objective Optimization Approach to Obtain Decision Thresholds for Distributed Detection in Wireless Sensor Networks,” IEEE Transactions on Systems, Man, and Cybernetics – Part B, Vol. 40, No. 2, Apr. 2010

Masazade, R. Niu, P. K. Varshney, M. Keskinoz, ”Energy Aware Iterative Source Localization Schemes for Wireless Sensor Networks,” IEEE Trans. Signal Process., vol.58, no.9, pp.4824-4835, Sept. 2010.

Ozdemir, R. Niu, and P. K. Varshney, “Tracking in wireless sensor networks using particle filtering: Physical layer considerations,” IEEE Trans. Signal Process., vol.57, no. 5, pp. 1987-1999, May 2009

Niu, B. Chen, and P. K. Varshney, “Fusion of decisions transmitted over Rayleigh fading channels in wireless sensor networks,” IEEE Trans. Signal Processing, vol. 54, pp. 1018-1027, Mar. 2006.

N. Heo and P. K. Varshney, “Energy-efficient deployment of intelligent mobile sensor networks,” IEEE Trans. Syst., Man, Cybern. A, vol. 35, pp. 78-92, Jan. 2005.

Degree(s):

• Ph. D., Electrical Engineering, Princeton University, Princeton, NJ, 2007
• M.A., Electrical Engineering, Princeton University, Princeton, NJ, 2004
• M.S., Electrical Sciences and Computer Engineering, Brown University, Providence, RI, 2001
• B.S., Electrical and Electronics Engineering, Bogazici University, Istanbul, Turkey, 1999

Research Interests:

• Computer vision
• Video/image processing
• Wireless smart camera networks (Wi-SCaNs)
• Distributed smart camera systems
• Mobile camera applications
• Multi-camera multi-object tracking
• Video event detection
• Object recognition
• Image understanding and multimedia
• Pattern recognition
• Detection and estimation
• Statistical learning
• Signal processing

Current Research:

Dr. Velipasalar’s primary areas of research are embedded computer vision, mobile camera applications and wireless embedded smart cameras, which combine sensing, processing and communication on a single embedded platform. Dr. Velipasalar has been working on designing resource-efficient algorithms that are suitable for embedded platforms, fall detection, step counting and activity classification with wearable cameras, traffic light detection and alert signal detection with vehicle-mounted cameras, distributed target detection and tracking across overlapping and non-overlapping cameras, and resource allocation strategies and detection of events of interest on embedded smart cameras. Potential uses include military surveillance, public transportation, health care and elder care, traffic systems, and industrial and retail applications.

Lab website: www.vision.syr.edu

Courses Taught:

• Image and Video Processing
• Multi-camera Systems
• Introduction to Embedded System Design
• Electrical Engineering Fundamentals

Honors/Awards:

• NSF CAREER Award, 2011
• 2014 Excellence in Graduate Education Faculty Recognition Award
• Graduate School All University Doctoral Prize, received by Dr. Velipasalar’s former Ph.D. student Akhan Almagambetov, 2014.
• Intelligent Transportation Society (ITS) of NY Best ITS Student Essay Award, received by Dr. Velipasalar’s former Ph.D. student Akhan Almagambetov, based on their research on vehicle taillight tracking and alert signal detection, May 2013.
• The college-wide award for “Applicability of Research to Business and Industry”, Nunan Lecture and Research Day, April 2013.
• Third place paper award at the ACM/IEEE International Conference on Distributed Smart Cameras for the paper titled “Energy-efficient Feedback Tracking on Embedded Smart Cameras by Hardware-level Optimization”, 2011
• EPSCoR First Award, 2009
• UNL Layman Award as Co-PI, 2009
• Best Student Paper Award at the IEEE International Conference on Multimedia & Expo (ICME) for the paper titled “Design and Verification of Communication Protocols for
• Peer-to-Peer Multimedia Systems,” 2006
• IBM Patent Application Award, 2005
• Travel Grant, Office of Graduate Affairs, Princeton University, 2005
• Graduate Fellowship, Princeton University, 2002
• Graduate Fellowship, Brown University, 1999
• NETAS Scholarship given on highly selective basis to successful engineering students, 1999
• Sabanci Scholarship for outstanding success at the university entrance examination, 1994
• The award from Is Bank to the top 70 students, out of about 1 million, in the university entrance examination, 1994

Selected Publications:

(Please visit https://ecs.syr.edu/faculty/velipasalar/ for a complete list)

Degree:

• Ph.D. Computer Science, Georgia Tech

Research Interests:

• System Security: Verifiable database outsourcing, cloud security, applied cryptography, multi-party computation, secure healthcare applications
• Big-Data Systems: Key-value stores, big-data analytics, graph databases, data streaming
• Performance: Scalability and elasticity, distributed system tracing, profiling and monitoring, automatic performance optimization, stress testing

Current Research:

Yuzhe Tang’s research interests are in building secure distributed with a current research focus on making modern database trustworthy and applying multi-party computations for federated big-data computation.

Courses Taught:

• Advanced computer architecture, distributed systems in cloud

Selected Publications:

Yuzhe Tang, Arun Iyengar, Wei Tan, Liana Fong, Ling Liu, B. Palanisamy. “Deferred Lightweight Indexing for Log-Structured Key-Value Stores”, in CCGrid’15, the Best Paper Award

Yuzhe Tang, Ling Liu. “Privacy-Preserving Multi-Keyword Search in Information Networks”, in TKDE’15

Yuzhe Tang, Ting Wang, Ling Liu, Xin Hu, Jiyong Jang. “Lightweight Authentication of Freshness in Outsourced Key-Value Stores”, in ACSAC’14

Yuzhe Tang, Ling Liu, Arun Iyengar. “e-PPI: Locator Service in Information Networks with Personalized Privacy Preservation”, in ICDCS’14

Yuzhe Tang, Bugra Gedik. “Auto-pipelining for Data Stream Processing”, in TPDS’13, Vol 24(12), pp 2344-2354

Yuzhe Tang, Jianliang Xu, Shuigeng Zhou, Wang-Chien Lee, Dingxiong Deng, Yue Wang. “A Lightweight Multi-dimensional Index for Complex Queries over DHTs”, in TPDS’11, Vol 22(12), pp 2046-2054

Yuzhe Tang, Shuigeng Zhou, Jianliang Xu. “LIGHT: A Query-Efficient yet Low-Maintenance Indexing Scheme over DHTs”, in TKDE’10, Vol 22(1), pp 59-75

Degree:

• Ph.D. in Computer Science, University of Virginia
• Master of Computer Science, University of Virginia
• B.S. in Computer Science and Engineering, Bangladesh University of Engineering and Technology

Research interests:

• Internet of Things (IoT)
• Pervasive and Ubiquitous Computing
• Machine Learning
• Connected and Mobile Health
• Cyber-Physical Systems (CPS)

Current Research:

My research takes a multi-disciplinary approach to develop novel and practical human behavioral and physical event sensing technologies that overlap with machine learning, human-centered Computing (e.g., health computing, human-machine interaction, and wellness monitoring applications), internet of things, cyber-physical systems and natural language processing. I enjoy building data-driven, application-specific novel technologies, as well as new systems and applications that involve sensors, mobile devices and cloud services. Research challenges that I deal with are the uncertainties in physical world sensing, human factors, such as, the user-context and mobility, limitation of current technologies, and resource constraints of the sensing data and platform. Technologies and systems that I develop are human-centric, several of them are attributed to health and wellness, and in general, they are in the scope of ubiquitous computing.

Teaching Interests:

• Design and Analysis of Algorithms

Honors:

• Graduate Student Award for Outstanding Research, UVA Department of Computer Science, 2018
• Nominated for Best Paper Award, Wireless Health 2016

Recent Publications:

• A. Salekin, S. Ghaffarzadegan, Z. Feng and J. Stankovic. A Real-Time Audio Monitoring Framework with Limited Data for Constrained Devices, The 15th International Conference on Distributed Computing in Sensor Systems (DCOSS 2019).
• A. Salekin, Jeremy W. Eberle, Jeffrey J. Glenn, Bethany A. Teachman, and John A. Stankovic. 2018. A Weakly Supervised Learning Framework for Detecting Social Anxiety and Depression, ACM Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), Vol. 2, No. 2, Article 81 (June 2018), 26 pages. (and Ubicomp 2018)
• A. Salekin, Z. Chen, M. Ahmed, J. Lach, D. Metz, K. de la Haye, B. Bell, and J. Stankovic, Distance Emotion Recognition, ACM Interactive, Mobile, Wearable, and Ubiquitous Technologies (IMWUT), Vol. 1, Issue 3, Sept. 2017, 96:1-96:24. (Ubicomp 2017)
• A. Salekin, H. Wang, K. Williams, and J. Stankovic, DAVE: Detecting Agitated Vocal Events, The IEEE/ACM International Conference on Connected Health: Applications, Systems and Engineering Technologies (CHASE), July 2017.
• Z. Chen, M. Ahmed, A. Salekin, and John A. Stankovic, ARASID: Artificial Reverberation-Adjusted Indoor Speaker Identification Dealing with Variable Distances, International Conference on Embedded Wireless Systems and Networks (EWSN), 2019.

Degrees:

• Ph.D., Computer Science, Marquette University, Wisconsin, USA (2013)
• M.S., Computer Science, Marquette University, Wisconsin, USA (2010)
• B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology (BUET), Bangladesh (2008)

Research interests:

• Mobile and pervasive health technologies
• Internet-of-Things
• Computer science education
• Impact of active learning pedagogy in CS courses
• Broadening participation of women and underrepresented students in CS

Current research:

Her research spans the domains of mobile healthcare, healthcare data analytics, and pervasive health technologies. Broadly, her research focuses on integrating mobile and pervasive technologies in health and wellness environments to improve users’ quality of life, mental and physical wellbeing. Her research also expands in the direction of mobile security, information and communication technology for development (ICT4D), Computer Science education, broadening participation in computing, best practices in undergraduate research, and how different pedagogical practices can increase diversity in CS. She is also interested in finding why and how people from diverse backgrounds are learning programming in 21^stcentury and how the development of new kind of scalable programming environments or platform can support all kind of learners.

Teaching Interests:

• Introduction to Programming
• Object-Oriented Programming
• Data Structure
• Mobile Application Programming
• Mobile and Pervasive Computing
• Computer Architecture

Honors:

• Provost LA Initiative Award, Florida International University, Spring 2018-2019
• Best paper award, IEEE Conference on Networking Systems and Security (NSysS’ 16), 2016
• Systers Pass-It-On (PIO) Award, Anita Borg Institute, 2014
• Best paper award, IEEE International Conference on e-Health Networking, Applications and Services (Healthcom’ 12), 2012

Recent Publications:

1. Claire Fulk, Grant Hobar, Kevin Olsen, Samy El-Tawab, Puya Ghazizadeh, and Farzana Rahman. Cloud-based Low-cost Energy Monitoring System through the Internet of Things. In Proceedings of the IEEE International Workshop of Mobile and Pervasive Internet of Things (PerIoT 2019), in Conjunction with IEEE Percom ’19. Japan, March 2019.
2. Farzana Rahman and Samy El-Tawab. App Development for the Social Good: Teaching Socially Conscious Mobile App Development in an Upper-Level Computer Science Course. In Proceedings of the 2019 ASEE Annual Conference and Exposition (ASEE ’19), Orlando, FL, July 2019.
3. Farzana Rahman. Leveraging Visual Programming Language and Collaborative Learning to Broaden Participation in Computer Science. In Proceedings of the 19th Annual Conference on Information Technology Education (SIGITE ’18), Ft Lauderdale, FL, Oct 2018.
4. Saiyma Sarmin, Nafisa Anzum, Kazi Hasan Zubaer, Farzana Rahman, A. B. M. Alim Al Islam. Securing Highly-Sensitive Information in Smart Mobile Devices through Difficult-to-Mimic and Single-Time Usage Analytics. In Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems, Computing, Networking and Services (MobiQuitous ’18), Nov 2018.
5. Farzana Rahman. From App Inventor to Java: Introducing Object-oriented Programming to Middle School Students Through Experiential Learning. In Proceedings of the 2018 ASEE Annual Conference and Exposition (ASEE ’18), Salt Lake City, UT, July 2018.
6. Farzana Rahman, Healthy Hankerings: Motivating Adolescents to Combat Obesity with a Mobile Application. In Proceedings of the 20th International Conference on Human-Computer Interaction (HCI International ’18), NV, July, 2018.
7. Farzana Rahman, Perry Fizzano, Evan M. Peck, Shameem Ahmed, and Stu Thompson. How to Build a Student-Centered Research Culture for the Benefit of Undergraduate Students. In Proceedings of the 49th ACM Technical Symposium on Computer Science Education (SIGCSE ’18), Maryland, Feb 2017.

Degree:

• Ph.D. Texas Tech University

Research Interests:

• Cyber Security – Cyber offense and defense
• Machine Learning
• Smart phones and tablets security
• Biometrics — network based and standalone

Current Research:

My focus is to do original research that cuts across conventional rigorously defined disciplines and unifies basic and common concepts across disciplines. In particular, my research centers around security (malignant systems, active authentication, for example touch based authentication on mobile devices) and machine learning (decision trees, statistical, and evolutionary methods) with a focus on large time series data streams and static data sets, and computer networks (anomalies, optimization). I am also using these methods to build field realizable defensive and offensive Cyber-based systems.

Courses Taught:

• Security and Machine learning; Biometrics
• Applied Cryptography

Honors:

• AAAS Fellow (elected 2018);  NAI Fellow (elect 2020)
• IEEE Region 1 Technological Innovation  Award, 2017
• SDPS Fellow (elected 2010)
• ACM Distinguished Scientist (elected 2008)
• ACM Distinguished Speaker (2012-2015)

Selected Publications:

• Amith K. Belman, Vir V. Phoha. Discriminative Power of Typing Features on Desktops, Tablets, and Phones for User Identification.ACM Transactions on Privacy and Security. 23(1): 4:1-4:36 (2020)
• Jin, Vir V. Phoha and R. Zafarani, “Graph-based Identification and Authentication: A Stochastic Kronecker Approach,” in IEEE Transactions on Knowledge and Data Engineering, doi: 10.1109/TKDE.2020.3025989.
• Li, W. Wang, Y. Gao, Vir V. Phoha and Z. Jin, “Wrist in Motion: A Seamless Context-Aware Continuous Authentication Framework Using Your Clickings and Typings,” in IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 2, no. 3, pp. 294-307, July 2020, doi: 10.1109/TBIOM.2020.2997004.
• Yang Gao; Wei Wang; Vir V Phoha; Wei Sun; Zhanpeng Jin. EarEcho: Using Ear Canal Echo for Wearable Authentication.Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), Vol. 3, No. 3, Article 81. Publication date: September 2019. Presented in The 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2019), London, UK, September 11-13, 2019.
• Shukla and Vir V. Phoha, “Stealing Passwords by Observing Hands Movement,” in IEEE Transactions on Information Forensics and Security, vol. 14, no. 12, pp. 3086-3101, Dec. 2019, doi: 10.1109/TIFS.2019.2911171.

Degree(s):

• Ph. D., State Univ. of New York at Stony Brook
• B.Tech., Indian Institute of Technology, Kanpur

Lab/Center Affiliation(s) :

• Syracuse Evolutionary and Neural Systems Exploration (SENSE) Lab
• Smart Grid Lab

Research Interests:

• Artificial intelligence
• Evolutionary algorithms
• Data mining
• Social networks
• Bioinformatics

Current Research:

Recent work has involved the development of algorithms for:

the recognition of patterns in promoter regions of genome sequences,
unsupervised detection of anomalies in data (including time series), and
optimization problems in the design of multiband cognitive radio networks.
Other current work includes the investigation of robustness properties of social networks, as well as the use of network models in understanding the dynamics of evolutionary algorithms.

Teaching Interests:

• Smart grid
• Social networks
• Evolutionary algorithms
• Neural networks

Honors:

• Distinguished Scholar Award, International Society of Applied Intelligence, July 2011.

Selected Publications:

Linkage Sensitive Particle Swarm Optimization (D. Devicharan and C.K. Mohan), in Handbook of Swarm Intelligence – Concepts, Principles, and Applications (eds. B.K. Panigrahi, Y. Shi, and B. Lim), pp. 119-132, 2011.

Rank-Based Outlier Detection with (HuaMing Huang, Kishan Mehrotra Chilukuri K. Mohan), in Journal of Statistical Computation and Simulation, Oct. 2011.

Distributed In-Network Path Planning for Sensor Network Navigation in Dynamic Hazardous Environments (D. Chen, C.K. Mohan, K.G. Mehrotra, and P.K. Varshney), in Wireless Communications and Mobile Computing 12(8): 739-754, 2012.

SMAlign: Alignment of DNA Sequences with Gap Constraints (F. Alobaid, K. Mehrotra, C.K. Mohan, and R. Raina), in Proc. BICOB, Las Vegas, March 2012.

Reference Set Metrics for Multi-Objective Algorithms (C.K. Mohan and K. Mehrotra), in Proc. SEMCCO, pp.723-730, Dec. 2011.

Mobile ad hoc networks, Satellite networks, Artificial intelligence, and 5G-and-beyond networks

Degree:

• Doctorate of Philosophy, Computer Science, University of Maryland at College Park
• Bachelor of Science, Computer Engineering, Michigan State University

Research interests:

• Programming Languages
• Static Analysis
• Formal Methods
• Foundations of Computer Security and Privacy

Current Research:

My research lies at the intersection of the theory and application of program analyses. Program analyses are tools that examine programs and determine (prove) facts about them. For example, a program analysis might prove that a program can never crash due to a type error. In general, however, program analyses can be arbitrarily complex and infer subtle program invariants relating to myriad applications (such as computer security).

Because program analyses must always approximate program behavior (otherwise they could solve the halting problem), there is an inherent tradeoff between analysis precision and analysis performance. Currently, program analyses are often applied only in limited contexts, as gaining acceptable performance requires too many compromises in terms of analysis precision. My current work focuses on three concurrent threads: tackling fundamental issues relating to scaling static analysis (specifically, scaling analyses to run on supercomputers rather than a single machine as all current analyses do); engineering those analyses (to allow analysis reuse); and applying those analyses to computer security (e.g., to check properties such as information flow and to support complex reverse engineering tasks).

Teaching Interests:

• Programming Languages
• Computer Security
• Formal Logic and Discrete Mathematics

Recent Publications:

• Symbolic Path Tracing to Find Android Permission-Use Triggers. NDSS Workshop on Binary Analysis Research (BAR 2019).
• User Comfort with Android Background Resource Accesses in Different Contexts Symposium on Usable Privacy and Security (SOUPS 2018).
• User Interactions and Permission Use on Android (CHI 2017).

Degree(s):

• Ph.D, Massachusetts Institute of Technology 1985
• M.S., Massachusetts Institute of Technology 1981
• B.S., Seoul National University, Seoul, Korea 1976

Lab/Center Affiliation(s):

• Electromagnetics Laboratory

Research Interests:

• Electromagnetic fields and waves
• Waves in complex and anisotropic media
• Antennas and propagation
• Microwave remote sensing

Current Research:

Development of dyadic Green’s functions for various complex media:
Dyadic Green’s functions (DGFs) have been an important and major tool for solving a great number of electromagnetic problems in many decades. Finding DGFs for anisotropic media have been very challenging due to its complexity. My research has been to obtain the DGFs for several different types of anisotropic media – including (i) uniaxially anisotropic medium, (ii) biaxially anisotropic medium, (iii) electrically gyrotropic (gyroelectric) medium, and (iv) magnetically gyrotropic (gyromagnetic) medium.

Wave propagation and scattering involving complex media:
The DGFs that we obtained above are used to solve a variety of theoretical and practical problems involving complex (anisotropic) media. We have investigated and solved the problems of wave propagation, reflection & transmission, radiation and scattering of electromagnetic waves in the presence of such anisotropic media as well as bianisotropic media. Problems of antennas and microstrip circuits have also been treated.

Courses Taught:

• Electromagnetics I & II
• Electromagnetic Engineering
• Antennas and Antenna Systems
• Electromagnetic Fields

Honors:

• Magna Cum Laude Honor, Seoul National University, Korea, 1976.
• Eta Kappa Nu Outstanding Undergraduate Teacher Award, 1999.
• IEEE Third Millennium Medal, 2000
• The Technology Alliance of CNY – College Educator of the Year Award, 2002
• IEEE Region 1 Award, August 2002
• Who’s Who in Electromagnetics

Selected Publications:

Arlon T. Adams and Jay K. Lee, Electromagnetics, University Readers, First Edition, 2012; Cognella, Revised First Edition, 2015.

[Undergraduate Electromagnetics course textbook, 632 pages] https://titles.cognella.com/electromagnetics-9781626615847.html

Brian J. Rautio, Vladimir I. Okhmatovski, Andreas C. Cangellaris, James C. Rautio, and Jay K. Lee, “The unified-FFT algorithm for fast electromagnetic analysis of planar integrated circuits printed on layered media inside a rectangular enclosure,” IEEE Trans. Microwave Theory and Techniques, vol. 62, No. 5, pp. 1112-1121, May 2014.

Ying Huang and Jay K. Lee, “Radiation from an arbitrarily oriented Hertzian dipole in the presence of a gyroelectric slab,” IEEE Trans. Antennas and Propagation, Vol. 62, No. 4, pp. 1837- 1843, April 2014.

Jennifer W. Graham and Jay K. Lee, “Reflection and transmission from biaxially anisotropic-isotropic interfaces,” Progress In Electromagnetics Research, Vol. 136, pp. 681-702, 2013.

Chong Mei, Moamer Hasanovic, Jay K. Lee, and Ercument Arvas, “Comprehensive solution to scattering by bianisotropic objects of arbitrary shape,” Progress In Electromagnetics Research B, Vol. 42, pp. 335-362, 2012.

Abdullah Eroglu, Yun Hee Lee, and Jay K. Lee, “Dyadic Green’s functions for multi-layered uniaxially anisotropic media with arbitrarily oriented optic axis,” IET (Institution of Engineering and Technology) Microwaves, Antennas & Propagation, Vol. 5, Iss.15, pp. 1779-1788, 2011.

Ying Huang and Jay K. Lee, “Dyadic Green’s functions for unbounded and two-layered general anisotropic media,” Progress in Electromagnetics Research (PIER) B, Vol. 30, pp. 27-46, 2011.

Abdullah Eroglu and Jay K. Lee, “Far field radiation from an arbitrarily oriented Hertzian dipole in an unbounded electrically gyrotropic medium,” Progress in Electromagnetics Research (PIER), vol. 89, pp. 291-310, 2009.

Abdullah Eroglu and Jay K. Lee, “The complete design of microstrip directional couplers using the synthesis technique,” IEEE Transactions on Instrumentation and Measurement, vol. 57, No. 12, pp. 2756-2761, December 2008.

Ahmet Yagli, Jay K. Lee and Ercument Arvas, “Monochromatic scattering from three-dimensional gyrotropic bodies using the TLM method,” Applied Computational Electromagnetics Society (ACES ) Journal, vol. 22, No. 1, pp. 155-163, March 2007.

Degree(s):

Ph.D. (U. of Maryland, College Park, 1998); M.A. (U. of Maryland, College Park, 1996); M.A. (U. of Michigan, Ann Arbor, 1988); B.A. (U. of Hong Kong, 1987).

Research Interests:

• Discrete Mathematics
• Computability Theory
• Computational Learning
• Artificial Intelligence
• Logic and Formal Methods

Current Research:

I study the role of queries and the associated learning strategies in solving computational problems. For example, the strategies for playing many board games and on-line games often resemble a basic paradigm in machine learning, namely, to learn a target concept via queries. By studying the (winning) strategies in specific concrete games, we may gain insights to determine the right set of queries and related parameters that are of interest in machine learning applications. I am also interested in graph coloring and graph labeling type problems. Many arise quite naturally in the study of social structures and networks. To better understand them it often requires new algorithms and analysis.

As an educator, I am interested in engaging students to do research. In addition, I like to explore new pedagogies to improve students’ reasoning ability, develop their inquisitiveness and strengthen their problem solving skills. Along in this direction I like to cast some of the research problems listed above in elementary settings and make them accessible to undergraduates and beginning graduate students.

Courses Taught:

• Artificial intelligence
• Data structures
• Algorithms
• Automata and Computability
• Formal methods

Selected Publications:

Andrew C. Lee, Sin-Min Lee and Ho-Kun Ng, On the balance index set of bi-regular and tri-regular graphs, 78, Journal of Combinatorial Mathematics and Combinatorial Computing, August 2011, pp.169-186.

Man Kong, Andrew C. Lee and Sin-Min Lee, On the Balance Index Sets of Homeomorph of Regular Graphs, Congressus Numerantium, vol. 204, Dec. 2010, pp. 193-203.

Andrew C. Lee and Sin-Min Lee and Hsin-Hao Su, On the balanced indexed set of generalized friendship graphs, envelope graphs of cycles and cubic graphs, Congressus Numerantium, 196 (2009), pp. 3-22.

William I. Gasarch and Andrew C. Lee, Inferring answers to queries, Journal of Computing and Systems Sciences Volume 74, No 4, 2008, 490-512.

Degrees

• Ph.D. in Computer Science, McGill University
• M.S. in Computer Science, Northeastern University (CN)
• B.S. in Computer Science, Northeastern University (CN)

Research interests

• Security, sustainability, and real-time aspects for Cyber-Physical Systems and Internet of Things

Current Research

My research interests include security, sustainability and real-time aspects for Cyber-Physical Systems (CPS) and Internet of Things (IoT). My application areas include automobiles and transportation systems, cloud and data centers, and power and energy systems. My research techniques include optimization, algorithm design, data analysis, machine learning, control, and game theory.

Courses taught

• Design of Operating Systems

Recent Publications

• Fanxin Kong, Meng Xu, James Weimer, Oleg Sokolsky, and Insup Lee, “Cyber-Physical System Checkpointing and Recovery”, in the 9th ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), 2018.
• Fanxin Kong, Xue Liu, and Insup Lee, “Joint Rate Control and Demand Balancing for Electric Vehicle Charging”, in the 3rd ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI), 2018.
• Fanxin Kong, Xue Liu, Zhonghao Sun, and Qinglong Wang, “Smart Rate Control and Demand Balancing for Electric Vehicle Charging”, in the ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS), 2016, pp. 1-10.
• Fanxin Kong and Xue Liu, “GreenPlanning: Optimal Energy Source Selection and Capacity Planning for Green Datacenters”, in the ACM/IEEE 7th International Conference on Cyber-Physical Systems (ICCPS), 2016, pp. 1-10.

Degree(s):

Ph.D. Computer Science, University of Illinois at Urbana-Champaign

M.S. Computer Science and Engineering, Seoul National University, Seoul, Korea

B.S. Computer Science and Engineering, Seoul National University, Seoul, Korea

Research interests:

• AI/Machine learning for Cyber-Physical Systems (CPS)
• Safety-/Time-critical systems
• Real-time embedded systems

Current Research:

Dr. Kim’s current research lies at cyber-physical systems incorporating AI/machine learning capabilities. Cyber-physical and embedded systems are usually running in a resource-constrained environment. Hence, depending on the criticality of the learning applications, an advanced learning performance could be compromised while satisfying certain temporal and spatial requirements of the system’s core and essential tasks. Her research interest also includes developing systematic and analytic way to enhance and/or decompose the performance of learning components running in cyber-physical and embedded systems.

Teaching Interests:

My teaching interests include cyber-physical systems for safety-critical systems and/or machine learning systems, as well as real-time embedded systems.

Honors:

• NSF SaTC (Secure and Trustworthy Cyberspace): CORE: Small: Partition-Oblivious Real-Time Hierarchical Scheduling, Co-PI, National Science Foundation, 2020–2023
• GPU Grant by NVIDIA Corporation, 2018
• The MIT EECS Rising Stars, 2015
• The Richard T. Cheng Endowed Fellowship, 2015 – 2016

Recent Publications:

• Man-Ki Yoon, Mengqi Liu, Hao Chen, Jung-Eun Kim and Zhong Shao, “Blinder: Partition-Oblivious Hierarchical Scheduling,” in Proceedings of the 30th USENIX Security Symposium (USENIX Security ’21), Aug. 2021.
• Jung-Eun Kim, Richard Bradford, Max Del Giudice and Zhong Shao, “Adaptive Generative Modeling in Resource-Constrained Environments,” in Proceedings of the 24th ACM/IEEE Design, Automation, and Test in Europe (DATE), Feb. 2021.
• Jung-Eun Kim, Richard Bradford, Max Del Giudice and Zhong Shao, “Paired Training Framework for Time-Constrained Learning,” in Proceedings of the 24th ACM/IEEE Design, Automation, and Test in Europe (DATE), Feb. 2021.
• Jung-Eun Kim, Richard Bradford and Zhong Shao, “AnytimeNet: Controlling Time-Quality Tradeoffs in Deep Neural Network Architectures,” in Proceedings of the 23rd ACM/IEEE Design, Automation, and Test in Europe (DATE), Mar. 2020.
• Jung-Eun Kim, Richard Bradford, Man-Ki Yoon and Zhong Shao, “ABC: Abstract prediction Before Concreteness,” in Proceedings of the 23rd ACM/IEEE Design, Automation, and Test in Europe (DATE), Mar. 2020.

Degree:

• Ph.D. in Computer Science and Engineering, Seoul National University
• M.S. in Electrical Engineering and Computer Science, Seoul National University
• B.S. in Electrical Engineering and Computer Science, University of California, Berkeley

Research interests:

• Flash and non-volatile memory-based systems
• Data storage systems
• File systems and key-value stores

Current Research:

I am broadly interested in computer systems and particularly focused on data storage systems. Current research directions include, but are not limited to, capacity-variant storage systems, self-learning systems, and next-generation key-value storage.

Recent Publications:

• Hyeongyu Lee, Juwon Lee, Minwook Kim, Donghwa Shin, Sungjin Lee, Bryan S. Kim, Eunji Lee, and Sang Lyul Min. “SpartanSSD: a Reliable SSD under Capacitance Constraints,” in ACM/IEEE International Symposium on Low Power Electronics and Design, 2021
• Jinhyung Koo, Junsu Im, Jooyoung Song, Juhyung Park, Eunji Lee, Bryan S. Kim, and Sungjin Lee. “Modernizing File System through In-Storage Indexing,” in USENIX Symposium on Operating Systems Design and Implementation, 2021
• Jeseong Yeon, Leeju Kim, Youil Han, Hyeon Gyu Lee, Eunji Lee, and Bryan S. Kim. “JellyFish: A Fast Skip List with MVCC,” in ACM/IFIP International Middleware Conference, 2020
• Youil Han, Bryan S. Kim, Jeseong Yeon, Sungjin Lee, and Eunji Lee. “TeksDB: Weaving Data Structures for a High-Performance Key-Value Stores,” in International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), 2019
• Bryan S. Kim, Eunji Lee, Sungjin Lee, Sang Lyul Min. “CPR for SSDs,” in ACM SIGOPS Workshop on Hot Topics in Operating Systems (HotOS), 2019
• Bryan S. Kim, Jongmoo Choi, and Sang Lyul Min. “Design Tradeoffs for SSD Reliability,” in USENIX Conference on File and Storage Technologies (FAST), 2019
• Geonhee Lee, Hyeon Gyu Lee, Juwon Lee, Bryan S. Kim and Sang Lyul Min. “An Empirical Study on NVM-based Block I/O Caches,” in ACM SIGOPS Asia-Pacific Workshop on Systems (APSys), 2018
• Bryan S. Kim, Hyun Suk Yang, and Sang Lyul Min. “AutoSSD: an Autonomic SSD Architecture,” in USENIX Annual Technical Conference (ATC), 2018
• Bryan S. Kim. “Utilitarian Performance Isolation in Shared SSDs,” in USENIX Workshop on Hot Topics in Storage and File Systems (HotStorage), 2018
• Bryan S. Kim, Yonggun Lee, and Sang Lyul Min. “Framework for Efficient and Flexible Scheduling of Flash Memory Operations,” in IEEE Non-Volatile Memory Systems and Applications (NVMSA), 2017
• Bryan S. Kim and Sang Lyul Min. “QoS-aware Flash Memory Controller,” in IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), 2017

Degrees

• M.S. in Computer Science, Syracuse University
• Ph.D. in Computer Engineering, Syracuse University

Teaching Interests

• Data Structures and Algorithms
• Object-Oriented Design
• Mobile Application Development
• Software Engineering

Degrees:

• B.A. Philosophy, Cornell University, 2007
• M.A. Mathematics, City College of New York, 2011
• Ph.D. Computer Science, University of Maryland, College Park, 2017

Research interests:

• Neural Computation
• Cognitive Robotics
• Dynamical Systems

Current Research:

My current research focuses on programmable neural networks: neural networks that can be “programmed” like a conventional computer to execute symbolic, cognitive-level tasks, but can then refine that procedural knowledge by learning from examples and experience.  One application of this work is in robotic imitation learning: “programming” robots from a single human demonstration of a task that requires high-level planning and reasoning.  A second application of this work is modeling the neural basis of cognition, and cognitive disorders, in humans.

In other research I am developing new solution methods for fixed point location in recurrent neural networks and other dynamical systems, including gradient flows of optimization objective functions.  This work applies broadly to solving non-linear systems of equations and non-convex optimization.  I have also worked on methods for computational tomography of biological virus particles.

Teaching Interests:

My teaching interests include machine learning and artificial intelligence, especially neural computation and automated planning, as well as dynamical systems, robotics, and human-robot interaction.

Honors:

• Best student paper award at the 9^thInternational Conference on Artifical General Intelligence, 2016
• Distinguished Graduate Student Teacher, University of Maryland, 2014

Recent Publications:

• Katz GE, Reggia JA (2017). Using Directional Fibers to Locate Fixed Points of Recurrent Neural Networks. IEEE Transactions on Neural Networks and Learning Systems.  DOI 10.1109/TNNLS.2017.2733544
• Katz GE, Huang DW, Hauge T, Gentili RJ, Reggia JA (2017).  A Novel Parsimonious Cause-Effect Reasoning Algorithm for Robot Imitation and Plan Recognition.  IEEE Transactions on Cognitive and Developmental Systems.  IEEE. DOI 10.1109/TCDS.2017.2651643

Degree(s):

• Ph.D. University of Florida, Gainesville, FL, 1985.
• M.S. Middle East Technical University, Ankara, Turkey, 1980.
• B.S. Middle East Technical University, Ankara, Turkey, 1978.

Lab/Center Affiliation(s):

• Syracuse Center of Excellence
• CASE Center

Research Interests:

• Intelligent systems applications
• Indoor environment control
• Modeling and forecasting for financial systems
• Medical Instrumentation

Current Research:

Modeling complex systems for improved control, forecasting, and signal processing is at the heart of my current research. I use a combination of analytical and computational methods, such as neural nets, fuzzy logic and genetic algorithms, validated by experimental and simulated data. We have applied this approach to process control, indoor environmental control, medical instrumentation, diagnostics and prognostics, and computational finance.

Courses Taught:

• Controls

Honors:

• Eta Kappa Nu, Member
• Tau Beta Pi, Member
• Golden Key, Honorary Member
• Who is Who in Science and Engineering, 9th Edition, 2006
• Outstanding Undergraduate Teacher, Eta Kappa Nu Syracuse University Chapter, 1998
• K.S. Fu Award, North American Fuzzy Information Processing Society, 1997
• Outstanding Service Award, Syracuse University, College of ECS, 1997
• Who is Who in American Education, 4th Edition, 1994
• University of Florida, Presidential Recognition, 1983

Selected Publications:

Dhummi, V., D. W. Demetriou, H. Palanthandalam-Madapusi, H. E. Khalifa, C. Isik, “Robust Occupancy-based Distributed Demand Ventilation”, International J. of Ventilation, Volume 9, No 4, March 2011.

Colak, S., C. Işık, H. E. Khalifa, J. Dannenhoffer, J. Grunewald, “Heat and Moisture Transport Modeling for a Protective Garment with an Active Sweating Device”, in ASME Congress, Vancouver, Canada, 2010.

Demetriou, D., O. Ozdemir, H. E. Khalifa and C. Isik, “Distributed Demand Controlled Ventilation for Improving IAQ”, Proc. Indoor Air 2008, Copenhagen, Denmark, 2008.

Sazli, M.H., Isik, C., “Neural Network Implementation of the BCJR Algorithm”, Digital Signal Processing, Volume 17, January 2007, pp 353-359.

Ari, S., I. Cosden, H. E. Khalifa, J. Dannenhoffer, P. Wilcoxen, and C. Isik, “Individual Thermal Comfort and Energy Optimization”, Proc. Clima2007, Helsinki, Finland, 2007.

S. Zhang, C.K. Mohan, P. Varshney, C. Isik, K. Mehrotra, S. Wang, Z. Gao, and R. Rajagopalan, “Coupling of Airflow and Pollutant Dispersion Models with Evacuation Planning Algorithms for Building System Controls”, ASHRAE Transactions. Vol. 112. Part 1. 2006.

Isik, C., “Blood Pressure Measurement”, invited chapter, the Encyclopedia of Medical Devices and Instrumentation, 2nd Ed, Vol 1. John G. Webster (Ed), Wiley, 2006.

Degree:

• Ph.D., Computer Science, Purdue University, 2015
• M.S., Computer Science, Marquette University, 2010
• B.S., Computer Science and Engineering, Bangladesh University of Engineering and Technology, 2008

Research interests:

• Security of computer networks and systems
• IoT systems security
• Program analysis, software testing and verification
• Vulnerability detection

Current Research:

His research focuses on the security of computer networks and systems. The software of computer networks and systems continues to have exploitable vulnerabilities, which are lucrative targets for adversaries. Within this broad domain, his particular emphasis is on automated detection of vulnerabilities as well as creating resilient protocols and systems. His research primarily builds on and expands program analysis, software engineering, and formal verification. His interests span several domains of computing, including network communication protocols, operating systems, distributed systems, internet-of-things (IoT) systems and embedded devices.

Honors:

• Distinguished Paper Award at NDSS (Network and Distributed System Security Symposium) 2018
• Bilsland Dissertation Fellowship Award from the Graduate School at Purdue University, 2015
• Graduate Teaching Fellowship Award from Dept. of Computer Science at Purdue University, 2014

Recent Publications:

1. Yahyazadeh, P. Podder, E. Hoque, and O. Chowdhury. Expat: Expectation-based Policy Analysis and Enforcement for Appified Smart-Home Platforms. In the proceedings of the 24th ACM Symposium on Access Control Models and Technologies (SACMAT 2019), Toronto, ON, Canada, June 2019
2. Samuel Jero, Endadul Hoque, David Choffnes, Alan Mislove, and Cristina Nita-Rotaru. Automated Attack Discovery in TCP Congestion Control Using a Model-guided Approach. In the proceedings of Network and Distributed System Security Symposium (NDSS), San Diego, California, Feb 2018. [Distinguished Paper Award]
3. Endadul Hoque, Omar Chowdhury, Sze Yiu Chau, Cristina Nita-Rotaru, and Ninghui Li. Analyzing Operational Behavior of Stateful Protocol Implementations for Detecting Semantic Bugs. In the Proceedings of IEEE/IFIP International Conference on Dependable Systems and Networks (DSN), Denver, CO, June 2017.
4. Sze Yiu Chau, Omar Chowdhury, Endadul Hoque, Huangyi Ge, Aniket Kate, Cristina Nita-Rotaru, and Ninghui Li. SymCerts: Practical Symbolic Execution For Exposing Noncompliance in X.509 Certificate Validation Implementations. In the Proceedings of IEEE Symposium on Security and Privacy (S&P), San Jose, CA. May 2017.

Degree(s):

• Ph.D. , Princeton University, 2004.
• B.S., Bogazici University, Istanbul, Turkey, 1999.

Research Interests:

• Wireless communications
• Information theory
• Signal processing
• Cognitive radio systems
• Energy efficiency
• Quality of service provisioning in wireless systems
• Wireless information-Theoretic security

Current Research:

Our recent research concentrated on the energy efficiency in wireless systems, performance analysis in wireless multiuser networks operating under quality of service (QoS) constraints, and energy-security tradeoffs in multi-antenna wireless communications.

We are also currently exploring cooperative and cognitive operation in wireless systems and the impact of interference. In particular, we study the spectrum and energy efficiency in cooperative relay channels, conduct performance analysis in cognitive radio channels in the presence of channel and/or sensing uncertainty, and investigate the throughput in fading interference channels under queuing constraints.

Teaching Interests:

• Digital communications
• Wireless communications
• Information theory
• Signals and systems
• Probability theory and random processes

Honors:

• Gordon Wu Graduate Fellowship, Princeton University
• NSF CAREER Award, 2006
• 2008 EURASIP Journal of Wireless Communications and Networking Best Paper Award
• University of Nebraska-Lincoln (UNL) College Distinguished Teaching Award, 2009
• Holling Family Master Teacher Award (UNL University-wide Teaching Award), 2009
• Maude Hammond Fling Faculty Research Fellowship, 2011

Select Publications:

Journal Papers

D. Qiao, M. C. Gursoy and S. Velipasalar, “Energy Efficiency in Multiaccess Fading Channels under QoS Constraints,” EURASIP Journal on Wireless Communications and Networking: Special Issue on Green Radio, 2012:136, April 2012.

M. C. Gursoy, “Secure Communication in the Low-SNR Regime,” IEEE Transactions on Communications, vol. 60, no. 4, pp. 1114- 1123, April 2012.

D. Qiao, M. C. Gursoy, S. Velipasalar, “Transmission Strategies in Multiple Access Fading Channels with Statistical QoS Constraints,” IEEE Transactions on Information Theory, vol. 58, no. 3, pp. 1578-1593, March 2012.

S. Akin and M. C. Gursoy, “Performance Analysis of Cognitive Radio Systems under QoS Constraints and Channel Uncertainty,” IEEE Transactions on Wireless Communications, vol. 10, no. 9, pp. 2883-2895, Sept. 2011.

M. C. Gursoy, “MIMO Wireless Communications under Statistical Queueing Constraints,” IEEE Transactions on Information Theory, vol. 57, no. 9, pp. 5897-5917, Sept. 2011.

D. Qiao, M. C. Gursoy, and S. Velipasalar, “Secure Wireless Communication and Optimal Power Control under Statistical Queueing Constraints,” IEEE Transactions on Information Forensics and Security, vol. 6, no. 3, pp. 628-639, Sept. 2011.

D. Qiao, M. C. Gursoy, and S. Velipasalar “Energy Efficiency in the Low-SNR Regime under Queueing Constraints and Channel Uncertainty,” IEEE Transactions on Communications, vol. 59, no. 7, pp. 2006-2017, July 2011.

Conference Papers

D. Qiao, M. C. Gursoy, and S. Velipasalar, “Throughput Regions for Fading Interference Channels under Statistical QoS Constraints,” Proc. of the 2012 IEEE Global Communications Conference (Globecom), Dec. 2012.

M. Ozmen and M. C. Gursoy, “Energy Efficiency in Fading Interference Channels under QoS Constraints,” Proc. of the 2012 International Symposium on Information Theory and its Applications (ISITA), Oct. 2012.

Q. Chen and M. C. Gursoy, “Spectrum and Energy Efficiency in Two-Way Multi-Relay Networks with Selective Relaying,” Proc of the 2012 Military Communications Conference (MILCOM), Oct. 2012.

M. Ozmen and M. C. Gursoy, “Impact of Channel and Source Variations on the Energy Efficiency under QoS Constraints,” Proc. of the 2012 IEEE International Symposium on Information Theory (ISIT), Boston, July 2012.

G. Ozcan and M. C. Gursoy, “Channel Sensing and Estimation in Cognitive Relay Networks,” Proc. of the 2012 the IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Turkey, June 2012.

Software Engineering and design

Degree(s):

• Ph. D. Pennsylvania State University

Research Interests:

• Smart grid
• Sensors and measurement
• High speed electronic devices and integrated circuits
• Power engineering
• Power electronics

Current Research:

I am actively developing several research projects in the area of Smart Grid systems, including Distributed Resources, EVs, Microgrid Design and Analysis. Other projects include the design and analysis of FinFET, as well as the development of Thin Film Sensors.

Courses Taught:

• Electronics devices
• Circuits
• Power engineering
• Diversity and ethics in the workplace

Selected Publications:

Nikkhah Mojdehi, P. Ghosh, and M. Fardad, “Energy and Cost Minimization of Bidirectional Frequency Regulation Service by EV following FERC Order 755,” IEEE Power and Energy Society General Meeting, 2015.

Mohammad Nikkhah Mojdehi and Prasanta Ghosh, “Minimization of Energy Usage and Cost for EV during Reactive Power Service”, Best Student Paper, IEEE International conference on Smart Energy Grid Engineering, 2015.

Chenrui Jin, Xiang Sheng and Prasanta Ghosh, “Optimized Electric Vehicle Charging with Intermittent Renewable Energy Sources”, IEEE Journal of Selected Topics in Signal Processing, Vol. 8, No. 6, pp 1063-1072, 2014.

Chenrui Jin, Jian Tang, Prasanta Ghosh, “Optimizing Electric Vehicle Charging with Energy Storage in the Electricity Market,” IEEE Transactions on Smart Grid, vol.4, no.1, pp311-320, 2013.

Feng and P. Ghosh, “Design Consideration in the Development of Multi-Fin FETs for RF Applications” World Journal of Nano Science and Engineering, 2012.

Degrees:

• Ph.D. Computer Science – Purdue University
• MS Computer Science – Purdue University
• MSc Mathematics – Birla Institute of Technology and Science, Goa, India
• B.E. Computer Science – Birla Institute of Technology and Science, Goa, India

Research interests:

• Coding Theory
• Information Theory
• Foundations of Machine Learning

Current Research:

My current research focuses the algorithmic aspects of computing on structured data with applications to coding theory and foundational problems in machine learning.

Teaching Interests:

• Foundations of Big Data Algorithms
• Theory of Computation
• Algorithms
• Coding Theory

Selected Publications:

Venkata Gandikota, Arya Mazumdar, Soumyabrata Pal. “Recovery of sparse linear classifiers from mixture of responses”. Thirty-fouth Conference on Neural Information Processing Systems (NeurIPS), 2020.

Venkata Gandikota, Arya Mazumdar, Ankit Rawat . “Reliable Distributed Clustering with Redundant Data Assignment”. IEEE Symposium on Information Theory (ISIT), 2020.

Larkin Flodin, Venkata Gandikota, Arya Mazumdar. “Superset Technique for Approximate Recovery in One-Bit Compressed Sensing”. Thirty-third Conference on Neural Information Processing Systems (NeurIPS), 2019.

Degree

• Ph.D., Computer Science, New Mexico State University & University of Udine

Research interest

• Artificial Intelligence
• Machine Learning
• Multiagent Systems
• Data Privacy

Current Research

I work on artificial intelligence, privacy, and machine learning. My recent work focuses on (1) how to make AI algorithms better aligned with societal values, especially privacy and fairness, and (2) how to use machine learning for solving complex optimization problems. I study these questions using methods and models from optimization, statistics, differential privacy, and multiagent systems. For more details, please see my publications.

Teaching Interests

• Artificial Intelligence
• Data Privacy

Honors & Awards

• Google Research Scholar Program award (2022) – Google [Link]
• NSF CAREER Award (2022) – NSF [Press]
• Best Paper Award (2022) – IEEE Transaction of Power System [Link]
• Mario Gerla Young Investigator Award (2021) – ISSNAF [Press]
• ACP Early Career Research Award (2021) – ACP [Link]
• Outstanding Reviewer Award (2021) – NeurIPS [Link]
• Best Paper Award (2021) – IEEE Transaction of Power System [Link]
• Differential Privacy Temporal Map Challenge Award (2020) – NIST ($5,000) [Link]
• Best AI Dissertation Award (2017) – AI*IA [Press]
• Most Visionary Paper Award (2016) – AAMAS Workshop series [Link]
• Best Student Paper Award (2013) – CMSB [Link]

Degree(s):

• BSc in Electrical Engineering, Sharif University of Technology, Iran, 1998.
• MSc in Control Engineering, Iran University of Science and Technology, 2000
• PhD in Mechanical Engineering, University of California, Santa Barbara, 2006

Research Interests:

• Optimization and design problems in dynamical networks;
• Synchronization and consensus in multi-agent networks;
• Optimal control subject to sparsity/architectural constraints.

Current Research:

Makan Fardad’s research interests are in the analysis and optimization of dynamical networks. Particular focus is on extending ideas from controls, dynamical systems, and optimization theory to problems in network science. Application areas include synchronization of oscillator networks, optimal control of vehicular formations, design of sensor networks, and problems in social networks such as community detection, leader selection, and consensus formation.

Courses Taught:

• Optimization and optimal control (ELE 712)
• Modern control (ELE 612)
• Functional methods of engineering analysis (ELE 603)
• Signals and systems (ELE 351)
• Classical control systems (ELE 312)

Honors:

• Dean’s Award for Excellence in Engineering Education, 2015.
• Recipient of 3 National Science Foundation Awards, 2009, 2013, 2015.

Selected Publications:

Fardad, F. Lin, and M. R. Jovanovic, “Design of Optimal Sparse Interconnection Graphs for Synchronization of Oscillator Networks,” IEEE Transactions on Automatic Control, vol. 59, pp. 2457-2462, 2014.

Lin, M. Fardad, and M. R. Jovanovic, “Algorithms for Leader Selection in Stochastically Forced Consensus Networks,” IEEE Transactions on Automatic Control, vol. 59, pp. 1789-1802, 2014.

Lin, M. Fardad, and M. R. Jovanovic, “Design of Optimal Sparse Feedback Gains via the Alternating Direction Method of Multipliers,” IEEE Transactions on Automatic Control, vol. 58, pp. 2426-2431, 2013.

Lin, M. Fardad, and M. R. Jovanovic, “Optimal Control of Vehicular Formations with Nearest Neighbor Interactions,” IEEE Transactions on Automatic Control, vol. 57, pp. 2203-2218, 2012.

Fardad and M. R. Jovanovic, “Design of Optimal Controllers for Spatially Invariant Systems with Finite Communication Speed,” Automatica, vol. 47, pp. 880-889, 2011.

Degree(s):

• Ph.D., Electrical Engineering, Arizona State University, 2012
• MSc. , Electrical Engineering, West Virginia University, 2008
• BSc., Electrical Engineering, University of Tehran, 2006

Research Interests:

• Integration of renewable energy into power systems
• Power system stability and control
• Power system reliability and security
• Phasor Measurement Units (PMU) in smart grids

Current Research:

My research focuses on integration of renewable energy resources and power system stability with high penetration of renewables. I investigate how power systems are impacted when various renewables are integrated into systems. I also investigate how power system operation and planning needs to be modified to accommodate more renewables while achieving reliable power systems.

I also investigate the problems at the intersection of network science theory and power system analysis. This includes identification of critical contingencies and solutions to prevent cascading blackouts.

Courses taught:

• Introduction to Power Systems
• Power System Analysis
• Power Electronics

Selected Publications:

Eftekharnejad, G.T. Heydt, and V. Vittal., “Optimal Generation Dispatch with High Penetration of Photovoltaic Generation”, IEEE Transactions on Sustainable Energy, Vol 6, Issue 3, pages 1013-1020, July 2015.

Eftekharnejad, V. Vittal, G.T. Heydt, B. Keel, and J. Loehr, “Impact of Increased Penetration of Photovoltaic Generation on Power Systems”, IEEE Transactions on Power Systems, Vol. 28, Issue 2, pages 893 – 901, May 2013.

Eftekharnejad, V. Vittal, G.T. Heydt, B. Keel, and J. Loehr, “Small Signal Stability Assessment of Power Systems with Increased Penetration of Photovoltaic Generation: A Case Study”, IEEE Transactions on Sustainable Energy, Vol. 4, Issue 4, pages 960 – 967, October 2013.

Degree:

• Ph.D. Computer Engineering, Case Western Reserve University

Research Interests:

• Computer Architecture
• Embedded System Design
• System Verification
• VLSI Design Automation

Current Research:

Design automation of embedded processors with extension of super-scalar architectures to exploit inherent thread-level parallelism and instruction-level parallelism at run time within a single chip. Hardware-software interactions in such systems and their applicability to shared-memory systems, and their performance and functional verification.

Courses taught:

• ECS 101 Introduction to Engineering and Computer Science
• CSE 262 Digital System Design and Simulation with VHDL
• CSE 561 Digital Machine Design
• CSE 671 Embedded System Design
• CSE 661 Advanced Computer Architecture
• CSE 765 VLSI Testing and Verification

Selected Publications:

Improving Memory Space Utilization in Multi-core Embedded Systems using Task Recomputation. Koc H, Tosun S, Kandemir M, and Ercanli E, International Journal of Computer Science and Network, Volume 1, Issue 5, pp. 27-34, Oct 2012.

Exploiting Large On-Chip Memory Space Through Data Recomputation, Koc H, Kandemir M, Ercanli E. In Proceedings of the 23rd IEEE International SoC Conference (SOCC 2010), pp. 513-518, Las Vegas, NV, Sept 2010.

An ILP Formulation for Recomputation Based SPM Management for Embedded CMPs. Koc H, Ercanli E, Kandemir M, Ozturk O; In Proceedings of the 5th Workshop on Optimizations for DSP and Embedded Systems (ODES’07). San Jose, CA. Mar 2007.

Reducing Off-Chip Memory Access Costs Using Data Recomputation in Embedded Chip Multi-processors. Koc H, Kandemir M, Ercanli E, Ozturk O; In Proceedings of the 44th Design Automation Conference (DAC’07). San Diego, CA. June 2007. (Ranked #3 in Most Popular Papers Category from ACM Digital Library’s Refereed Journals and Conference Proceedings Downloaded in September 2007).

Compiler-Directed Temporary Array Elimination. Koc H, Ercanli E, Kandemir M, Son SW. The 4th Workshop on Optimizations for DSP and Embedded Systems. NY. Feb 2006.
Minimizing Energy Consumption of Banked Memories Using Data Recomputation. Koc H, Ozturk O, Kandemir M, Narayanan S, Ercanli E. In Proceedings of Intl Symposium on Low Power Electronics and Design (ISLPED’06). Tegernsee, Germany. Oct 2006.

Automated Code Generation For Database Applications. Ercanli E, Ozgencil N, Kahraman MG. The 14th Intl Conference on Intelligent and Adaptive Systems and Software Engineering (ISCA’05). Toronto, Canada, June 2005.

Degree:

• Ph. D. Syracuse University

Lab/Center Affiliation(s):

• Center for Information Systems Assurance and Trust
• Institute for National Security and Counter Terrorism

Research Interests:

• Computer security
• Systems assurance
• Formal verification

Current Research:

Shiu-Kai Chin’s research uses mathematical logic for the design and verification of trustworthy computer systems. Examples of computer systems that must be trustworthy are command and control systems, financial services, and distributed control of the power grid. His focus is on policy-based design and verification with an emphasis on using computer-assisted reasoning using higher-order logic theorem provers.

Shiu-Kai supports the Air Force’s research in trustworthy systems and hardware-based security. His work with JP Morgan Chase was used to reason about the security and integrity of credentials and entitlements in large-value commercial transactions.

Courses Taught:

• Hardware design
• Access control
• Secure computer architecture
• Certified security by design

Honors:

• Provost Faculty Fellow
• Laura J. and L. Douglas Meredith Professor for Teaching Excellence
• Chancellor’s Citation for Outstanding Contributions to the University’s Academic Programs
• 2005 Syracuse University Outstanding Teacher of the Year
• Crouse Hinds Award for Excellence in Education

Selected Publications:

Shiu-Kai Chin, “Teaching Undergraduates Certified Security by Design,” 19th Colloquium for Information Systems Security Education, Las Vegas, NV, June 15-17, 2015.

Glenn Benson, Shiu-Kai Chin, Sean Croston, Karthick Jayaraman, Susan Older, Banking on interoperability: Secure, interoperable credential management, Computer Networks, Volume 67, 2014, pp. 235-251.

Shiu-Kai Chin, Erich Devendorf, Sarah Muccio, Susan Older, and James Royer, “Formal Verification for Mission Assurance in Cyberspace: Education, Tools, and Results,” Proceedings of the 16th Colloquium for Information Systems Security Education, Lake Buena Vista, FL, June 11-13, 2012, pp. 75—82.

Shiu-Kai Chin and Susan Older, Access Control, Security, and Trust: A Logical Approach, CRC Press, 2011.

Shiu-Kai Chin, “Logic Design for Access Control, Security, and Trust,” (Invited Keynote) Engineering of Reconfigurable Systems and Algorithms (ERSA’11) Las Vegas, 18-21 July 2011

Shiu-Kai Chin, Sarah Muccio, Susan Older, and Thomas N. J. Vestal, “Policy-Based Design and Verification for Mission Assurance,” in Igor Kotenko and Victor Skormin (Eds.), Computer Network Security, 5th International Conference on Mathematical Methods, Models and Architectures for Computer Network Security, MMM-ACNS 2010, St. Petersburg, Russia, September 2010.

Glenn Benson, Shiu-Kai Chin, Sean Croston, Karthick Jayaraman, and Susan Older, “Credentials Management for High-Value Transactions,” in Igor Kotenko and Victor Skormin (Eds.), Computer Network Security, 5th International Conference on Mathematical Methods, Models and Architectures for Computer Network Security, MMM-ACNS 2010, St. Petersburg, Russia, September 2010.

Degree(s):

• Ph. D., University of Connecticut

Lab/Center Affiliation(s):

• Communication Laboratory

Research Interests:

• Statistical inference applied to decentralized systems
• Network information theory
• Signal processing for MIMO, multi-user, and multi-carrier communications

Current Research:

My current work focuses on decentralized inference and in particular, how inference functions can impact the value of information in a networked system. Specific topics of interests include the sufficiency principle in the decentralized setting that guides optimal data reduction, the role of feedback and interactive communication in networked inference, and architectural issues in data fusion systems.

Another area of current interest is in characterizing the performance limits of multi-user networks, and in particular the classical interference channel. On the applied side, we have been involved in developing MIMO communication systems for airborne platforms when MIMO channels exhibits rank deficiency due to the lack of scatterers and in developing robust, efficient, and secure software radio systems.

Courses Taught:

• ELE606: Probability
• ELE651: Digital Communications
• ELE751: Wireless Communications
• ELE757: Information Theory

Honors:

• NSF Career Award (2006)
• Finalist, DARPA Spectrum Challenge (2013-2014)
• IEEE Fellow (2015)

Selected Publications:

Akofor and B. Chen,”Interactive distributed detection: architecture and performance analysis,”IEEE Trans. Information Theory. vol. 60, pp.6456-6473, Oct. 2014.

Xu, S. Zhu and B. Chen,”Decentralized data reduction with quantization constraints,”IEEE Trans. Signal Processing, vol. 62, pp. 1775-1784, April 2014.

Chen, B. Chen, and P.K. Varshney,”A new framework for distributed detection with conditionally dependent observations,”IEEE Trans. Signal Processing, vol. 60, pp. 1409-1419, March 2012.

Shang, G. Kramer, and B. Chen,”A new outer bound and the noisy-interference sum-rate capacity for Gaussian interference channels,”IEEE Transactions on Information Theory, vol. 55, pp. 689-699, February 2009.

Chen, R. Jiang, T. Kasetkasem, and P.K. Varshney,”Channel aware decision fusion for wireless sensor networks,”IEEE Trans. Signal Processing, vol. 52, pp. 3454-3458, Dec. 2004.

Degree(s):

• Ph. D., University of Illinois at Urbana-Champaign, 1987

Research Interests:

• VLSI timing analysis and simulation
• Transistor/circuit level power leakage reduction
• Software debugging and verification
• Distributed data sharing and collaboration

Current Research:

A current work that a doctoral student and I are working on is to develop techniques to reduce leakage power of circuits during idle times. Two specific techniques are developed: (1) Leakage power behavior is examined for reordering serially connected transistor blocks. Based on that, we can then determine a primary input vector to a circuit to reduce its leakage power during idle mode. (2) Effect of body bias is studied for nano-scale transistor. A hybrid technique (mixing reverse body bias and forward body bias) is developed to reduce power leakage during idle mode. Another current work that a doctoral student and I are working on is to develop a tool for software debugging and verification. Traditional IDE allows setting of break points, but provides minimum supports in reasoning and bug locating. The goal of this research work is to allow programmers to query various properties of programs and help locating the causes of property violations. Another current work that a doctoral student and I are working on is to design a transistor level circuit simulator, which gives an accuracy near that of SPICE, and can handles much larger circuits in much less run time. Other research work involves distributed data sharing and collaboration, design of platform and protocol for emergency response systems, etc.

Teaching Interests:

• VLSI timing analysis
• VLSI computer-aided design
• Transistor level leakage power reduction
• Multimedia information systems
• Modeling and performance evaluation of computer/communication systems
• Object-oriented databases
• Computer networks
• Parallel/distributed processing
• Computer architecture

Select Publications:

Don P. McGarry, C.Y. Roger Chen.; “IC.NET — Incident Command “Net”: A system using EDXL-DE for intelligent message routing,” 2010 IEEE International Conference on Technologies for Homeland Security (HST), pp. 197 – 203, Nov. 2010.

Jae Woong Chun and C. Y. Roger Chen, A Novel Leakage Power Reduction Technique for CMOS Circuit Design, IEEE International SoC Design Conference (ISOCC), Nov. 1010.

Veerapaneni Nagbhushan, C. Y. Roger Chen: Modeling and reduction of complex timing constraints in high performance digital circuits. IEEE International Conference on Computer Design (ICCD) 2009

Ting-Wei Chiang, C Y Roger Chen and Wei-Yu Chen , “A Technique for Selecting CMOS Transistor Orders,” IEEE International Conference on Computer Design (ICCD), Oct. 2007.

Ting-Wei Chiang, C Y Roger Chen and Wei-Yu Chen, “An Efficient Gate Delay Model for VLSI Design,” IEEE International Conference on Computer Design (ICCD), Oct. 2007.

Degree(s):

• Ph.D. in Electrical and Computer Engineering

Lab/Center Affiliation(s):

Smart Grid Lab

Smart Grid and Power Engineering Lab at Syracuse University has been developed to support teaching and research in contemporary Power Engineering.

• Power Engineering Lab section has been designed for basic and advanced teaching and research in Power Electronics, Sensors & Measurements, Electromechanical Devices, including control systems, communication, and signal processing aspects. The advanced power electronics boards, supported by the real-time interfaces, are equipped for modern undergraduate and graduate level contemporary experimentation in power electronics and electromechanical devices.
• Smart Grid Lab section enables continued development of a multidisciplinary research concept that includes advances in communication and control systems, cyber-security, privacy, and economics. This section consists of the setups for electrical transmission and distribution system, solar and wind energy integration, and synchrophasor measurement technology implementation.
• Smart Home Lab section has been designed for building wired and wireless communication infrastructure and algorithm development for future smart home ideas. The lab is equipped with smart metering infrastructure, providing state-of-the-art environment to our researchers.
• Distant learning concept implementation in Smart Grid Lab has been developed to enable the on-line lectures and student presentations, as well as the distant lab experiment demonstrations.

Research Interests:

• Distributed generation integration and control in electric power microgrid
• Dynamic optimization of microgrid operations and islanding capabilities
• Microgrid secure communication and cybersecurity infrastructure
• Singularity detection and classification and signal segmentation
• Segmentation and motion estimation in time-varying images

Current Research:

• Methodology for the development of sustainable microgrid infrastructure with distributed generation including difficult‑to‑predict renewable energy sources (survey of existing assets, economic feasibility study, technical feasibility study, microgrid design and pre‑deployment parameter validation, on‑site commissioning, post‑deployment metrics validation)
• Microgrid stability and protection challenges (synchrophasor technology implementation for real time monitoring and control, protection schemes coordination with distributed generation, merging challenges of monitoring and protection infrastructure)
• Sustainable microgrid operations by real time load scheduling optimization, using nonlinear and heuristic approaches
• Microgrid cyber secure, distributed, and resilient communication architecture
• Smart metering implementation for demand priority optimization and consumer’s cost reduction with energy availability and signal disaggregation constraints
• Singularity detection and classification and signal segmentation in medical electroencephalography signals for real time epileptic seizure monitoring

Courses Taught:

Power engineering basic and advanced courses in:

• Power electronics
• Electromechanical devices
• Sensors & measurements
• Electric power systems
• Distributed generation integration in smart grid
• Advanced measurements in power engineering
• Microprocessor based power system protection
• Control of distributed generation

Signal processing and applied mathematics basic and advanced courses in:

• Signals & systems
• Digital signal processing
• Functional methods and linear analysis
• Spectral analysis and adaptive filtering
• Wavelets

Supporting teaching courses in:

• Introduction to Electrical Engineering
• Introduction to Smart Grid
• Smart grid: Security, Privacy, & Economy

Professional activities:

• American Society for Engineering Education, St Lawrence Section Conference Co‑Chair, Syracuse, April 17‑18, 2015
• American Society for Engineering Education, St Lawrence Section Chair, 2015

Skills:

• Six-sigma green belt, SUNY-ESF, Syracuse, NY, 2012
• Anti-explosion defense of electrical appliances on over-ground places imperiled from explosive blends, Institute for Nuclear Sciences “Vinca”, Belgrade, Serbia, Yugoslavia, 1995
• Specialist’s examination certificate (the specialist’s examination for engineers dealing with construction projects), Chamber of the Economy of Serbia, Belgrade, Yugoslavia, 1993 (Serbian/Yugoslavian equivalent to Professional Engineer in the USA)

Publications & Presentations:

Arnav Kavadia et al., The Smart Grid: Operational, Privacy, Security & Economic Issues, American Society for Engineering Education, St Lawrence Section Conference, Syracuse, NY, 2015

Tomislav Bujanovic & Prasanta Ghosh, Laboratory Experiments for Enhanced Learning of Electromechanical Devices, American Society for Engineering Education, Zone 1 Conference, Bridgeport, CT, 2014

Tomislav Bujanovic & Ikhlas Abdel-Qader, On Wavelet Transform General Modulus Maxima Metric for Singularity Classification in Mammograms, Open Journal of Medical Imaging, 2013, 3, 17-30

Tomislav Bujanovic et al., Development of Undergraduate Power Engineering Teaching and Learning for future Smart Grid, American Society for Engineering Education, St. Lawrence Section Conference, Buffalo, NY, 2013

Liwen Sun et al., Wavelet Application to Detect Spikes in EEG Signals Due to Epileptic Seizure, IEEE Signal Processing in Medicine and Biology Symposium, New York City, NY, 2012

Degree(s):

• Ph.D. 2001, from Purdue University

Research Interests:

• Computer and network security
• Smartphone and mobile system security
• Security education

Current Research:

Recent work has involved the studies of the Android operating systems with the following goals: (1) identify security problems in the design of the Android operating system, (2) identify security problems in mobile apps and develop tools to detect them, (3) develop improved access control for mobile systems.

Other current work includes the development of effective hands-on lab exercises for security education. We started the work in 2002, and we have developed about 30 labs for both undergraduate and graduate students. As of September 2015, over 350 universities and colleges worldwide are using them.

Courses Taught:

• Computer security
• Internet security
• Android security
• Android Programming

Honors:

• 2014 Dean’s Award for Excellence in Engineering Education, May 2014.
• 2013 Faculty Excellence Award from College of Engineering and Computer Science.
• 2013 ACM CCS Test-of-Time Award.
• Best Paper Award in the 11th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), May 22-25, 2007, Nanjing, China.
• Best Paper Award in The 19th IEEE International Parallel & Distributed Processing Symposium (IPDPS), April 4-8, 2005, Denver, Colorado.
• Guo Mo-ruo Award (1992), University of Science & Technology of China.

Selected Publications:

Click here to see full list of publications.

Yousra Aafer, Nan Zhang, Zhongwen Zhang, Xiao Zhang, Kai Chen, XiaoFeng Wang, Xiaoyong Zhou, Wenliang Du, and Michael Grace. Hare Hunting in the Wild Android: A Study on the Threat of Hanging Attribute References. To appear in the 22nd ACM Conference on Computer and Communications Security (CCS), Denver, Colorado, USA. October 12-16, 2015.

Xing Jin, Xunchao Hu, Kailiang Ying, Wenliang Du, Heng Yin and Gautam Nagesh Peri. Code Injection Attacks on HTML5-based Mobile Apps: Characterization, Detection and Mitigation. In Proceedings of the 21st ACM Conference on Computer and Communications Security (CCS), Scottsdale, Arizona, USA. November 3 – 7, 2014.

Paul Ratazzi, Ashok Bommisetti, Nian Ji, and Wenliang Du. PINPOINT: Efficient and Effective Resource Isolation for Mobile Security and Privacy. In Proceedings of the Mobile Security Technologies (MoST) workshop, May 21, 2015.

Tongbo Luo, Hao Hao, Wenliang Du, Yifei Wang, and Heng Yin. Attacks on WebView in the Android System. In Proceedings of the 27th Annual Computer Security Applications Conference (ACSAC), Orlando, Florida, USA. December 5-9, 2011.

Karthick Jayaraman, Wenliang Du, Balamurugan Rajagopalan, and Steve J. Chapin. Escudo: A Fine-grained Protection Model for Web Browsers. In ICDCS: The 30th International Conference on Distributed Computing Systems, Genoa, Italy, June 21-25, 2010

Wenliang Du. The SEED Project: Providing Hands-on Lab Exercises for Computer Security Education. In IEEE Security and Privacy Magazine, September/October, 2