Engineering and Computer Science Students Attend 2021 ACM Tapia Conference

The Life Sciences Complex at night from above.

Seven students from the College of Engineering and Computer Science attended the 2021 ACM Tapia Conference with help from a STARS Ignite grant awarded to electrical engineering and computer science Professor Farzana Rahman. The ACM Tapia Conference is designed to promote diversity, connect undergraduate and graduate students, faculty, researchers, and professionals in computing from all backgrounds and ethnicities. Before attending the ACM Tapia conference, the student cohort participated in monthly webinar series facilitated by STARS Ignite leadership to mentor students so they can bring the best out of attending diversity conferences, develop value for diversity and inclusiveness in Computing, and contribute to institutional broadening participation activities.

The students had opportunities for workshops and presentations by nationally recognized labs, academic leaders and industry leading companies. A career fair at the conference gave students a chance to meet with recruiters.

“I could have individual meetings with recruiters of different companies in the conference. During meeting with researchers and engineers, I could become more familiar with the culture and projects of companies,” said graduate student Reyhaneh Abdolazimi. “Tapia was also a great opportunity to connect with diverse students from different backgrounds who are looking for job or doing research in the related areas.”

“The early career workshops were very helpful and I was able to connect with some of the presenters to ask about their area of specialization,” said Jemma Mallia ‘23 In many of the career workshops they had a very energetic presenting style that motivated me. Some of the most helpful information included how to optimize my resume, effectively network, seek opportunities, and create opportunities.

“At the Tapia Conference, you can choose the people to speak with. If you choose a recruiter, you may know more about the recruiting process. If you choose a developer, you may know more about the company culture and techniques,” said graduate student Xin Chen.

“I feel as though attending the ACM Tapia conference allowed me to see the diverse paths ahead of me in computing,” said Michael Perry ’22. “I plan to give a talk at our school’s hack-a-thon about broadening participation in computing to hopefully spread the awareness among my community.”

Farzana Rahman

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 21stcentury 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.

Qinru Qiu

Degree(s):

  • Ph.D.

Areas of expertise:

  • Green computing
  • Neuromorphic computing
  • Machine learning
  • Distributed systems
  • Explainable AI

Research Interests:

  • Dynamic power and thermal management for computer systems
  • Power and performance optimization of energy harvesting real-time embedded systems
  • Neuromorphic computing and high performance computing for cognitive applications

Current Research:

Dr. Qinru Qiu received her PhD in Electrical Engineering from the University of Southern California. She is currently a Distinguished Professor in the Department of Electrical Engineering and Computer Science at Syracuse University. Her research interests include neuromorphic computing, machine learning, and energy efficient computing. She served/serves as an associate editor for several IEEE/ACM journals including IEEE TNNLS, IEEE CAS Magazine, IEEE TCDS, IEEE TCAD, IEEE TC-CS, and Frontier on Neuroscience on Neuromorphic Engineering. She also served/serves on the organization committee and technical program committee of many IEEE/ACM conferences. Dr. Qiu is a recipient of the NSF CAREER award in 2009, IEEE Region 1 Technological Innovation award in 2020, ACM Distinguished Member in 2022, and Distinguished Lecturer of the IEEE CEDA Society (2023-2024). She is a Fellow of IEEE.

Courses Taught:

  • VLSI Design
  • Computer architecture

Honors:

  • Distinguished Professor
  • IEEE fellow
  • CEDA Distinguished Lecturer (2023 – 2024)
  • IEEE CAS Magazine Best Associate Editors (2023)
  • Chancellor’s Citation for Faculty Excellence and Scholarly Distinction (2023)
  • IEEE Circuit and System Magazine Best Associate Editors 2022
  • ACM Distinguished Member (2022)
  • IEEE Region 1 Technological Innovation (Academic) Award (2020)
  • ACM Recognition of Service Award (2019)
  • ACM SIGDA Distinguished Service Award (2011)
  • NSF Career Award (2009)
  • American Society for Engineering Education (ASEE) Summer Research Faculty Fellowship (2007)

Selected Publications:

1. B. Wang, Y. Ma, and Q. Qiu, “Prompt-based Domain Incremental Learning with Modular Classification Layer,” European Conference on Artificial Intelligence (ECAI), 2024.

2. N. Lin, J. Chen, R. Zhao, Y. He, K. Wong, Q. Qiu, Z. Wang, J J. Yang, “In-memory and in-sensor reservoir computing with memristive devices,” APL Machine Learning, 2024.

3. J. Liu, Y. Bu, and Q. Qiu, “Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling,” International Conference on Learning Representations (ICLR), 2024.

4. Z. Zhang, J. Jing, and Q. Qiu, “SOLSA: Neuromorphic Spatiotemporal Online Learning for Synaptic Adaptation,” to appear on 29th Asia and South Pacific Design Automation Conference (ASP-DAC), 2024.

5. Y. Bu, J. Liu, and Q. Qiu, “Predictive Temporal Attention on Event-based Video Stream for Energy-efficient Situation Awareness,” International Green and Sustainable Computing (IGSC), 2023.

6. Q. Huang, C. Luo, S. Khan, A. B. Wu, H. Li, and Q. Qiu, “Multi-agent Cooperative Games Using Belief Map Assisted Training,” European Conference on Artificial Intelligence (ECAI), 2023.

Vir V. Phoha

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 and Awards:

  • Fellow of: AAAS; AAIA; IEEE; NAI; SDPS 
  • ACM Distinguished Scientist 
  • IEEE Computer Society Distinguished Visitor (2024-2026) 
  • ACM Distinguished Speaker (2012-2015) 
  • IEEE Region 1 Technological Innovation  Award, 2017 

Selected Publications:

  • F. Chen, J. Xin and V. V. Phoha, “SSPRA: A Robust Approach to Continuous Authentication Amidst Real-World Adversarial Challenges,” in IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 6, no. 2, pp. 245-260, April 2024, doi: 10.1109/TBIOM.2024.3369590 
  • Jingyu Xin, Vir V. Phoha, and Asif Salekin. 2022. Combating False Data Injection Attacks on Human-Centric Sensing Applications. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 2, Article 83 (July 2022), 22 pages. https://doi.org/10.1145/3534577 
  • Xinyi Zhou, Kai Shu, Vir V. Phoha, Huan Liu, and Reza Zafarani. 2022. “This is Fake! Shared it by Mistake”:Assessing the Intent of Fake News Spreaders. In Proceedings of the ACM Web Conference 2022 (WWW ’22). Association for Computing Machinery, New York, NY, USA, 3685–3694. https://doi.org/10.1145/3485447.3512264 
  • Fallahi, A., Phoha, V.V. (2021). Adversarial Activity Detection Using Keystroke Acoustics. In: Bertino, E., Shulman, H., Waidner, M. (eds) Computer Security – ESORICS 2021. ESORICS 2021. Lecture Notes in Computer Science(), vol 12972. Springer, Cham. https://doi.org/10.1007/978-3-030-88418-5_30 
  • Xinyi Zhou, Atishay Jain, Vir V. Phoha, and Reza Zafarani. 2020. Fake News Early Detection: A Theory-driven Model. ACM Digital Threats 1, 2, Article 12 (June 2020), 25 pages. https://doi.org/10.1145/3377478 
  • B. Li, W. Wang, Y. Gao, V. 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. 

Susan Older

Degrees:

  • B.S. in Computer Science, Washington University
  • Ph.D. in Pure & Applied Logic, Carnegie Mellon University

Research Interests:

  • Semantics of programming languages
  • Logics of programs
  • Access control, security, and trust
  • Concurrency theory

Current Research:

My research primarily focuses on the development and application of mathematical models and specialty logics that support reasoning about complex system behavior, such as concurrency and cyber security. My recent work (joint with Shiu-Kai Chin) has centered on a modal logic for reasoning about access control, security, and trust. This logic can be applied at all levels of abstraction, from organizational policies to network protocols to operating-system requirements to hardware.

I am also interested in the technology transfer of these ideas (specifically, through undergraduate and graduate education): how does one best enable budding engineers and computer scientists to deploy these methods to develop assured systems?

Courses Taught:

  • Discrete mathematics
  • Functional programming
  • Programming languages
  • Applications of formal methods for assurance

Selected Publications:

Textbook

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

Articles

Susan Older and Shiu-Kai Chin, “Engineering Assurance at the Undergraduate Level,” IEEE Security & Privacy, Volume 10, Number 6, pages 74-77, Nov/Dec 2012.

Shiu-Kai Chin, Erich Devendorf, Sarah Muccio, Susan Older, and James Royer, “Formal Verification for Mission Assurance in Cyberspace,” Proceedings of the 16th Colloquium for Information Systems Security Education, Orlando, Florida, June 2012.

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), St. Petersburg, Russia, September 2010.

Jae C. Oh

Degree(s):

  • Ph.D in Computer Science, The University of Pittsburgh

Lab/Center Affiliation(s):

  • Distributed Multi-agent Systems Laboratory (Director)

Areas of Expertise:

  • Distributed systems, multi-agent systems, Game Theory, and Symbolic and Non-Symbolic AI.
  • Studying Interaction dynamics among multiple entities in networked and non-networked environments.

I am interested in studying interaction dynamics among multiple entities in networked and non-networked environments, resource allocation and management in distributed environments, dialogical artificial intelligence, and studies on visual dialogues and visual art.

Honors and Awards:

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

Selected Publications:

Nathaniel Gemelli, Jeffrey Hudack, Steven Loscalzo and Jae Oh, “”Using Coalitions with Stochastic Search to solve Distributed Constraint Optimization Problems,” in Proceedings of the 7th International Conference on Agents and Artificial Intelligence. 2015

A Game Theoretic Framework for Community Detection, The 2012 IEEE/ACM International Conference in Social Networks Analysis and Mining, ASONAM 2012. Best Paper Award. with K. Mehrotra and P. McSweeny

An Open Co-op Model for Global Enterprise Technology Education: Integrating the Internship and Course Work. SIGCSE 2012. With J. Saltz.

Joo Lee and Jae C. Oh, A Node-Centric Reputation Computation Algorithm on Online Social Networks, in Lecture Notes in Social Networks: Application of Social Media and Social Network Analysis, Springer International Publishing, Eds:, Kazienko, Przemyslaw and Chawla, Nitesh, Pages 1-22.

Jae C. Oh, Emergence of self-reflection through visual dialogues based on evolutionary algorithms,” a description of Informatrix III from a computer science perspective, in the Art Catalogue of 14th International Festival of Intermedia Art, Maribor, Solvenia, October 13, 2008, English), ISBN 978-961-6154-19-2, an Art Catalogue

Wonkyung Park and Jae C. Oh, \New Entropy Model for Extraction of Structural Information from XCS Population,” Proceedings of the Genetic and Evolutionary Computation Conference 2009 (GECCO 2009), July, Montreal, Canada, ACM, Best paper award.

Chilukuri K. Mohan

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

Areas of Expertise:

  • Neural Networks
  • Evolutionary Algorithms
  • Bioinformatics
  • Reinforcement Learning
  • Anomaly Detection

Prof. Mohan has been conducting research on neural network algorithms and applications since 1990.  He has also been a long-term contributor to the field of Evolutionary Algorithms, including Genetic Algorithms and Particle Swarm Optimization.  He collaborates actively with researchers in the sciences, particularly on Bioinformatics research.  His prior research also includes automated reasoning, network science, and anomaly detection algorithms (with financial and cybersecurity applications).  His group’s current research topics include the automated design of objects (optimizing desired properties), the analysis of behaviors of autonomous individuals in networks, explainable reinforcement learning using Learning Classifier Systems, and code stylometry (to detect authorship). 

Honors:

  • IEEE Region 1 Technological Innovation (Academic) Award (“For development of novel algorithms in computational intelligence”), 2019 
  • Distinguished Scholar Award, International Society of Applied Intelligence, July 2011.

Selected Publications:

Books: 

  • Anomaly Detection Principles and Algorithms (K. Mehrotra, C. K. Mohan, and H. Huang), Springer, 2017 
  • Frontiers of Expert Systems: Reasoning with limited knowledge (C. K. Mohan), Kluwer, 2000 
  • Elements of Artificial Neural Networks (K. Mehrotra, C.K. Mohan and S. Ranka), MIT Press, 1997 

Recent Papers: 

  • “Structural Optimization with Isogeometric Representation using an Evolutionary Approach” (S. Kalia, N. Padhye, and C. Mohan), in Proc. Genetic and Evolutionary Computation Conference (GECCO), 2024. 
  • “Learning-Based Resource Management in Integrated Sensing and Communication Systems” (Z. Lu, M.C. Gursoy, C. Mohan, and P. Varshney), IEEE Conference on Computer Communications (INFOCOM) Workshop, 2024. 
  • “Accelerating Quantum Chemistry Calculations: Machine Learning for Efficient Evaluation of Electron-Repulsion Integrals” (N. Rodrigues, N. Spanedda, C. Mohan, and A. Chakraborty),  International Journal of Nuclear and Quantum Engineering, 18(3), 2024. 
  • “Dictionary Attack on IMU-based Gait Authentication” (R. Kumar, C. Isik, and C. Mohan), Proceedings of the 16th ACM Workshop on Artificial Intelligence and Security, 2023. 

Joao Paulo Marum

Degrees: 

Ph.D. in Computer Science – University of Mississippi (2021)

Areas of Expertise:

  • Programming Languages
  • Software Engineering
  • Augmented Reality
  • Virtual Reality

My research is focused in using multi-paradigm programming to solve accuracy issues on User Interactive System, especially in Virtual and Augmented Reality.  This research uses dependency relationships between loosely coupled components. We use techniques of Functional Reactive Programming and Change Propagation to identify how a change may cause additional modification in other several components and force the systems to wrap all these modification in a single update cycle. This research resulted in a design pattern that was applied into User Interfaces, Virtual Reality and it can be applied on many other research fields. I am also currently interested in research about CS Education and Accessibility technologies especially focused on education and autonomy.

Honors and Awards:

Dissertation Fellowship Award, University of Mississippi, 2019.

Outstanding Doctoral Student Award, University of Mississippi, 2021.

Order of Engineer inductee, School of Engineering. University of Mississippi. 2021.

Pledge of Computing Professional inductee, School of Engineering. University of Mississippi. 2021.

Upsilon Pi Epsilon inductee, School of Engineering. University of Mississippi. 2021.

IEEE Computer Science Society Professional Member. IEEE. 2021.

IEEE Education Society Professional Member. IEEE. 2021.

ACM SIGSOFT (Special Interest Group – Software Engineering) Professional Member. ACM. 2021

ACM SIGCSE (Special Interest Group – Computer Science Education) Professional Member. ACM. 2021

ACM SIGCHI (Special Interest Group – Computer-Human Interaction) Professional Member. ACM. 2021

Brazilian Computing Society (SBC) Professional Honor Member. SBC. 2021.

Selected Publications:

Joao Paulo O. Marum, J. Adam Jones, and H. Conrad Cunningham (2019), Towards a reactive game engine, in Proceedings of the 50th IEEE SouthEastCon, IEEE, Huntsville, AL, USA.

Joao Paulo O. Marum, H. Conrad Cunningham, and J. Adam Jones (2020), Unified library for dependency graph reactivity on web and desktop user interfaces, in Proceedings of the ACM Southeast Conference (ACMSE 2020), ACM, Tampa, FL, USA

Joao Paulo O. Marum, J. Adam Jones, and H. Conrad Cunningham (2020), Dependency graph-based reactivity for virtual environments, in Proceedings of the IEEE VR 2020 Workshop on Software Engineering and Architectures for Interactive Systems (SEARIS), IEEE, Atlanta, GA, USA.

Jean-Daniel Medjo Me Biomo

Education:

       Ph.D., Electrical and Computer Engineering, Carleton University

       M.A.Sc., Electrical and Computer Engineering, Carleton University

       B.Eng., Electrical Engineering, Polytechnique Montreal

Areas of Expertise:

Routing protocols

Medium access control protocols

Wireless ad hoc networks

Unmanned aerial vehicles’ networks

LEO satellite networks

My research has focused on wireless ad hoc networks, especially the mobile/flying ones. I specialize in the design of routing protocols (Network layer) and medium access control (MAC) protocols (Link layer) for such networks, with the goal of increasing the packet delivery ratio and reducing the end-to-end packet delay/latency while keeping a low overhead. I am interested in integrating artificial intelligence (deep learning, reinforcement learning) in the design. Some applications networks are networks of unmanned aerial vehicles (UAV/drones) and networks of LEO satellites.

Selected Publications:

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “A Novel Routing Protocol for Reducing Packet Latency with Multi-Beam Antennas,” in Computer Networks, Vol. 220, 2023.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “MBA-DbMAC: A random-access MAC protocol for MBAs,” in Proceedings of the 11th EAI International Conference on Ad Hoc Networks (AdHocNets 2019), Queenstown, New Zealand, November 2019.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “Exploiting multi-beam antennas for end-to-end delay reduction in ad hoc networks,” in Mobile Networks and Applications, Vol. 23, No. 5, pages 1293-1305, October 2018.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, Marc St-Hilaire, “Exploiting multiple beam antennas for end-to-end delay reduction in ad hoc networks,” in Proceedings of the 9th EAI International Conference on Ad Hoc Networks, Niagara Falls, Canada, September 2017.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “Directional antennas in FANETs: A performance analysis of routing protocols,” in Proceedings of the Sixth International Conference on Selected Topics in Mobile & Wireless Networking (MoWNet’17), Avignon, France, May 2017.

Thomas Kunz, Jean-Daniel Medjo Me Biomo, and Marc St-Hilaire, “NetAnalyzer: Analyzing dynamic network topologies,” in Proceedings of the 8th IEEE-IFIP Wireless and Mobile Networking Conference (WMNC 2015), pp. 64-71, Munich, Germany, October 2015.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, Marc St-Hilaire, and Yifeng Zhou, “Unmanned aerial ad hoc networks: Simulation-based evaluation of entity mobility models impact on routing performance,” in Aerospace Journal, special issue on Unmanned Aerial Systems (UAS), Vol. 2, No. 3, pp. 392-422, June 2015.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “An enhanced Gauss-Markov mobility model for simulations of Unmanned Aerial Ad hoc networks,” in Proceedings of the 7th IEEE-IFIP Wireless and Mobile Networking Conference (WMNC 2014), pp. 1-8, Vilamoura, Portugal, May 2014.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “Routing in Unmanned Aerial Ad hoc networks: Introducing a route reliability criterion,” in Proceedings of the 7th IEEE-IFIP Wireless and Mobile Networking Conference (WMNC 2014), pp. 1-7 , Vilamoura, Portugal, May 2014.

Jean-Daniel Medjo Me Biomo, Thomas Kunz, and Marc St-Hilaire, “Routing in unmanned aerial ad hoc networks: A recovery strategy for greedy geographic forwarding failure,” in Proceedings of the IEEE Wireless Communications and Networking Conference (WCNC 2014), pp. 2236-2241, Istanbul, Turkey, April 2014.

Kristopher Micinski

Degree:

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

Areas of Expertise:

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

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).

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).

Andrew C. Lee

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).

Areas of Expertise:

  • Theory of Computing
  • Graphs and Combinatorics
  • Computer Science Education
  • History of Computing

I am interested in investigating, via mathematical means, the resources used (e.g., time, memory, no. of queries etc.) and the strategies required for solving problems that arise within a computing (e.g., machine learning etc.) context. In my prior studies, I used methods from mathematical logic (e.g., compatibility theory), discrete mathematics (e.g., combinatorial and algorithmic methods for graphs) and automata (e.g., omega automata) in my investigation. I am also interested in incorporating and integrating my expertise in computer science education (e.g. curriculum design and development, undergraduate research etc.) and, in the interplay between the history of computing and education where I find them crucial in educating future computing professionals and scientists. Regarding undergraduate research, some solution strategies formulated in my work are of interest to our students for studying concrete games, questionnaire design and in data analytic applications.

Courses Taught:

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

Selected Publications:

  1. William I. Gasarch and Andrew C. Y. Lee, On the finiteness of the recursive chromatic number, Annals of Pure and Applied Logic, 93 (1998) 73-81.
  2. Andrew C. Lee, On an application of graph theory to formal learning theory, Congressus Numerantium (160): 183-192, 2003.
  3. Andrew C. Lee, Learning via finitely many queries, Annals of Mathematics and Artificial Intelligence, 44 (4), 401-418, 2005.
  4. Andrew C. Lee, A connection between learning models and secret guessing games, Congressus Numerantium (175): 65-72, 2005
  5. William I. Gasarch and Andrew C. Y. Lee, Inferring answers to queries, Journal of Computer and System Sciences 74 (2008) 490–512.
  6. 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.

Bryan S. Kim

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

Areas of Expertise:

  • File and storage systems
  • Computer architecture
  • Operating systems

I am broadly interested in computer systems and particularly focused on data storage systems. System qualities that I care about are performance (how to store and retrieve data fast as hardware scaling stops), reliability (how to ensure the correctness as hardware becomes more error-prone), and scalability (how to scale a system as heterogeneity increases).

Recent Publications:

  • Ziyang Jiao, Xiangqun Zhang, Hojin Shin, Jongmoo Choi, and Bryan S. Kim. The Design and Implementation of a Capacity-Variant Storage System. In USENIX Conference on File and Storage Technologies (FAST), pages 159–176, Feb. 2024
  • Shao-Peng Yang, Minjae Kim, Sanghyun Nam, Juhyung Park, Jin-yong Choi, Eyee Hyun Nam, Eunji Lee, Sungjin Lee, and Bryan S. Kim. Overcoming the Memory Wall With CXL-Enabled SSDs. In USENIX Annual Technical Conference (ATC), pages 601–617, July 2023
  • Jinhyung Koo, Jinwook Bae, Minjeong Yuk, Seonggyun Oh, Jung-Soo Park, Eunji Lee, Bryan S. Kim, and Sungjin Lee. All-Flash Array Key-Value Cache for Large Objects. In Proceedings of the European Conference on Computer Systems (EuroSys), pages 784–799, May 2023
  • Manoj P. Saha, Adnan Maruf, Bryan S. Kim, and Janki Bhimani. KV-SSD: What Is It Good For? In Proceedings of ACM/IEEE Design Automation Conference (DAC), pages 1105–1110, Dec. 2021
  • Junsu Im, Jooyoung Song, Juhyung Park, Eunji Lee, Bryan S. Kim, and Sungjin Lee. Modernizing File System Through In-Storage Indexing. In Proceedings of USENIX Symposium on Operating Systems Design and Implementation (OSDI), pages 75–92, July 2021
  • Bryan S. Kim, Jongmoo Choi, and Sang Lyul Min. Design Tradeoffs for SSD Reliability. In Proceedings of USENIX Conference on File and Storage Technologies (FAST), pages 281–294, Feb. 2019
  • Bryan S. Kim, Hyun Suk Yang, and Sang Lyul Min. AutoSSD: an Autonomic SSD Architecture. In Proceedings of USENIX Annual Technical Conference (ATC), pages 677–689, July 2018
  • Bryan S. Kim and Sang Lyul Min. QoS-aware Flash Memory Controller. In IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS), pages 51–62, Apr. 2017

Garrett Ethan Katz

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

Areas of Expertise:

  • Automated Planning and Reasoning
  • Robotic Manipulation and Imitation Learning
  • Neuro-Symbolic Programming
  • Numerical Path Following and Optimization

Current Research:

My research focuses on “vertically integrated” artificial intelligence, ranging from low-level robotic motor control and synaptic learning rules to high-level planning and abstract reasoning. My recent work has focused on single-pass learning, automated algorithm discovery, and neuro-symbolic robotic control.

Honors and Awards:

  • Best Paper Award at the 18th International Conference on Augmented Cognition at HCII, 2024
  • Best Paper Award at the SAI Computing Conference, 2020
  • Larry S. Davis Doctoral Dissertation Award, UMD, 2018
  • Best Student Paper Award at the 9th International Conference on Artificial General Intelligence 2016

Selected Publications:

  • Liu R, He B, Tahir N, Katz GE. On the Feasibility of Single-Pass Full-Capacity Learning in Linear Threshold Neurons with Binary Input Vectors. In Forty-first International Conference on Machine Learning (ICML). 2024. PMLR.
  • Katz GE, Tahir N. Towards Automated Discovery of God-Like Folk Algorithms for Rubik’s Cube. In 2022 AAAI Conference on Artificial Intelligence. AAAI.
  • Katz GE, Akshay, Davis GP, Gentili RJ, Reggia JA. Tunable Neural Encoding of a Symbolic Robotic Manipulation Algorithm. Frontiers in Neurorobotics. 2021:167.
  • Tahir N, Katz GE. Numerical Exploration of Training Loss Level-Sets in Deep Neural Networks. In 2021 International Joint Conference on Neural Networks (IJCNN) 2021 (pp. 1-8). IEEE.
  • Katz GE, Reggia JA. Using directional fibers to locate fixed points of recurrent neural networks. IEEE Transactions on Neural Networks and Learning Systems. 2017 Aug 24;29(8):3636-46.

Can Isik

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

Areas of Expertise:

  • Artificial Intelligence Applications
  • Controls, Modeling, Decision Making
  • Medical Instrumentation
  • Indoor Environmental Systems

Dr. Isik utilizes analytical and artificial intelligence methods to engineering applications in controls, system modeling, signal processing and instrumentation.

Courses Taught:

  • Introduction to ECS, Signals and Systems, Controls, Probability and Statistics 

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:

R Kumar, C Isik, C Mohan, Dictionary Attack on IMU-based Gait Authentication, The 16th ACM Workshop on Artificial Intelligence and Security (AISec 2023)

R Kumar, C Isik, VV Phoha, “Treadmill Assisted Gait Spoofing (TAGS): An Emerging Threat to Wearable Sensor-based Gait Authentication”, ACM Journal of Digital Threats: Research and Practice, Article No.: 23, pp 1–17, July 2021

PK Bera, C Isik, “A Data Mining Based Protection and Classification of Transients for Two-Core Symmetric Phase Angle Regulators”, IEEE Access Journal 9, 72937-72948, 2021

PK Bera, C Isik, V Kumar, “Discrimination of Internal Faults and Other Transients in an Interconnected System With Power Transformers and Phase Angle Regulators”, IEEE Systems Journal, VOL 15, ISSUE 3, PP. 3450-3461 July 2020

Endadul Hoque

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

Lab/ Center/ Institute affiliation

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 and Awards:

  • NSF CAREER Award, 2024
  • Google Research Scholar Award, 2022
  • 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

Selected Publications:

  • A. J. Nafis, O. Chowdhury, and E. Hoque, “VetIoT: On Vetting IoT Defenses Enforcing Policies at Runtime,” Proc. of IEEE Conference on Communications and Network Security (CNS) pp. 1-9, 2023.
  • M. H. Mazhar, L. Li, E. Hoque, and O. Chowdhury, “MAVERICK: An App-independent and Platform-agnostic Approach to Enforce Policies in IoT Systems at Runtime,” Proc. of ACM Conference on Security and Privacy in Wireless and Mobile Networks (WiSec ’23), 2023.
  • M. Yahyazadeh, S. Y. Chau, L. Li, M. H. Hue, J. Debnath, S. C. Ip, C. N. Li, E. Hoque, and O. Chowdhury, “Morpheus: Bringing The (PKCS) One To Meet the Oracle,” Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS ’21) (CCS ’21), Association for Computing Machinery, New York, NY, USA, pp. 2474–2496, 2021.
  • M. H. Hue, J. Debnath, K. M. Leung, L. Li, M. Minaei, M. H. Mazhar, K. Xian, E. Hoque, O. Chowdhury, and S. Y. Chau, “All Your Credentials Are Belong to Us: On Insecure WPA2-Enterprise Configurations,” Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security (CCS ’21), Association for Computing Machinery, New York, NY, USA, pp. 1100–1117, 2021.

M. Cenk Gursoy

Degree(s):

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

Lab/ Center/ Institute Affiliations:

Director, Wireless Communication and Networking Lab.

Senior Research Associate and Core Faculty Member, Autonomous Systems Policy Institute

Areas of Expertise:

Wireless Networking

Signal Processing

Communication/Information Theory

Machine Learning

Decision Making Theory

Optimization

Unmanned Systems

Dr. Gursoy has broad research expertise in the general areas of wireless communications and networking, signal processing, information theory, optimization, and machine learning. In particular, he has conducted research in detection and estimation, hypothesis testing, anomaly detection, optimal resource allocation, wireless performance evaluation, cognitive radio networks, dynamic spectrum access, energy efficiency analysis, multiple-antenna communication, millimeter wave communications, low-latency communications, physical-layer security, radio access networks, scheduling, edge computing, content caching, and 4G/5G/beyond-5G wireless network design. His expertise in information theory includes the analysis of wireless channel capacity and optimal signaling and coding schemes. He further has expertise in machine learning through the design, implementation and application of deep learning, reinforcement learning, and federated learning algorithms. Moreover, he has studied sequential optimization and decision-making in highly dynamic scenarios (involving autonomous and unmanned systems), and security and privacy in distributed learning.

Honors and Awards:

  • 2020 IEEE Region 1 Technological Innovation (Academic) Award
  • 2019 The 38th AIAA/IEEE Digital Avionics Systems Conference Best of Session    Award.
  • 2017 IEEE Green Communications & Computing Technical Committee Best Journal Paper Award.
  • 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) Best Paper Award
  • 2008 EURASIP Journal of Wireless Communications and Networking Best Paper Award
  • NSF CAREER Award

Selected Publications:

  • G. Joseph, C. Zhong, M. C. Gursoy, S. Velipasalar, and P. K. Varshney, “Anomaly Detection via Learning-Based Sequential Controlled Sensing,” IEEE Sensors Journal, vol. 24, no. 13, pp. 21025-21037, July 2024.
  • F. Wang, M. C. Gursoy, and S. Velipasalar, “Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, pp. 823-840, 2024.
  • M. H. Sulieman, M. Liu, F. Kong, and M. C. Gursoy, “Path Planning for UAVs Under GPS Permanent Faults,” ACM Transactions on Cyber-Physical Systems, 2024.
  • X. Li, Z. Tian, W. He, G. Chen, M. C. Gursoy, S. Mumtaz, and A. Nallanathan, “Covert Communication of STAR-RIS Aided NOMA Networks,” IEEE Transactions on Vehicular Technology, vol. 73, no. 6, pp. 9055-9060, June 2024.
  • Y. Yang, Y. Hu, and M. C. Gursoy, “Energy Efficiency of RIS-Assisted NOMA-Based MEC Networks in the Finite Blocklength Regime,” IEEE Transactions on Communications, vol. 72, no. 4, pp. 2275-2291, April 2024.
  • F. Wang, M. C. Gursoy, and S. Velipasalar, “Robust Network Slicing: Multi-Agent Policies, Adversarial Attacks, and Defensive Strategies,” IEEE Transactions on Machine Learning in Communications and Networking, vol. 2, pp. 49-63, 2024.
  • Y. Yang and M. C. Gursoy, “Joint Trajectory Design and Resource Optimization in UAV-assisted Caching-Enabled Networks with Finite Blocklength Transmissions,” Drones, 2024; 8(1):12.
  • Z. Lu and M. C. Gursoy, “Resource Allocation for Multi-target Radar Tracking via Constrained Deep Reinforcement Learning,” IEEE Transactions on Cognitive Communications and Networking, vol. 9, no. 6, pp. 1677-1690, Dec. 2023.
  • G. Joseph, C. Zhong, M. C. Gursoy, S. Velipasalar, and P. K. Varshney, “Scalable and Decentralized Algorithms for Anomaly Detection via Learning-Based Controlled Sensing,” IEEE Transactions on Signal and Information Processing over Networks, vol. 9, pp. 640-654, 2023.
  • X. Wang and M. C. Gursoy, “Resilient Path Planning for UAVs in Data Collection Under Adversarial Attacks,” in IEEE Transactions on Information Forensics and Security, vol. 18, pp. 2766-2779, 2023.
  • M. Guo and M. C. Gursoy, “Joint Activity Detection and Channel Estimation for Intelligent-Reflecting-Surface-Assisted Wireless IoT Networks,” in IEEE Internet of Things Journal, vol. 10, no. 12, pp. 10207-10221, June, 2023.
  • Y. Zhu, X. Yuan, Y. Hu, T. Wang, M. C. Gursoy and A. Schmeink, “Low-Latency Hybrid NOMA-TDMA: QoS-Driven Design Framework,” in IEEE Transactions on Wireless Communications, vol. 22, no. 5, pp. 3006-3021, May 2023.
  • Y. Zhu, Y. Hu, X. Yuan, M. C. Gursoy, H. V. Poor and A. Schmeink, “Joint Convexity of Error Probability in Blocklength and Transmit Power in the Finite Blocklength Regime,” in IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2409-2423, April 2023.
  • Y. Shi, Y. E. Sagduyu, T. Erpek and M. C. Gursoy, “How to Attack and Defend NextG Radio Access Network Slicing with Reinforcement Learning,” IEEE Open Journal of Vehicular Technology, vol. 4, pp. 181-192, 2023.
  • D. Deng, X. Li, S. Dang, M. C. Gursoy and A. Nallanathan, “Covert Communications in Intelligent Reflecting Surface-Assisted Two-Way Relaying Networks,” IEEE Transactions on Vehicular Technology, vol. 71, no. 11, pp. 12380-12385, Nov. 2022
  • X. Wang, M. C. Gursoy, T. Erpek, and Y. E. Sagduyu, “Learning-Based UAV Path Planning for Data Collection with Integrated Collision Avoidance,” IEEE Internet of Things Journal, vol. 9, no. 17, pp. 16663-16676, Sep. 2022.
  • X. Wang and M. C. Gursoy, “Learning-Based UAV Trajectory Optimization with Collision Avoidance and Connectivity Constraints,” IEEE Transactions on Wireless Communications, vol. 21, no. 6, pp. 4350-4363, Jun. 2022.
  • Z. Lu, C. Zhong, and M. C. Gursoy, “Dynamic Channel Access and Power Control in Wireless Interference Networks via Multi-Agent Deep Reinforcement Learning,” IEEE Transactions on Vehicular Technology, vol. 71, no. 2, pp. 1588-1601, Feb. 2022.
  • Z. Xu, J. Tang, C. Yin, Y. Wang, G. Xue, J. Wang, M. C. Gursoy, “ReCARL: Resource Allocation in Cloud RANs with Deep Reinforcement Learning,” EEE Transactions on Mobile Computing, vol. 21, no. 7, pp. 2533-2545, Jul. 2022
  • M. Guo and M. C. Gursoy, “Joint Activity Detection and Channel Estimation in Cell-Free Massive MIMO Networks with Massive Connectivity,” IEEE Transactions on Communications, vol. 70, no. 1, pp. 317-331, Jan. 2022.
  • H. Huang, D. Qiao and M. C. Gursoy, “Age-Energy Tradeoff Optimization for Packet Delivery in Fading Channels,” IEEE Transactions on Wireless Communications, vol. 21, no. 1, pp. 179-190, Jan. 2022.
  • F. Wang, C. Zhong, M. C. Gursoy, and S. Velipasalar, “Resilient Dynamic Channel Access via Robust Deep Reinforcement Learning,” IEEE Access, vol. 9, pp. 163188-163203, 2021.
  • P. Sinha, I. Guvenc, and M. C. Gursoy, “Fundamental Limits on Detection of UAVs by Existing Terrestrial RF Networks,” IEEE Open Journal of the Communications Society, vol. 2, pp. 2111-2130, 2021
  • X. Wang and M. C. Gursoy, “Uplink Coverage in Heterogeneous mmWave Cellular Networks with Clustered Users,” IEEE Access, vol. 9, 2021.
  • M. Guo and M. C. Gursoy, “Statistical Learning Based Joint Antenna Selection and User Scheduling for Single-Cell Massive MIMO Systems,” IEEE Transactions on Green Communications and Networking, vol. 5, no. 1, pp. 471-483, March 2021

Jennifer W. Graham

Electromagnetic, complex media, antenna design and modeling

Education:

  • B.S.E.E Syracuse University, 2000
  • M.S.E.E. Syracuse University, 2004
  • Ph.D. Syracuse University, 2012

Current Research:

My current research includes understanding the behavior of electromagnetic waves in complex media specifically anisotropic media. I have studied biaxially anistropic media with the most depth including wave propagation and reflection and transmission.

I also have research interest in antennas including antenna modeling and measurement. I have combined research areas by modeling microstrip antennas printed on biaxially anisotropic substrates.

Courses taught:

  • ECS 101:  Introduction to Engineering and Computer Science
  • ELE 331:  Digital Circuits and Systems
  • ELE 333:  Analog Circuits
  • ELE 621:  Electromagnetic Fields
  • ELE 623:  Microwave Measurements
  • ELE 722:  Microwave Filters
  • ELE 726:  Computational Methods of Field Theory

Selected Publications:

J.W. Graham, J.K. and Lee, “Electromagnetic Waves in Biaxially Anisotropic Media,” Wiley Encyclopedia of Electrical and Electronics Engineering. 1–15 2015.

J.W. Graham and J. K. Lee, “Reflection and Transmission from Biaxially Anisotropic-Isotropic Interfaces,” Progress in Electromagnetic Research, PIER 136, 681-702, 2013.

J.W. Graham and J. K. Lee, “Rectangular Patch Antennas on Biaxial Substrates,” IEEE International Symposium on Antennas and Propagation, Orlando, FL July 2013.

J.W. Graham and J. K. Lee, “Microstrip Dipoles Printed on Biaxial Substrates,” IEEE International Symposium on Antennas and Propagation, Chicago, IL July 2012.

J.W. Graham and J. K. Lee, “Reflection and Transmission at Isotropic-Biaxial Interface,” URSI General Assembly and Scientific Symposium, Istanbul, Turkey, August 2011.

J.W. Graham, G. F. Pettis, and J. K. Lee, “Symmetrical Property of Dyadic Green’s Functions for Layered Anisotropic Medium,” IEEE International Symposium on Antennas and Propagation/URSI National Radio Science Meeting, Toronto Ontario, Canada, July 2010.

Nadeem Ghani

Areas of Expertise:

Human Vision and Psychophysics

Neurophysiology

Human Factors

Software Engineering and Design

Multi-disciplinary approaches to problems like GUI design and visualizations. Biology inspired computing.

Prasanta K. Ghosh

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.

Venkata S.S. Gandikota

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

Lab/ Center/ Institute affiliation:

Areas of Expertise:

  • Foundations of Data Science
  • Coding & Information Theory
  • Lattice Algorithms

Dr. Gandikota’s research delves into the algorithmic principles of data recovery from noise, with an emphasis on its applications in fundamental machine learning problems. His primary objective is to delineate the conditions that enable successful data recovery while also devising efficient algorithms to achieve it.

Honors and Awards:

  • IEEE Senior Member
  • SOURCE RA Grant.
  • CUSE Seed Grant.

Selected Publications:

Makan Fardad

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

Areas of Expertise:

  • Convex optimization
  • Complex networks
  • Dynamical systems
  • Control theory

Makan Fardad has expertise in convex optimization and its applications in the areas of distributed control, signal processing, and social networks.

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.

Sara Eftekharnejad

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.

Ehat Ercanli

Degree:

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

Research Interests:

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

Areas of Expertise:

  • Embedded System Design
  • Computer Architecture
  • Database Systems
  • Design Automation
  • System Verification and Testing

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.
  • A Register File and Scheduling Model for Application Specific Processor Synthesis. Ercanli E, Papachristou C. The 33rd IEEE/ACM Design Automation Conference (DAC’96), Las Vegas, NV, June 1996.
  • A Research Database For Improved Data Management And Analysis In Longitudinal Studies. Bielefeld R, Yamashita T, Kerekes E, Ercanli E, Singer L.  M.D. Computing. Vol. 12. NO. 3. 1995.
  • Custom Processor Design for Image Processing Applications. Ercanli E, Papachristou C. The 10th International Symposium on Computer and Information Sciences (ISCIS’95). Sept 1995.

Shiu-Kai Chin

Degree:

  • Ph. D. Syracuse University

Lab/Center Affiliation(s):

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

Areas of Expertise:

  • Computer security
  • Systems assurance
  • Formal verification

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.

Honors and Awards:

  • 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.

Biao Chen

Degree(s):

  • Ph. D., University of Connecticut

Lab/Center Affiliation:

  • Communication Laboratory

Areas of Expertise:

  • Information Theory
  • Signal Processing
  • Statistical Learning Theory

Chen’s area of research interest mainly focuses on information theory, signal processing, and foundational theory to machine learning, with applications to wireless communications and sensor networks. On the applied side, he has worked extensively on software radio system design, including leading two student teams to compete as finalist in the DARPA Spectrum Challenge and DARPA Spectrum Collaboration Challenge. His most recent endeavors include the development of passive RF sensing theory and systems for a variety of indoor situational awareness missions.

Honors and Awards:

IEEE Fellow (2015)

NSF CAREER Award (2006)

Selected Publications:

  • Y. Liu, T. Wang, Y. Jiang and B. Chen, “Harvesting Ambient RF for Presence Detection Through Deep Learning” , IEEE Trans. Neural Networks and Learning Syst., vol. 33, no. 4, pp. 1571-1583, April 2022, doi: 10.1109/TNNLS.2020.3042908.
  • S. Zhu, B. Chen, Z. Chen and P. Yang, “Asymptotically Optimal One- and Two-Sample Testing With Kernels,” in IEEE Transactions on Information Theory, vol. 67, no. 4, pp. 2074-2092, April 2021, doi: 10.1109/TIT.2021.3059267.
  • G. Xu, W. Liu and B. Chen, “A Lossy Source Coding Interpretation of Wyner’s Common Information,” in IEEE Transactions on Information Theory, vol. 62, no. 2, pp. 754-768, Feb. 2016, doi: 10.1109/TIT.2015.2506560.
  • H. Chen, B. Chen and P. K. Varshney, “A New Framework for Distributed Detection With Conditionally Dependent Observations,” in IEEE Transactions on Signal Processing, vol. 60, no. 3, pp. 1409-1419, March 2012, doi: 10.1109/TSP.2011.2177975.
  • X. Shang, G. Kramer and B. Chen, “A New Outer Bound and the Noisy-Interference Sum–Rate Capacity for Gaussian Interference Channels,” in IEEE Transactions on Information Theory, vol. 55, no. 2, pp. 689-699, Feb. 2009, doi: 10.1109/TIT.2008.2009793.

C.Y. Roger Chen

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.

Syracuse Center of Excellence in Environmental Energy Systems

The Syracuse Center of Excellence (CoE) is a collaborative organization that accelerates the development of innovations for a sustainable future. As New York State’s Center of Excellence in Environmental and Energy Systems, we engage more than 200 private companies, organizations, and academic institutions to create new products and services in indoor environmental quality, clean and renewable energy, and water resource management.

With a staff based at its headquarters in downtown Syracuse, the CoE has three specialized teams that focus on research, industry collaboration, and sustainable community solutions. In research, we are at the forefront of groundbreaking new clean technologies—leveraging world-class R&D facilities from the iconic, high-performance, LEED™ Platinum “living laboratory” that is the CoE headquarters to the state-of-the-art labs of our academic and industry partners. We drive and accelerate innovative research to the marketplace through strategic industry collaborations regionally, nationally, and internationally. We create sustainable community solutions by implementing new technologies and bringing the latest knowledge on environmental sustainability to the public through educational and training programs.

At our Syracuse site, we provide laboratory and office space for research and business collaborations involving new environmental and energy systems products and services. Research areas include systems that monitor and control comfortable air temperature, air quality, lighting, sound and water quality in built and urban environments, and innovative energy systems, including clean technologies and renewable fuel sources.

The work of the CoE and its members impacts the essentials of our human existence in harmony with nature. We improve the energy that powers our lives, the air we breathe, the water we drink, and the buildings in which we live, work, learn, and play.

Learn More

Center for Advanced Systems and Engineering (CASE)

CASE is New York State’s premier applied research center for interdisciplinary expertise in complex information-intensive systems, including monitoring and control, predictive analysis, intelligence, security, and assurance.
CASE has been a designated New York State Center of Advanced Technology (CAT) since 1984, bringing together traditional academic strengths in research and education to promote strong university-industry interaction and generate positive economic impact across New York State and beyond.

Learn more >

Faculty

Wenliang (Kevin) Du

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:

  • IEEE Fellow
  • 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

J. Cole Smith

Degrees:

  • PhD, Industrial and Systems Engineering, Virginia Tech, 2000
  • BS, Mathematical Sciences, Clemson University, 1996

Areas of Expertise:

  • Integer programming and combinatorial optimization
  • Network flows and facility location
  • Computational optimization methods
  • Large-scale optimization due to uncertainty or robustness considerations

My research interests lie in the field of mathematical optimization, especially in mixed-integer programming and combinatorial optimization. Much of my research has recently focused on network interdiction and fortification, along with bilevel mixed-integer optimization problems. I am particularly interested in interdiction problems that involve uncertain data, and/or in which there is an asymmetry of information among the players. My research has applications in areas including logistics, national security, healthcare, production, ecology, and sports. This research has recently appeared in journals such as Operations Research, Mathematical Programming, IISE Transactions, Networks, and INFORMS Journal on Computing, and has been supported by agencies including the National Science Foundation, the Office of Naval Research, the Air Force Office of Scientific Research, the Defense Threat Reduction Agency, and the Defense Advanced Research Projects Agency.

Honors:

  • 2023 Fellow, Institute for Operations Research and the Management Sciences (INFORMS)
  • 2019 Member, Academy of Distinguished Alumni for the Grado Department of Industrial and Systems Engineering at Virginia Tech
  • 2018 Fellow, Institute of Industrial and Systems Engineers
  • 2014 Glover-Klingman Prize for Best Paper in Networks (Sullivan and Smith, 2014)
  • 2010 Hamed K. Eldin Outstanding Young Industrial Engineer in Education Award

Selected Publications:

* Nguyen, D., Song, Y., and Smith, J.C., “A Two-Stage Interdiction-Monitoring Game,” 81(3), 334-358, Networks, 2023.

*Bochkarev, A.A., and Smith, J.C., “On Aligning Non-order-associated Binary Decision Diagrams,” 35(5), 910-928, INFORMS Journal on Computing, 2023.

*Curry, R.M. and Smith, J.C., “Minimum-cost Flow Problems Having Arc-activation Costs,” Naval Research Logistics, 69(2), 320-335, 2022.

* Lozano, L. and Smith, J.C., “A Binary Decision Diagram Based Algorithm for Solving a Class of Integer Two-Stage Stochastic Programs,” Mathematical Programming, 191(1), 381-404, 2022.

* Nguyen, D. and Smith, J.C., “Network Interdiction with Asymmetric Cost Uncertainty,” European Journal of Operational Research, 297(1), 239-251, 2022.

* Holzmann, T. and Smith, J.C., “The Shortest Path Interdiction Problem with Randomized Interdiction Strategies: Complexity and Algorithms,” Operations Research, 69(1), 82-99, 2021.

Electrical Engineering and Computer Science Professor Pramod Varshney and Students Working With Industry Leaders on Drone use Research

Pramod Varshney Portrait

Distinguished Professor Pramod Varshney’s Sensor Fusion Lab in the College of Engineering and Computer Science along with the Center for Advanced Systems and Engineering (CASE) at Syracuse University, is collaborating with the multinational Thales company to develop new tools and techniques for monitoring air space and tracking of small unmanned aircraft systems (UAS), commonly referred to as “drones”.

Drones, are becoming increasingly important in our daily lives in order to quickly and safely deliver essential goods and better serve populations. As the world faces new challenges, these types of capabilities provide alternative access with reduced physical touch points, which is particularly important in the context of COVID-19.  Varshney says this collaboration is critical to the advancement of drone integration into the national airspace system and integral to multiple, on-going integration projects including the U.S. Air Force Research Lab’s Collaborative Low-Altitude UAS Integration Effort (CLUE) and for the New York UAS Corridor—a project taking place in close proximity to Syracuse University to integrate drones into the airspace safely between Syracuse, NY, and the FAA’s UAS Test Site at the Griffiss International Airport located in Rome, NY.

Dr.Varshney’s lab is developing performance metrics and models for new radar systems being deployed ensuring that traditional aviators and drones do not get too close in the air, thereby creating a safety issue within the national airspace system.  Varshney and his students are working with Thales engineers and business leaders to implement algorithms that will more accurately track drones using multiple sensors (radar, acoustic, radio frequency and cameras) to provide real-time tracking ensuring safety in the air and on the ground.  Surveillance data fusion is a core competency at Syracuse University which led to the partnership between Thales and Varshney—a recognized, world-renowned expert in multi-sensor data fusion algorithmic development.

Thales, a global company with more than 80,000 employees developing and delivering solutions for aerospace, space, ground transportation, defense and digital identity and e-security,  has a long-standing commitment to university partnerships.

“While the company possesses world-class engineering and development professionals, business leaders within the company recognize the importance of academic partnerships to rapidly advance technologies and concepts, and develop the next generation workforce who will revolutionize business practices and technology advancement,” said Varshney.

As a large systems integrator, Thales helped define the standard for UAS airspace integration and traffic management models – specifically as an early partner with the FAA for Low Altitude Authorization and Notification Capability (LAANC). The company’s integration of third party capabilities, such as surveillance and other data services into a UTM platform, is enabling new digital services for UAS airspace access.  Varshney says Syracuse University plays a vital role in the integration of this safety-critical service.

“Central New York is leading the United States in the integration of drone technology.  Syracuse University and the school’s Autonomous Systems Policy Institute along with other organizations including CenterState CEO and NUAIR and Thales are committed to establishing a leadership role in the development of critical technologies, policies and new public-private business models to advance the United States’ national airspace system,” said Varshney.

Electrical Engineering and Computer Engineering 2021 Senior Design Capstone Presentations

Electrical engineering and computer engineering seniors worked together as teams on their senior capstone design projects. Each team built a working physical prototype and demonstrated their design, key components and technology to their classmates and faculty. Since teams were not allowed to present their designs to the public due to COVID-19 precautions, here are videos of the 2021 team presentations.

Train Driven Wind Turbine (Emerson Iannone, Miguel Gomez, Nick Fazzone, Ketan Dubey)

Smart Cup Holder (Brendan Ciarlone, Alex Cramer, Nick Mohan, Ian Dickerson)

Ride Along Autonomous Vehicle (Trevonne Davis, Han Gyul Kwon, Mrinal Mathur, Matthew Storozum)

Smart Home (Chongfang Xu, Shu Wang, Yifei Che, Guoliang Chen)

Etch-A-Sketch Control (Vincent Camarena, Andrew Kelsey, John Garcia)

Solar Tracking Panel (Isaiah Plummer, Daniah Alzubaidi, Roberto Salazar, Ryan Kane)

Fall Detection Alert (Dana Marie Castillo Chea, Matthew Gelinas, Kylie Nikolaus, Malkiel Asher)

Homebrew Radar (Jinzhi Cai, Eli Clark, Jack Guida, Erik Olsen)

Programmable Delivery Bot (Justin Geary, Stephen Rogers, Nicholas Landry, Ritwik Takkar)

Automatic Pet Feeder (Xionfeng Zhu, Shengran Cheng, Yuang Cao, Antian Liu)

Electrical engineering and computer science and Upstate Medical University researchers win notable award at artificial intelligence conference

A research collaboration between electrical engineering and computer science (EECS) researchers and colleagues at Upstate Medical University on detecting Alzheimer’s disease won notable award at an artificial intelligence conference. Professors Asif Salekin and Senem Velipasalar, EECS graduate students Fatih Altay and Guillermo Ramon Sánchez along with doctors Yanli James and Stephen V. Faraone from Upstate Medical University won the IAAI-21 Deployed Application Award at the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence.

The team’s research centers on early detection of Alzheimer’s disease. The most common symptoms of Alzheimer’s disease include problems with communicating and abstract thinking, as well as disorientation. Early detection of the disease can help improve cognitive functioning with medication and training. The research paper from the Syracuse University/ Upstate Medical University team proposes two machine learning approaches for detecting Alzheimer’s disease from MRI images to help early detection efforts at a preclinical stage before symptoms have appeared.

In their paper the team described the impact their research could have. “Recent reports on Alzheimer’s disease (AD) suggest that change in the brain may be evident 20 years before dementia symptoms, typically when the disease gets diagnosed. But substantial neuronal loss happens during that latent period of the disease. The early-stage intervention of AD can significantly impact the neuronal degeneration process and treatment of symptoms that would expand the patients’ life expectancy and quality of life. Hence, accurate detection or indication of preclinical AD is a major interest in the medical community. Our research is the first to develop an effective machine learning approach that can identify the latent patterns due to preclinical AD from MRI brain scans, which can significantly improve AD patients’ intervention and treatment.”

Engineering and Computer Science 2021 Research Day Award Winners

Thank you to everyone who took part in the Engineering and Computer Science 2021 Research Day on March 12th! We would also like to give a special thanks to Dr. Joseph Helble, Provost of Dartmouth College, for the keynote presentation. Here are the winners as chosen by our panel of judges.

Energy, Environment and Smart Materials

First Prize: Light-Induced Self-Writing: A Novel Approach to Develop Organized Polymer Composite Materials. Shreyas Pathreeker; Advisor Dr. Ian Hossein

Second Prize: Development of Inside Out Solid Oxide Fuel Cells for Combined Heat and Power Systems. Alexander Hartwell, Advisor Dr. Jeongmin Ahn

Third Prize: HYDRUS-1D Modeling to Represent Hydrologic Performance of the OnCenter Green Roof. Courtney Gammon; Advisor Dr. Cliff Davidson

Communication and Security

First Prize: Optimized Virtual Antenna Array of Wideband Narrow Beam MIMO System for Overlapped Virtual Elements. Richard Tanski, Advisor: Dr. Jay Lee

Second Prize: Coverage in Networks with Hybrid Terahertz, Millimeter Wave, and Microwave Transmissions. Xueyuan Wang, Advisor: Dr. M. Cenk Gursoy

Third Prize: An Efficient Deep Capsule Network with Interleaved Sparse Connections and Attention-Based Routing. Chenbin Pan, Advisor: Dr. Senem Velipasalar

Sensors, Robotics and Smart Systems

First Prize: Towards Disaster Recovery: Incorporating the Uncertainties Caused by Cyber Attacks in Controlled Islanding. Sagnik Basumallik, Advisor: Dr. Sara Eftekharnejad

Second Prize: Real-Time Adaptive Sensor Attack Detection in Autonomous Cyber-Physical Systems. Francis Akowuah, Advisor: Dr. Fanxin Kong

Third Prize (tie): Data Generation for Transient Stability Assessment to Address Lack of Training Data. Rui Ma, Advisor: Dr. Sara Eftekharnejad AND Soft Crawling Inchworm Robot Enabled by Dynamically Tunable Friction. Siavash Sharifi, Advisor: Dr. Wanliang Shan

Health and Well-being

First Prize: Investigation of the Effects of Electrochemical Reactions on Complex Metal Tribocorrosion within the Human Body. Thomas Welles; Advisor Dr. Jeongmin Ahn

Second Prize: Prediction of Tight Junction Strand Architecture. Nandhini Rajagopal, Advisor Dr. Shikha Nangia

Third Prize: Persister Control by Leveraging Dormancy Associated Reduction of Antibiotic Efflux. Sweta Roy; Advisor Dr. Dacheng Ren

Electrical Engineering and Computer Science Professor Vir Phoha on the Ethics of Facial Recognition Software

The use of facial recognition technology has been controversial and it has been criticized as being prone to misuse and reinforcing existing biases. Cities across the United States have been banning the use of facial recognition software and in the past year, companies like IBM, Microsoft and Amazon decided to suspend selling facial recognition software to police.  Electrical engineering and computer science professor Vir Phoha says he agrees with taking a deep look at the use of facial recognition technology and holding it back until proper safeguards to prevent unintentional misuse are found  but still believes it can be beneficial.

On the suspension of selling face recognition technology to police by Amazon, IBM, and Microsoft, he says “My first reaction was that they did the right thing. At the same time, once I thought about it, it is a very good technology. It has a lot of potential but it is a double edge sword. You use it properly and it can do great things and if you don’t use it properly, it can hurt you.”

Phoha has done extensive research on artificial intelligence, machine learning and security. He says a lot of questions about facial recognition should start with the humans who built them.

“There are many ways to do face recognition, one is geometric. So you look at the points, for example the distance between eyes, the length of the nose – that is geometric,” said Phoha. “There are multiple other ways such as making a base model, looking at variations, and storing the variations as a template for a user.  There are methods that involve learning and associating specific face types to specific gender or history, or behaviors. There is a learning involved. If you use machine learning or artificial intelligence, any learning can be biased by the people who build those algorithms. Unconsciously, people who build those algorithms may be bringing their own biases in regard to gender, race and age.”

An algorithm that reflects biases can have destructive effects. Numerous studies have shown it misidentifies Black and Brown faces at a much higher rate. A Commerce Department test of facial recognition software found that error rates for African men and women were twice as high as they were for Eastern Europeans. Errors can lead to wrongful arrests.

“If you say 10% more of a specific racial group have been convicted of a crime compared to a majority race, then a random person from that racial group who is completely innocent – their chance of being labeled as a criminal could be 10% higher just due to this underlying statistic being part of the algorithm,” said Phoha.

Phoha says it will be an ongoing fight to combat inherent biases in algorithms.

“It is good technology but we must make sure there are safeguards. Enough science should be there to make sure the algorithms that are built are impartial,” said Phoha. “In replicating human capabilities, humans have bias.”

Software that attempts to identify people based on their facial structure can easily be misconfigured.

“Facial structure can be very different for differing ethnicities,” said Phoha. “People who are biased without knowing they are biased, implicit bias that will be translated into data.”

If the technology is going to move forward, Phoha and many other experts believe it is an area where sociology, psychology, machine learning, computer science, artificial intelligence need to come together.

“The science will be a mess if we don’t consider all these factors. We want an equitable society,” said Phoha. “The potential of misuse is very high. Social justice, empathy and equity should be part of research in this area. We do not want a group where any groups are marginalized for any reason.”

Fall 2020 Engineering and Computer Science Dean’s List

In recognition of superior scholarship, the following students have been entered on the Engineering and Computer Science Dean’s List for Fall 2020.

To be eligible for Dean’s List recognition, the minimum semester grade point average must be 3.40 or higher, must have earned a minimum of 12 graded credits and must have no missing or incomplete grades.

Students: Please email engineering@syr.edu if you have questions about your current Dean’s List status.

Aerospace Engineering

Sean  Adams

Zar Nigar  Ahmad

Mukhammed Shamil  Askarov

Justin Douglas Blowers

Katherine Elizabeth Braun

Madeline Constance Brooks

Richard L Bruschi

Owen P Clyne

Nicholas Daniel Crane

Brian James Cronin

Ryan  Demis

Aleksandar  Dzodic

Kaleb Jonah Eddy

Hans-Christian  Esser

Kassidy  Fields

Christian Scott Fitzgerald

Elan  Fullmer

Benjamin Daniel Gerard

Alexandre J Gill

Sareta Rose Gladson

Jacob D Gomez

Zachary William Haas

David Leo Hadley

Alyssa  Henley

Aidan  Hoff

Jiaji  Hu

Sydney F Jud

Harrison  Kayton

Trevor Anthony Knight

Justin  Kohan

Trevor D Kroells

Isaac Alan Lehigh

Jacob Eric Long

Powers Craig Lynch

Noah  Martel

Maxwell Joseph Martin

Jason W McElhinney

Mariana C McManus

Alexander T Metcalf

John P Michinko

Vincent Anthony Miczek

Kendra Teresa Miller

Maximus Jules Mintz

Paul Robert Mokotoff

Evan Gregory Moore

Brendan Pierce Murty

Mark  Namatsaliuk

Daniel  Oluwalana

Randall McGinnis Osborn

David Dang Pham

Madeline G Phelan

Logan D Prye

Kazi Golam Rafee

Kip  Risch-Andrews

Tracey Josephine Rochette

Jared M Rodriguez

Gregory Joseph Ruef

William J Saueressig

Fred Evan Schaffer

Justine John A Serdoncillo

Vraj  Shah

Prabha  Singh

Gregory C Slodysko Jr

Zachary Michael Stahl

Ethan J Stocum

Marco  Svolinsky

Richard A Tedeschi

Darlene A Tinsley

Anthony R Tricarico

Sasha  Valitutti

Cody Joseph Vannostrand

Mason Alexander Weber

Timothy Dwayne Wiley

Aliza Marie Willsey

Xinyu  Wu

Melissa  Yeung

Bioengineering

Samantha Michelle Abate

Jordyn Danielle Abrams

Bianca Louise Andrada

Gabriela  Angel

Oumou  Azika

Colin J Babick

Paige  Bencivenga

Ailla Frances Bishop

Colby James Black

Anna Mae Brunson

Zeynep Sue Cakmak

Britnie Jean Carpentier

Jade Ashlee Carter

Maria G Catalane

Elizabeth Ann Clarke

Dominic Thomas Clinch

Mya R Cohen

Lukas  Cook

Shane A Corridore

Shaila S Cuellar

Linzy M Dineen

Anthony Mark Dragone

Alejandro J Durand

Bailey M Felix

Akweshie A Fon-Ndikum

Gabriela Renee Gonzalez-Beauchamp

Skyla  Gordon

Nathaniel Fee Gur-Arie

Grace  Haas

Lauren Elizabeth Hamilton

Victoria Li Rui Hathaway

Brenna  Henderson

Avinash  Jagroo

Madeline  Jones

Simran  Karamchandani

Gabriel  Khan

Mohamed F Khan

Olivia Lynne Kmito

Kiana Yanira Lally

Sara Anne Leonardo

Isabelle S Lewis

Trevor Daniel Amnott Liimatainen

Xinyan  Lin

Alejandra Eugenia Lopez

Mark Maximilian Macios

Ethan L Masters

Aelish  McGivney

Caitlin R Mehl

Lindy M Melegari

Hallie Teresa Morgan

Connor G Mulligan

Hannah V Murphy

Jonathan  Ngo

Mark  Nicola

Nicole E Nielsen

Matt Evan Orlando

Megan Isabel Perlman

Natalie Marie Petryk

Connor  Preston

Alexander C Rateb

Beatrice Elizabeth Reilly

Gavin David Richards

Rebecca A Schaefer

Brielle L Seidel

Alyssa  Shelburne

Justin N Stock

Elizabeth Tarami Su

Bearett Ann Tarris

Zhuoqi  Tong

Edgardo  Velazquez

Royce Robert Weber-Pierson

Nathaniel D Wellington

Maximillian Meier Wilderman

Lauren Margaret Woodford

Rui  Xie

Alina  Zdebska

Julian Marcus Smucker Zorn

Samantha  Zysk

Chemical Engineering

Paige O Adebo

Adriana M Archilla

Steven Matthew Axelsen

Olivia Anna Babu

Athena Andrea Basdekis

Sandy Ynhu Cao

Karley M Chambers

Trinity Joy Coates

Olushola  Coker

Kelly  Correa

Hao  Dai

Dennis  Dao

Samantha  Esparza

David Anthony Fikhman

Edward Coleman Fluker

Priya S Ganesh

Brent Tadao Gosselin

Avery  Gunderson

Oduduabasi James Isaiah

Aiden A Jacobs

Stanley  Jimenez

Sayf  Karim

Laxmi  Khatiwada

Adam J Klinger

Simran Dharmendra  Lakhani

Rawia F A M  Marafi

Angela L Martinez

Oliver  Mutu

Fabiana Nohelia Perez

Seth  Reed

Ivan  Sarbinov

Arsh Saifahmed Shaikh

Jacob Matthew Shellhamer

Dakota Alexander Story

Jason  Tan

Spencer T Tardy

Megan  Varcoe

Briana Nicole Vlacich

Connor Andrew Wescott

Nia  Williams

Melita  Zejnilovic

Civil Engineering

Orges  Agolli

Osama  Alkasabra

Anna Rose Arcaro

Nicole  Ayora-Gonzalez

Vincent  Barone

Noah J Bonett

Ryan  Bourdeau

Arielle  Bramble

Matthew Emmet Brewster

David Michael Brodsky

Emma Jane Brown

Alycia Joline Bruce

Joli L Cacciatore

Trevor  Caviness

Alejandro E Correa

Aymeric P Destree

Thomas  Driscoll

Bradley Charles Frederick

Maraea K Garcia

Stephen  Goffredo

Bensen  Gu

Zelin  Guo

Kyle Jacob Huff

Zachary Stephen Jodice

Kate Astrid Kemnitz

Alexander Gregory Klee

Adam Paul Landry

Abigail G Laschalt

Haben  Legesse

Daniel  Leyva

Emma Marie Liptrap

Emilija Alise Lizins

Erick  Lojano-Quispe

Lluvia Margarita Lopez Garces

John M Mazza

Michael J McDonough

Jessica M McGowan

Amira A Mouline

Marissa R Nicole

Erin E O’Brien

Kevin B Ordonez

Benjamin Joseph Putrino

Svetislav  Radovic

Victoria Isabella Rea

Isabella  Salgado

Cassie Elizabeth Saracino

Emma Hayes Schoonover

Juha Wesley Schraden

Ravyn  Smith

Caitlin Jane Spillane

Erin Meagan Splaine

Adrian  Stiefelmann

Anand  Veeraswamy

Nathan  Viramontes

Joseph Peter Wollke

Isabelle  Wong

Paige H Yamane

Computer Engineering

Adekunle J Akinshola

Chikeluba K Anierobi

Malkiel  Asher

Mergim  Azemi

Gavin M Beaudry

Kyle J Betten

Jackson Thomas Bradley

Jinzhi  Cai

Edward Patrick Caraccioli

Dynasty Da’Nasia Chance

Yifei  Che

Dana Marie Castillo Chea

Guoliang  Chen

Kongxin  Chen

Hossain  Delwar

Xavier  Evans

Elizabeth A Fatade

Isaiah Armando Fernandez

Aidan Robert Harrington

Ethan  Hensley

Benjamin N Johnson

Fundi  Juriasi

Ryan Anthony Kane

Andrew Edward Kelsey

Bikash  Khatiwoda

Connor  Kinahan

Jason C Kirk

Nicholas Gerard Lee Landry

Jessica K Lat

Matthew B Leight

Jiaxiong  Li

Cayden T Lombard

Nicholas Kent Magari

Kyle David Maiorana

Mrinal  Mathur

Isabel M Melo

Nicholas J Mohan

Benjamin Hudson Murray

Jose L Olivera

Jiannuo  Pei

Jessica A Reslan

Alfonso E Rivas

Kevin  Robertson

Daniel  Rose

Hongyi  Ruan

Alexander  Segarra

Ritwik  Takkar

Shu  Wang

Ryan  Wolff

Renjie  Xu

Andy  Zheng

Xiong Feng  Zhu

Computer Science

Aashutosh  Acharya

Aaron  Alakkadan

Genesis  Alvarez

Kwaku  Amofah-Boafo

Garret W Babick

Simon C Barley

Giovanna Elizabeth Barsalona

Julia R Barucky

Samantha E Bastien

Dazhi  Bi

Maxwell William Hans Bockmann

Joshua Jordan Boucher

Dane B Brazinski

Bryan Bladimir Bueno Reyes

Bryce  Cable

Christopher Manuel Calderon Suarez

Liam M Calnan

Megan J Campbell

Benjamin Elliott Canfield

Ta’Yea A Cano

Yuecheng  Cao

Abby  Chapman

Jackie  Chen

Kelvin  Chen

Siyu  Chen

Xinglin  Chen

Yixing  Chen

Yuhao  Chen

Doung Lan  Cheung

Season  Chowdhury

Konstantinos  Chrysoulas

Melissa  Chu

Bram H Corregan

Matthew  Cufari

Ryan Matthew Czirr

Otitodirichukwu Oto  Darl Uzu

Salvatore  DeDona

Rudolph  DelFavero

William Stuart Devitt

Matthew E Dickson

Ting  Dong

Russell Carl Doucet

Christopher  Edmonds

Xueyan  Feng

Nathan B Fenske

Lucas Kuebler Fox

Jeremy  Gavrilov

Grant Thomas Gifford

Brianna S Gillfillian

Brian J Giusti

Justin S Glou

Justin  Gluska

Dayong  Gu

Athanasios  Hadjidimoulas

Erika R Hall

Andrew  Hamann

Jillian Elizabeth Handrahan

Taisei  Hashimoto

Zitao  He

Miranda Rose Heard

Karen  Herrera

Wendy  Hesser

Cameron  Hoechst

Nicholas A Hoffis

Laurel  Howell

Jacob  Howlett

Natalie  Huang

Xuanye  Huang

Nathakorn  Jitngamplang

Austin Dean Johnson

Michael Wesley Jones

Alan  Jos

Aarya Tara Kaphley

Cynthia Sze Nga  Kar

Jaehun  Kim

Ekaterina  Kladova

Jared Michael Kozak

Polina  Kozyreva

Miksam  Kurumbang

Rami L Kuttab

Eric C Lee

Gaeun  Lee

Janet Jihoo Lee

Andy  Li

Hao  Li

Jiaqi  Li

Modi  Li

Rick M Li

Ruowen  Li

Ziqi  Li

Arvin  Lin

Haochen  Lin

Chang  Liu

Erxi  Liu

Jiaming  Liu

Jing  Liu

Junzhang  Liu

Steven  Liu

Yuyuan  Liu

Yiheng  Lu

Runzhi  Ma

Hunter O’Neal Malley

Kanoa  Matton

Anthony Louis Mazzacane

Noah  Mechnig-Giordano

Jose R Mendoza

Yiheng  Meng

Preston  Mohr

Thomas J Montfort

Gregory Philip Morneault

Jacob  Morrison

Jovanni Nicholas Mosca

Chenxi  Mu

Andi  Muhaxheri

Paige C Mundie

Phuc Nguyen  Nguyen

Kayla  Nieto

Carlyn M O’Leary

Maduakolam  Onyewu

Maya  Ostoin

Daniel  Pae

William Anderson Palin

Xiaofeng  Pan

Yulin  Pan

Michael J Panighetti

Joshua S Park

Jun Hyoung  Park

Brian Joseph Pellegrino

Siwei  Peng

Anthony  Perna

Duy  Phan

Fiona Colleen Powers Beggs

Shane Michael Race

Alexis Hope Ratigan

Maxwell Johnson Reed

Christopher  Rhodes

Lauryn Ashley Rivers

Julia R Ruiz

Sadikshya  Sanjel

Yousaf  Shahid

Huahao  Shang

Benjamin William Smrtic

Yijie  Song

Jeremy P Stabile

Kevin  Sullivan

Tasfia  Sultana

Mohammad Murtaza Ali Syed

Louanges Essohana Marlene Takou-Ayaoh

Melissa Li Tang

Rae  Tasker

Jonathan Ezra Thomas

Kyra Danielle Thomas

Griffin E Timm

Maxwell D Townsend

Brendan J Treloar

Fiona Mirabella Tubiana

Courtney Patricia Tuozzo

Randy C Vargas

Anthony Michael Verdone

Bermalyn Maricel  Vicente

Christopher Mark Vinciguerra

Tristan C Waddell

Puxuan  Wang

Ruobing  Wang

Zicheng  Wang

Robert  Ward

Daniel  Weaver

Jack Andrew Willis

Nolan Gabriel Willis

Ethan  Wong

Sio Iok  Wong

Tianyi  Wu

Zhiang  Wu

Zongxiu  Wu

Yurui  Xiang

Yujie  Xu

Jinyang  Xue

Chen  Yang

Chen  Yang

Jintao  Yang

Jishuo  Yang

Rory  Yang

Yisheng  Yang

Stella R Yaunches

Elin J Yaworski

Linsong  You

Yulun  Zeng

Chengyuan  Zhang

Liaotianbao  Zhang

Rixiang  Zhang

Weikun  Zhang

Liuyu  Zhou

Mochen  Zhou

Yixuan  Zhou

Ziying  Zhou

Raymond  Zhu

Sida  Zhu

Joseph Patrick Zoll

Engineering Undeclared

Olivia R Conlin

Andrew J Esposito

Elliane Reut Greenberg

Nicholas John Jacobs

Gavin Thomas Macisaac

Sean R Maddock

Sean  O’toole

Eric  Rodriguez

Haoran  Wang

Xinyi  Wang

Carly J Ward

Abigail Meghan Wischerath

Haven M Wittmann

Electrical Engineering

Mohammed A Aljohani

Tianle  Bu

Kevin E Buciak

Vincent Alec Camarena

Arianna Maxine Cameron

Yuang  Cao

Mingfu  Chen

Shengran  Cheng

Brendan Robert Ciarlone

Eli Aiden Clark

Nicholas Shawn Connolly

Alex Lev Cramer

Trevonne  Davis

Nicholas  Fazzone

John Charles Garcia

Justin P Geary

Matthew R Gelinas

Christopher  Gill

Jose I Ginorio

Jack Orlando Guida

Emerson  Iannone

Qingwen  Jia

Michael Matthew Kelly

Han Gyul  Kwon

Jemma  Mallia

Liam Fuller Marcato

Tyler Sean Marston

Zixun Nian  Nian

Kylie Elizabeth Nikolaus

Julia  Pepin

Stephen Joseph Rogers

Gilberto E Ruiz

Roberto Alexander Salazar-Ramirez

Jenna Mei Stapleton

Luke J Terris

Jared William Welch

Abigail  Wile

Zheyuan  Zhang

Environmental Engineering

Ana Cristina  Baez Gotay

Luke M Borden

Benjamin R Cavarra

Evan James Cibelli

Cambre Rae Codington

Elizabeth Bryant Cultra

Cameron Nicole Edwards

Anna  Feldman

Allyson  Greenberg

Jessenia Paola Guzman

Brady E Hartnett

Christopher Graham Harvey

Anna M Holdosh

Eva Rose Kamman

Abigail Rose King

Nicholas Colin Axel Kohl

Birch  Lazo-Murphy

Audrey B Liebhaber

Carleigh A Lutz

Kevin A Lynch

Molly M Matheson

Matthew Edward Nosalek

Yongfang  Qi

Kaura Yanse Reyes

Mary H Schieman

Noah Michael Sherman

Ian  Storrs

Husna M Tunje

Jacob M Tyler

Maria Antonia  Villegas Botero

Savannah Marie Wujastyk

Qiuyu  Zhou

Reilly  Zink

Mechanical Engineering

Owyn Phillip Adams

Joshua Carl Arndt

Timothy G Arnold

Arda  Arslan

Michael James Battin Jr

Rachael O Beresford

Renee Allison Brogley

Arnaud  Buard

Meaghan Patricia Loan Burns

Ryan G Burns

Tyler  Burns

Adrian L Caballero

Alexander Joseph Callo

Joseph Timothy Capra

Caleigh J Casey

Rishov  Chatterjee

Artur  Chuvik

Santiago  Correa

Samuel Joseph Corrigan

Cooper P Crone

Peter M Daniels

David Matthew Denneen

Madeline  Doyle

Katherine Grace Driscoll

Henry C Duisberg

Griffin Thomas Estes

Luke Samuel Fink

Andrew John Gagan

Clinton Edward Farina Garrahan

Samuel Ryan Getman

Derrick Edward Goll

Emily Ann Greaney

Daniel Robert Greene

David M Griffin

Connor  Hayes

Melissa Jane Hiller

Elliott J Holdosh

Yongsong  Huang

John Christopher Inzinga

Nicholas W Jebaily

Zhao  Jin

Dong Myeong  Kang

Daniel Jacob Kenney

Finnian James Kery

Teagan L Kilian

Cherry  Kim

Savannah Mae Kreppein

Elizabeth Marcy Kretzing

John  Larkin

Lily  Larkin

Peter  Le Porin

Samuel Robert Livingston

Honorata  Lubecka

Bei  Luo

Katherine Elizabeth Macbain

Ryan Patrek Martineau

Ryan A Melick

Sarah Ann Michael

Georgios  Michopoulos

Leilah  Miller

Wiley Robert Moslow

Allison  Mullen

Yuanhao  Nong

Beau M Norris

Aidan T O’Brien

Nicholas Joseph Papaleo

Scott  Reyes

Aidan  Riederich

Colin  Santangelo

Nathan  Schnider

Shane M Sefransky

William Kaspar Sherfey

Jake Matthew Sheridan

Zachary Ryan Shuler

Eric  Silfies

Nathaniel  Slabaugh

Griffin  Smith

Owen Nicholas Smith

Austin James Sumner

Yiyuan  Sun

Matthew K Swanson

Ethan William Tracey

Evan R Tulsky

Nicholas Erik Vestergaard

Taj Asim Whitney

Michael  Wong

Tszho  Wong

Sean T Wuestman

Ruohan  Xu

Maxwell James Yonkers

Xiaoqing  Yu

Systems & Information Science

Sean  Chen

Ryan Thomas Congdon

Yiyang  Dai

Anuj P Gupta

Connor W Gurnham

Rodcliff  Hall

Skyler Marie Hall

Stacy  Kim

Mitchell F Liang

Anthony  Moon

Niara A Phoenix

College of Engineering and Computer Science Honored by the American Society for Engineering Education’s Diversity Recognition Program

Syracuse University’s College of Engineering and Computer Science received bronze level status by the American Society for Engineering Education’s (ASEE) Diversity Recognition Program. The program’s goal is to help engineering, engineering technology, and computing programs promote diversity, equity, and inclusion in member colleges and ultimately in the workplace.

“I am thrilled that our collective efforts to support the college’s strategic goals, and the DEI advancements in our policies, procedures, practices and programs, positioned Syracuse University’s College of Engineering and Computer Science to be among select best in class institutions who received this national recognition,” said Assistant Dean for Inclusive Excellence Karen Davis.

Syracuse University’s bronze status from the ASEE is valid for three years and begins in 2021. The ASEE says timetables for silver and gold recognition will be posted in the future.

Electrical Engineering and Computer Science Professor Farzana Rahman Awarded ExploreCSR 2020 Grant by Google to Introduce and Engage Underrepresented Students in Computing Research

Electrical engineering and computer science (EECS) Professor Farzana Rahman received a 2020 Google exploreCSR award to fund the development of an undergraduate student engagement workshop program, Research Exposure in Socially Relevant Computing (RESORC).

The RESORC program will provide research opportunities to undergraduate students from Syracuse University and nearby institutions targeting populations underrepresented in computing, including Latinx, African American, American Indian or Indigenous and LGBTQIA+ students.

According Rahman, the population of students pursuing CS and computing degrees is not representative of the diversity of people in the U.S., with women and other groups persistently underrepresented. Additionally, research has shown that computing research pipeline is not diverse since women and underrepresented students face many barriers like lack of self-confidence, stereotype threat, and lack of women role models. There is also lack of knowledge regarding research opportunities and the potential benefit of research careers. Many unrepresented students are never exposed to research due to coming from institutions with limited research capabilities. The intersectionality of these students also places more structural barriers for them to explore anything other than a regular degree. RESORC aims to diversify the Ph.D. pipeline through peer-assisted, team-based research exposure that places special emphasis on mentoring women.

The primary objectives of this workshop are to –

  • Introduce women students to graduate education and research career opportunities.
  • Share best practices and resources to conduct research.
  • Support students to become stronger candidates for doctoral programs.
  • Create a network of future women scientists in the area of computing.

The RESORC experience will expose participants to research in socially relevant computing though close mentoring provided by the graduate students of the SU EECS department. These graduate mentors will attend a training session informed by best practices for mentoring underrepresented students by NCWIT.

The workshop will use Social Cognitive Career Theory (SCCT) that will help to influence the career ambitions and choices of participants in computing through guided research exploration. It will also use a Peer-Assisted Team Research (PATR) model that will involve participants in research experiences within teams with a dedicated graduate mentor’s supervision. PATR will improve student’s scientific reasoning abilities, research self-efficacy, and sense of belonging in computing.

“I expect that this experience will enable our Ph.D. student volunteers to be better, more inclusive mentors as they pursue their own careers,” said Rahman.

After an initial proof-of-concept year, Rahman hopes to sustain and expand RESORC to reach more students at Syracuse University and nearby other institutions in the area.

Syracuse University Ranked in the Top 25 for Best Online Graduate Information Technology Programs by U.S. News & World Report

Syracuse University’s School of Information Studies (iSchool) and the College of Engineering and Computer Science (ECS) have been recognized as No. 11 for Best Online Graduate Information Technology Programs for Veterans and No. 25 for Best Online Graduate Information Technology Programs by U.S. News & World Report for 2021.

The full rankings, released earlier today, are available on the U.S. News & World Report website.

The College of Engineering and Computer Science offers online master’s degree programs in cybersecurity, computer science and computer engineering.

The iSchool offers M.S. degree programs in applied data science, information management, information management for executives and library and information science online.

“This ranking reflects the outstanding work our faculty have put in to make Syracuse University a leader in online education. The online computing master’s programs offered by the College of Engineering and Computer Science allow students to take classes on a schedule that is right for them and it can be an opportunity to advance their career while still working full time,” said Jae C. Oh, chair of the Department of Electrical Engineering and Computer Science and the David G. Edelstein Professor for Broadening Participation.

“The iSchool is pleased to receive this recognition of our high-quality online programs from U.S. News and World Report,” says Victoria Williams, director of online education and post traditional education at the iSchool. “For over 25 years, our online programs have attracted working professionals from around the world. The iSchool’s interdisciplinary and applied-learning approach allows students to customize a degree to gain the skills needed to meet their career goals and immediately apply what they’re learning in the classroom to their professional roles. We’re proud that our programs remain highly ranked for Information Technology and Info Tech for Veterans as the field continues to be competitive.”

“Our online programs are an outstanding option for people having a diverse array of educational and personal backgrounds. We have been intentional in designing a high-quality, rigorous online educational program while also giving students the flexibility they need,” said College of Engineering and Computer Science Dean J. Cole Smith. “It is gratifying to see our Syracuse University programs in the top 25 of the national rankings.”

iSchool Dean Raj Dewan adds, “There is a long history of groundbreaking work being done at Syracuse University’s iSchool. This 2021 ranking underscores that standing as well as the school’s ongoing commitment to innovation in the digital age. The iSchool is exceptional at offering today’s students and professionals the kinds of education and experiences they will need for successful careers in a wide range of fields, and our graduates are highly sought-after for their skills in information technology and management, cloud computing, data analytics, machine learning, library science, and more.”

Innovation & Entrepreneurship at Syracuse University Webinar

A discussion between the Executive Director of the Blackstone LaunchPad, Linda Dickerson Hartsock, and aerospace engineering and Invent@SU alumna Kayla Simon ’19 about the many ways Syracuse University supports students in designing, prototyping and pitching their new businesses.

Electrical Engineering Alumni Profile: Ed Swallow ’80

When Ed Swallow ’80 first visited the Syracuse University campus, he was not certain what engineering major he would pursue with his Air Force ROTC scholarship. Following a meeting with the electrical engineering program director, Swallow learned something he thought made electrical engineers unique and he knew what he wanted to do.

“Electrical engineers learn problem solving,” said Swallow. There isn’t one answer. In electrical engineering there are dozens or hundreds of ways of accomplishing the same thing.”

His initial Syracuse experience had an immediate and lasting impact.

“My advisor was really good about trying to get me to broaden my horizons. It was good the University allowed me to engage in a variety of experiences. It’s the multi-disciplinary education that my advisor helped me get that was the greatest takeaway,” said Swallow. “Knowing that I was Air Force ROTC and I was going to become an officer, my advisor basically said recognize you are not going to do a lot of engineering, you’re going to lead engineers and being a generalist is going to be better for your entire career. He was incredibly right about that. More than anything else, that one conversation made a big university feel very personal to me.”

That meeting formed the foundation of what would become the theme of his career. Swallow went on active duty in August of 1980 and started in satellite operations.

“I was very interested in image processing. I focused on infrared image processing by the time I graduated and that’s what ended up having the Air Force send me out to California to fill an electrical engineering slot,” said Swallow. “Back then it was highly classified, but I worked on the Gambit and Hexagon film return reconnaissance spacecraft and I heavily used my Syracuse background.”

While on active duty, Swallow went into space operations and helped on the front-end building first of their kind space systems. He gained leadership experience as an acting commander while stationed at Thule Air Force base in Greenland. Before entering the reserves in 1985, Swallow gained his first experience with NASA working as one of the payload communicators on space shuttle STS-4. From there things moved rapidly. Swallow took a job with a company named Ultrasystems Defense and Space, which through a series of mergers and acquisitions eventually became part of Logicon.

“I went from an individual contributor, to task manager, to assistant program manager, to deputy program manager, to program manager to director of programs for the entire Silicon Valley office. A lot of that was because I understood the customers and how to solve problems for them as a generalist, which helped me grow the business. I went to work for a company called Space Applications Corporation as tech director, but quickly moved to division general manager, and in 1997 I became the vice president of business development. Not long after that, they promoted me to the equivalent of COO,” said Swallow. “By 2001 we sold the company to L3 Communications, so I went to work at Northrop Grumman.”

Following the events of September 11th in 2001, Swallow’s work had him building relationships with the Department of Homeland Security and he helped deploy the homeland secure data network. He would then go on to play critical roles in some of the largest IT projects in the country, including the New York City secure broadband wireless system for first responders and the first cloud deployment for the federal government. Swallow’s team even helped bring together the opening sequence of the 2008 Academy Award winning film “The Hurt Locker.”

“If you look carefully, that robot had a Northrop Grumman logo on it and I was the one that signed the deal that allowed them to use the robot for the film,” said Swallow. “They did not actually blow it up. Thank goodness.”

Like his Syracuse University advisor had told him, being a generalist had become the primary thread in his career. Following a brief retirement from Northrop in 2014, Swallow accepted his current position as senior vice president, Civil Systems Group at The Aerospace Corporation.

“It is the best job on the planet. I get to work with senior leaders in the space world, help advise them on policy and help them find solutions to deep technical problems,” said Swallow.

His current position has put him at the heart of the human exploration system. Recently, he co-chaired the program status assessment for Artemis, the mission to put the next man and first woman on the moon by 2024. He oversees a team building a next-generation space suit and he has people managing the extravehicular activity of astronauts.

Swallow has ten simple rules for success he shares with students and young professionals. One of them is invest your time, don’t just put in the hours. This is a reminder to always think about what you are going to take away from working on a project. It’s a habit that helped him begin developing critical soft skills his last semester at Syracuse University when ROTC made him the cadet corps commander and he had to give weekly addresses.

“I sought leadership positions and it was that leadership training I received through the ROTC that I think was incredibly important,” said Swallow.

Now, as an industry leader, Swallow has some ideas about the next big growth areas for aerospace and electrical engineering.

“In aerospace engineering, where things are headed very quickly is hypersonics [pun intended]. High-speed point to point transportation. On the electrical engineering side, building trust into autonomous systems is the big thing,” said Swallow. Building trusted AI systems that always have a predictable outcome is really a tough nut to crack and if somebody figures that out at the graduate level, they’re going to find a job just about anywhere.”

Ed Swallow’s ten simple rules for success:

  1. Invest your time, don’t just put in the hours
  2. Dress for the job you want, not the one you have
  3. Trying to show how smart you are usually backfires
  4. W.A.I.T: Why Am I Talking?
  5. There are no “gut courses” in business — always do your best
  6. Build a brand, internally and externally, and honor that brand
  7. Verbs matter: Take blame; accept credit
  8. Make your boss a hero, help her get promoted, never surprise them
  9. Don’t confuse activity with results
  10. Integrity, honesty, and strong ethics outweigh all else

Electrical Engineering and Computer Science Professors Qiu and Gursoy Receive 2020 IEEE Region 1 Technological Innovation (Academic) Awards

Electrical engineering and computer science Professors Cenk Gursoy and Qinru Qiu received 2020 IEEE Region 1 Technological Innovation (Academic) Awards. Both were nominated by Distinguished Professor Pramod Varshney.

Qiu was recognized for her pioneering contributions in stochastic power management and brain-inspired architectures to achieve energy efficient computing.

“I want to thank Dr. Varshney for the nomination, and thank my colleagues, friends and students for their support,” said Qiu. “I’m honored to be recognized by this award and also encouraged to further my research in the area of energy efficient and brain-inspired neuromorphic computing.”

Gursoy was recognized for his significant contributions in wireless communications and networking.

“In my research group, we have been working to solve the challenges in the design of 5G wireless networks. More recently, we have started to analyze next-generation 6G wireless systems by incorporating machine learning into the network design. It is a great honor to have these efforts and contributions recognized with the IEEE Technological Innovation (Academic) Award,” said Gursoy. “I also would like extend my sincere thanks to Prof. Varshney for nominating me for this award.”