Find Academic Supervisors

Bingzhe LiView profile

Assistant Professor

• DNA Storage Systems
• Machine Learning Systems
• Low-Power Computing
• +3 more

Dr. Bingzhe Li is an Assistant Professor in Computer Science at UT Dallas' Erik Jonsson School of Engineering. His research at the Lab for Intelligent Storage and Computing (Lab4ISC) focuses on DNA storage systems, machine learning infrastructure, and energy-efficient computing architectures. Awarded the NSF CAREER Award (2025) and recognized for Best Paper nominations at leading conferences. Research spans DNA storage capacity optimization, reinforcement learning for hybrid SSDs, Kubernetes storage optimization, and stochastic computing architectures. Recent publications demonstrate innovations in out-of-core graph processing and blockchain storage systems. Leads multiple NSF/NASA-funded projects on DNA storage and convertible SSDs. Teaches Digital Logic and Computer Architecture courses. Supervises 8 PhD students and 3 master's candidates in storage systems and low-power computing research.

Piotr GmytrasiewiczView profile

Associate Professor

• Artificial Intelligence
• Multiagent Systems
• Decision Theory
• +7 more

Piotr Gmytrasiewicz is an Associate Professor at the Department of Computer Science, University of Illinois at Chicago (UIC). He leads the Multiagent Systems Group within the Artificial Intelligence Laboratory at UIC. His research focuses on rationality in artificial agents , particularly in environments with multiple interacting agents. Key areas include Interactive Decision-Making Bayesian Modeling for Agent Communication Recursive Belief Frameworks Time Pressure and Computational Trade-offs Evolution of Agent Communication Languages Dynamic Resource Allocation His recent work examines the rationality of insincere communication and methods to discount potentially insincere information. Past projects include modeling emotions in agent design and developing decision-theoretic approaches to game theory. He has secured funding from prestigious institutions such as the National Science Foundation (NSF) , Office of Naval Research (ONR) , and DARPA . Current and past projects emphasize Automated Linguistic Competence Evolution Emergent Communication Protocols Scalable Multiagent Learning Strategic Coordination under Uncertainty He earned his Ph.D. from the University of Michigan, Ann Arbor (1992) and has previously collaborated with the Department of Computer Science and Engineering (CSE) at the University of Texas at Arlington on DARPA-funded research.

Erman AcarView profile

Assistant Professor

• Neuro-Symbolic AI
• Causal Inference
• Explainable AI
• +4 more

Erman Acar is an Assistant Professor for Explainable AI in Finance at the University of Amsterdam, affiliated with the Socially Intelligent Artificial Systems (SIAS) group at the Informatics Institute (IvI) and the Cognition, Language and Computation (CLC) lab at the Institute of Logic, Language and Computation (ILLC). His research focuses on Neuro-Symbolic AI architectures that integrate machine learning with symbolic approaches (logical or causal) to enhance reasoning and explainability in single/multiagent scenarios, applied to financial services. Education : PhD in Computer Science (University of Mannheim, 2017), MSc in Computational Logic (TU-Wien/TU-Dresden, 2012). Previous Roles : Postdoctoral researcher at VU Amsterdam (2018-2021), Leiden University (2021-2022). Research Trends : His recent work emphasizes causal discovery via meta-reinforcement learning, aligning with his Neuro-Symbolic AI and XAI themes. A PhD position (2022) highlights his focus on deploying these approaches for fairness and transparency in fintech. Teaching : Co-teaches the course Interpretability & Explainability in AI (University of Amsterdam, 2023) and leads the AI4Fintech initiative. Labs & Teams : Collaborates with the SIAS group (IvI), CLC lab (ILLC), and the upcoming AI4Fintech hub in Amsterdam.

Asieh Salehi FathabadiView profile

Lecturer

• Formal Methods
• Autonomous Systems
• Responsible AI (Socio-technical)
• +3 more

Dr. Asieh Salehi Fathabadi is a Lecturer (Assistant Professor) in the Cyber-Physical Systems (CPS) group at the University of Southampton, UK. She specializes in formal methods for software engineering, with a focus on Event-B methodology for designing safe and secure systems. Her research addresses challenges in autonomous systems, responsible AI, and human-AI trust dynamics. She leads the Verifiably Safe and Trusted Human-AI Systems (VESTAS) and HANA-HAIP projects as Principal Investigator and contributes to initiatives like HD-Sec and HICLASS . Her work integrates formal verification into critical system development, emphasizing security and safety. Recent publications explore exception handling in secure hardware (CHERI), socio-technical trust frameworks for defense systems, and human intervention in self-driving vehicles. She supervises two PhD students in Computer Science and actively participates in the Rodin formal methods community. Dr. Salehi Fathabadi has over 13 years of research experience, applying formal methods to aerospace systems, embedded software, and cybersecurity. Her interdisciplinary approach bridges theoretical rigor with practical engineering solutions for modern complex systems.

Franco ZAMBONELLIView profile

Professor

• Pervasive Computing
• IoT (Internet of Things)
• Multiagent Systems
• +7 more

Franco ZAMBONELLI is a Full Professor in the Department of Engineering Sciences and Methods at the University of Modena and Reggio Emilia. He holds positions in both the Reggio Emilia and Modena campuses, offering courses such as Software Engineering and Distributed Artificial Intelligence. His research focuses on IoT, pervasive computing, multiagent systems, and self-organization in distributed systems, with applications in smart cities, healthcare, and mobility. He leads projects like FLUIDWARE (PRIN 2017) and CONNECARE (H2020), exploring adaptive IoT systems and integrated healthcare solutions. ZAMBONELLI is an IEEE Fellow, ACM Distinguished Scientist, and member of the Academia Europaea. His work bridges theory and practice, emphasizing software engineering methodologies for IoT and agent-based systems. Education: Not explicitly detailed in provided texts. Research Grants: FLUIDWARE (2019-2022), CONNECARE (2016-2019). His research interests include causal discovery in pervasive environments, reinforcement learning for cybersecurity, and digital twin technologies. He contributes to editorial boards of journals like ACM Transactions on Autonomous and Adaptive Systems and IEEE Technology and Society Magazine. His teaching spans software engineering, distributed AI, and IoT-oriented methodologies. The Agents and Pervasive Computing Lab (agentgroup.unimore.it) is a focal point for his experimental work. Professional memberships include IEEE, ACM, and the Italian Association for Artificial Intelligence. Recent achievements include successful final reviews for CONNECARE and advancements in fluidware programming paradigms.

Eric MatsonView profile

Professor

• Multiagent Systems
• Robotics
• Software Engineering
• +3 more

Eric T. Matson is a Professor in the Department of Computer and Information Technology at Purdue University's Purdue Polytechnic Institute. He also holds a non-tenure-track Professorship at Dongguk University's Department of Computer Science and Engineering in Seoul, South Korea, and serves as an International Faculty Scholar at Kyung Hee University. His roles include directing the RICE Research Center and co-founding the M2M Lab. Education: PhD (Computer Science), University of Cincinnati (2008) MSE (Software Engineering), Kansas State University (2002) MBA (Operations Management), Ohio State University (1993) BS (Computer Science), Kansas State University (1988) Research Interests: Dr. Matson focuses on Multiagent Systems, Robotics, Software Engineering, and STEM Education. His work emphasizes organizational models for autonomous systems and outreach to underserved communities. Recent projects include sensor networks, cooperative robotics for search and rescue, and global academic collaborations through programs like the Korean Square Initiative. Publications: His research spans agent coordination, organizational transition algorithms, and robotics education, with notable contributions to journals like Autonomous Agents and Multiagent Systems and conferences such as AAMAS and SPIE. Awards: Ho Award for Outstanding Undergraduate Teaching (2010, 2011) 2024 Outstanding Leadership in Globalization Award Grants & Collaboration: Leads initiatives like the Purdue-Dongguk Korean Square Program and the POSTECH Graduate Degree Collaboration. Engages in global partnerships to advance AI and robotics education. Labs/Teams: Director of the RICE Research Center and co-founder of the M2M Lab, focusing on multiagent systems and robotic applications.

• Artificial Intelligence
• Image Processing
• Narrative Planning
• +3 more

Associate Professor Julie Porteous is affiliated with the School of Computing Technologies at RMIT University. Her research focuses on Artificial Intelligence applications including narrative planning, medical image processing, and human-agent interaction. She supervises research projects in areas such as dynamic transportation networks, medical imaging frameworks, and explainable AI in planning systems. Her work combines AI techniques with storytelling, medical diagnostics, and collaborative decision-making. Notable contributions include SellaMorph-Net for medical image segmentation and advancements in automated narrative generation systems. She actively contributes to conferences like AAMAS and AAAI, publishing on topics ranging from story sifting algorithms to intention communication in multiagent environments. Dr. Porteous collaborates on projects involving interactive narrative platforms, virtual urban environments, and neurofeedback systems for adaptive storytelling. She maintains an ORCID profile (0000-0003-4618-2359) and is open to supervising PhD/Masters students in her research areas.

Vasilis GkatzelisView profile

Associate Professor

• Algorithmic Mechanism Design
• Multiagent Resource Allocation
• Approximation Algorithms
• +4 more

Vasilis Gkatzelis is an Associate Professor in the Department of Computer Science at the College of Computing & Informatics, Drexel University. He joined the faculty in 2016 and has since been actively contributing to theoretical computer science research with a focus on algorithmic game theory and optimization. His educational background includes a PhD and MSc in Computer Science from New York University's Courant Institute of Mathematical Sciences, and a Diploma in Computer Engineering and Informatics from the University of Patras. Gkatzelis' research lies at the intersection of algorithms and economics, particularly in designing efficient and fair mechanisms for resource allocation among self-interested agents. His work in approximation algorithms and multiagent systems has been supported by national recognition such as the NSF CAREER award. The trends in his research, though not detailed in specific publications here, center on foundational problems in algorithmic mechanism design, with implications for distributed computing, AI, and economic systems. NSF CAREER Award He has advised students and mentored researchers in theoretical computer science, though specific names are not listed. His prior experience includes significant research grants and collaborations through postdoctoral work at UC Berkeley (Department of EECS, International Computer Science Institute, and Simons Institute) and Stanford University, as well as industrial research roles at Microsoft Research, HP Labs, and Google, indicating a strong record of funded and applied research. Gkatzelis has been affiliated with elite research labs including the Simons Institute for the Theory of Computing and the International Computer Science Institute at UC Berkeley, contributing to collaborative, interdisciplinary efforts in theoretical computer science and AI.

• Theoretical Computer Science
• Algorithmic Game Theory
• Artificial Intelligence
• +9 more

Simina Brânzei is an Associate Professor in the Department of Computer Science at Purdue University. She joined Purdue in Spring 2018, after postdoctoral positions at Hebrew University of Jerusalem and the Simons Institute for the Theory of Computing at UC Berkeley. Her research spans theoretical computer science and artificial intelligence, focusing on algorithmic game theory, computational complexity, fair division, and the intersection of dynamical systems with optimization. PhD in Computer Science from Aarhus University (2015), advised by Peter Bro Miltersen Undergraduate and Master's degrees from University of Waterloo Research Interests : Her work addresses algorithmic game theory, fair division, market and auction design, learning dynamics, and computational complexity. She explores how strategic behavior, fairness, and dynamics interact in resource allocation problems, with applications to economics and multiagent systems. Publication Trends : Recent articles examine lower bounds for local search algorithms, fair division protocols, market equilibrium computation, and learning in competitive environments. Her work often bridges theoretical computer science with economic models, emphasizing mathematical rigor and interdisciplinary applications. Scientific Awards : NSF CAREER Award IBM Ph.D. Fellowship Google Anita Borg Memorial Scholarship Advising and Grants : She mentors graduate students in theoretical computer science and algorithmic game theory. Her research is supported by grants from NSF and prior funding from IBM and Google during her PhD.

• Algorithmic Game Theory
• Fair Division
• Computational Economics
• +3 more

Dr. Georgios Birmpas is a researcher specializing in algorithmic game theory, computational economics, and fair division. He currently serves as Module Co-ordinator for Algorithmic Game Theory (COMP559) and Computational Game Theory and Mechanism Design (COMP326) at an institution not explicitly named. His research focuses on fairness and efficiency in resource allocation problems, often intersecting computer science, economics, and multiagent systems. Key research areas: Algorithmic Fairness Submodular Optimization Strategic Agent Modeling Distortion in Voting Systems Recent contributions include: Fair multiobjective submodular function maximization Existence of approximate equilibria in resource allocation Two-query distortion analysis in matching problems Interdependent value models in fair division His work has appeared in venues such as the International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS) and journals like Mathematics of Operations Research and SIAM Journal on Discrete Mathematics . Collaborators include researchers from institutions across Europe, focusing on theoretical and applied aspects of algorithmic fairness.

• Virtual Reality
• Scientific Visualization
• Computer Graphics
• +4 more

Aleksandr Zagarskikh is an Associate Professor at the Game Development School of ITMO University, specializing in virtual reality, scientific visualization, and high-performance computing. He has led projects in quantum chemistry visualization, flight simulators, and urban simulation technologies. Developed real-time graphics systems for ultra-realistic image synthesis Created high-performance network protocols for distributed visualization Current research focuses on big data decision-making in finance and multiscale urban modeling His work spans predictive modeling, GPU optimization, and cloud-based infrastructure visualization, with publications in Procedia Computer Science. He teaches courses in game technologies, VR, and scientific computer graphics.

• Artificial Intelligence
• Knowledge Graphs
• Natural Language Processing
• +5 more

Tim Finin is a Professor in the Computer Science and Electrical Engineering department at the University of Maryland, Baltimore County (UMBC), where he serves as Director of the UMBC Center for Artificial Intelligence and holds the Willard and Lillian Hackerman Chair in Engineering. With over 50 years of experience, his research focuses on knowledge graphs, natural language processing, machine learning, and applications to information systems security and social media. Education: Ph.D. in Computer Science from the University of Illinois (1980), M.S. in Computer Science (1977), and S.B. in Electrical Engineering (1971) from MIT Current Roles: Director, UMBC Center for AI; Hackerman Chair; Professor, UMBC Previous Roles: Adjunct Associate Professor at University of Pennsylvania; positions at Unisys, JHU HLT CoE, and MIT AI Lab Research Interests: Dr. Finin's work spans Knowledge graphs and semantic web technologies Natural language processing for cybersecurity Machine learning for data assimilation Privacy and security in distributed systems Social media analysis Quantum computing applications Recent Grant Trends: His funded research includes projects on knowledge graph optimization, AI cybersecurity, semantic manufacturing standards, and quantum machine learning. Grants from DoD, NSF, NIST, and industry partners like IBM and Google demonstrate his interdisciplinary impact. Scientific Honors: ACM Fellow (2018) AAAI Fellow (2013) IEEE Technical Achievement Award (2009) UMBC Presidential Research Professor (2012) Fellow, Foundation for Intelligent Physical Agents (1997) Academic Leadership: Dr. Finin has chaired UMBC's Computer Science department, served on the Computing Research Association board, and held editorial roles including Editor-in-Chief of the Journal of Web Semantics (2005-2016).

• Control Systems
• Cyber-Physical Systems Security
• Power Systems Resilience
• +3 more

Kamil Hassan is a Doctoral student and Researcher at KTH Royal Institute of Technology, affiliated with the Division of Decision and Control Systems. His work focuses on securing cyber-physical infrastructure through advanced control methodologies. His research spans Control Systems , Cyber-Physical Security , and Power Systems Resilience , with emphasis on mitigating attacks in time-critical networks. Key contributions include finite-time control barrier functions for power inverters and randomized detector tuning for attack impact reduction. His methodologies integrate hardware-in-the-loop validation with theoretical guarantees. Recent publications (2021–2025) reveal a trajectory toward resilient control architectures for energy systems, blending multiagent consensus theory with security-aware design. Work on power inverter networks dominates his output, addressing grid stability under cyber threats through novel barrier function frameworks and simulation-validated approaches. Hassan serves as course assistant for Cyber-Physical Security in Time-Critical Systems (EL2850) and operates within KTH's Decision and Control Systems division, contributing to hardware-in-the-loop testing environments for critical infrastructure protection.

Munindar SinghView profile

Professor

• Artificial Intelligence
• Multiagent Systems
• Sociotechnical Systems
• +5 more

Munindar P. Singh is the SAS Institute Distinguished Professor of Computer Science at North Carolina State University . He serves as a core faculty member in the Science of Security Lablet and contributes to initiatives in responsible computing and ethical AI . His research spans artificial intelligence , software engineering , and computing ethics . Education: Ph.D. in Computer Sciences from University of Texas at Austin (1993) B.Tech. in Computer Science and Engineering from Indian Institute of Technology, Delhi (1986) Research Focus: Dr. Singh's work centers on trustworthy AI and sociotechnical systems , with key contributions in Multiagent systems and BDI architectures Defensive cyberdeception using hypergame theory Normative systems for blockchain applications Equitable transportation systems via AI Service-oriented computing and protocol engineering Scientific Recognition: Fellow of AAAI , IEEE , and ACM Recipient of NSF CAREER Award and multiple industry awards Editor-in-Chief of ACM Transactions on Internet Technology Grant Activities: Currently leading several major NSF-funded projects including: SCC: Serving Households in Food Insecurity ($2.018M) RI: Foundations of Ethics for Multiagent Systems ($500K) Science of Security Lablet ($3.65M)

Junsoo LeeView profile

Assistant Professor

• Control Theory
• Stochastic Systems
• Multiagent Networks
• +3 more

Junsoo Lee is an Assistant Professor in the Departments of Mechanical and Aerospace Engineering at the University of South Carolina's Molinaroli College of Engineering and Computing. His research centers on stability theory, stochastic systems, and distributed control of multiagent networks, with applications in aerospace systems and large-scale dynamical networks. Education credentials: Ph.D. in Aerospace Engineering, Georgia Institute of Technology (2022) M.S. in Mathematics, Georgia Institute of Technology (2021) M.S. in Aerospace Engineering, Seoul National University (2018) B.S. in Mechanical and Aerospace Engineering, Seoul National University (2016) Dr. Lee's research develops novel frameworks for finite-time and fixed-time stability in stochastic systems, creating control architectures based on thermodynamic principles. His publications demonstrate consistent focus on semistability, network consensus protocols, and optimal control of nonlinear discrete-time systems across deterministic and stochastic domains. Awards include multiple IEEE travel grants and the 2021 Faces of Inclusive Excellence honor. He serves as editorial reviewer for leading journals including IEEE Transactions on Automatic Control and Automatica, and participates in professional societies including IEEE, AIAA, and ASME.