CPS-VIDA Lab Members

Jyotirmoy V. Deshmukh

Applies formal methods to cyber-physical systems, embedded control systems, temporal logics, and time-series analysis.

Merve Atasever

Merve completed a double major in Mathematics and Physics at Bogazici University and a master’s degree in Differential Geometry at Istanbul Technical University. Before beginning doctoral studies at USC, she worked as a data scientist on AI projects. Her research interests include reinforcement learning and robotics.

• Multi-agent reinforcement learning
• Representation learning
• Robotics

Sheryl Paul

Sheryl Paul is a Ph.D. candidate interested in policy making, reinforcement learning, and game theory. Her doctoral research focuses on evolutionary games in reinforcement-learning settings for pathfinding and distribution shift, with additional work on societal applications of AI, formal methods, and signal temporal logic.

• Game theory
• Reinforcement learning
• AI in society

Vidisha Kudalkar

Yiqi “Nick” Zhao

Yiqi Zhao is a USC Computer Science Ph.D. student working with Professor Jyo Deshmukh and Professor Lars Lindemann. His research focuses on design, verification, and testing of learning-enabled cyber-physical systems using formal-methods and control-theoretic approaches. Before USC, he studied computer science and mathematics at Vanderbilt University.

• Formal methods
• Cyber-physical systems
• Systems and control theory
• Mathematical optimization

Sam Williams

Sam Williams is a USC Computer Science Ph.D. student and CPS-VIDA Lab member. His research applies game theory to reason about strategic behavior in multi-agent cyber-physical systems. He received a B.S. in Computer Science from the University of Colorado Boulder in 2022.

• Formal methods
• Game theory
• Multi-agent systems
• Optimization

Iurii Biktairov

Edward Kim

Ryan Rubel