Position Title
Navid Mojahed
Position Title
Navid Mojahed
Bio
Navid’s research focuses on developing data-driven optimization techniques to approximate Nash equilibrium in multi-agent systems.
His work involves leveraging game-theoretic frameworks to model strategic interactions and decision-making under uncertainty. By employing computationally efficient methods, he transforms complex equilibrium-finding problems into tractable optimization processes, ensuring robust and adaptive control strategies for dynamic systems.
Education and Degree(s)
- Ph.D. in Applied Mathematics at University of Mazandaran, Babolsar
- M.Sc. Amirkabir University, Tehran
- B.Sc. in Mechanical Engineering at Isfahan University of technology, Isfahan
Publications
- Inverted Gaussian Process Optimization for Nonparametric Koopman Operator Discovery
- Optimal Modified Feedback Strategies in LQ Games under Control Imperfections