Michael Tang

Ph.D. Student · Electrical and Computer Engineering · UC San Diego
Portrait of Michael Tang

Hello! I am a PhD student in Electrical and Computer Engineering at UC San Diego, advised by Jorge Poveda, and I sometimes work with Miroslav Krstic. I received my B.S. degrees in Electrical Engineering and Applied Math from UCSD in 2023. I am grateful to be supported by the NSF Graduate Research Fellowship.

My research interests are broadly at the intersection of control, optimization, game theory, dynamical systems, and their applications. My work develops rigorous algorithms for multi-agent decision-making, bandit learning, feedback optimization, and the stability analysis of large-scale systems. Applications include robotics, aerospace systems, cyber-physical systems, and traffic networks.

Selected publications

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  1. Figure from A Lyapunov-Based Small-Gain Theorem for Fixed-Time ISS: Theory, Optimization, and Games
    journal TAC
    A Lyapunov-Based Small-Gain Theorem for Fixed-Time ISS: Theory, Optimization, and Games
    M. Tang, M. Krstic, and J. I. Poveda
    IEEE Transactions on Automatic Control, Feb 2027
  2. Figure from A Separation Principle for Stochastic Feedback Optimization
    journal L-CSS
    A Separation Principle for Stochastic Feedback Optimization
    M. Tang, M. Abdelgalil, and J. I. Poveda
    IEEE Control Systems Letters, Jun 2026
  3. Figure from Deception in Nash Equilibrium Seeking
    journal TAC
    Deception in Nash Equilibrium Seeking
    M. Tang, U. Javed, X. Chen, M. Krstic, and J. I. Poveda
    IEEE Transactions on Automatic Control, Dec 2025
  4. Figure from The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning
    conference CDC
    The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning
    M. Tang, M. Abdelgalil, and J. I. Poveda
    IEEE Conference on Decision and Control, Dec 2026