Fathima Zarin Faizal

Fathima Zarin Faizal is a graduate student in electrical engineering and computer science, where she is advancing theoretical foundations for decision-making under uncertainty. Her research focuses on decentralized learning in multi-agent systems, with a particular emphasis on game-theoretic interactions and stochastic optimization. As a MathWorks Fellow, she will investigate efficient but meaningful learning dynamics for strategic agents in complex, networked environments. Currently, her work provides the first-known polynomial-time finite-sample guarantees for convergence to approximate Nash equilibria in certain zero-sum and polymatrix games using best-response type dynamics. Fathima uses MATLAB extensively to validate her theoretical results with Monte Carlo simulations; its graph theory toolbox and fast matrix computations enable her to run smoother simulations. Her work could inform the design of robust learning protocols in social networks and distributed systems. Fathima hopes to deepen our understanding of strategic learning and to shape how large-scale, uncertain environments are modeled and managed.