Sharan Vaswani

Sharan Vaswani is an Assistant Professor in the School of Computing Science at Simon Fraser University (SFU). His research focuses on designing algorithms for sequential decision-making under uncertainty, stochastic optimization, and their interplay with machine learning generalization. He holds a PhD from the University of British Columbia (2019) and postdoctoral experiences at the University of Alberta and Mila. His academic journey includes MSc (UBC, 2015) and BTech (BITS Pilani, 2012) degrees.

• Education: PhD (UBC, 2019), MSc (UBC, 2015), BTech (BITS Pilani, 2012)
• Postdoctoral Work: University of Alberta (2020-2021), Mila (2019-2020)

Teaching includes courses on Probability and Computing (CMPT 210), Optimization for Machine Learning (CMPT 409/981), and Theoretical Foundations of Reinforcement Learning (CMPT 419/983). His research group focuses on developing scalable optimization algorithms with theoretical guarantees. He advises multiple PhD and MSc students, contributing to areas like constrained MDPs, adaptive learning rates, and reinforcement learning theory.

Research Highlights: Contributions to bandit algorithms, stochastic gradient methods, and reinforcement learning theory. Notable work includes global convergence analysis of policy gradients and variance-reduced optimization frameworks.