معرفی
Sharan Vaswani is an Assistant Professor in the School of Computing Science at Simon Fraser University (SFU), Canada. His research focuses on designing algorithms for sequential decision-making under uncertainty, stochastic optimization, and their application to modern machine learning, particularly reinforcement learning and generalization analysis.
Education & Career:
- PhD in Computer Science (2015-2018), University of British Columbia (UBC), supervised by Laks Lakshmanan and Mark Schmidt.
- Postdoc (2019-2021) at Mila - Quebec AI Institute with Simon Lacoste-Julien, and University of Alberta with Csaba Szepesvári.
- MSc in Computer Science (2015), UBC, focusing on influence maximization in social networks.
- BS from Birla Institute of Technology and Science, Pilani (2012), followed by research engineering at Siemens Corporate Research.
Research Interests:
- Algorithmic development for decision-making in uncertain environments (bandits, reinforcement learning).
- Stochastic optimization methods with provable guarantees.
- Generalization and theoretical foundations of machine learning models.
Recent Trends in Publications:
- Focus on optimization algorithms (e.g., stochastic gradient methods, line search, momentum techniques) with theoretical analysis.
- Contributions to reinforcement learning, including policy gradient methods and constrained MDPs.
- Exploration of adaptive algorithms for continual learning and over-parameterized models.
Awards:
- Best Paper Honorable Mention (AISTATS 2022).
- Best Paper Award (2nd IEEE International Conference on Parallel Distributed and Grid Computing 2012).
Research Group: Leads a team at SFU focused on machine learning optimization and decision-making systems. Active in organizing workshops at NeurIPS and ICML on optimization and reinforcement learning theory.
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