Hi, I am Abdus Salam Azad, a final-year Ph.D. student at UC Berkeley (expected graduation August 2024). I have been incredibly fortunate to be advised by Prof. Ion Stoica. I also have the privilege of collaborating with Prof. Pieter Abbeel from UC Berkeley and Izzeddin Gür & Aleksandra Faust from Google DeepMind. My research has been funded by Google. Inc. & BAIR Commons Research initiative. 

I am passionate about designing intelligent autonomous agents to solve complex and realistic tasks that require sequential decision making. During my Ph.D., I focused on Environment Generation & Curriculum Learning methods that algorithmically generate diverse training environments (e.g., learning scenarios) to improve the generalization of agents trained with Reinforcement Learning while improving sample efficiency. Recently, I have been focusing on designing 'agentic' workflows to solve complex sequential decision making tasks (e.g. web navigation) with multi-modal Large Language Models. In this era of rapidly advancing multi-modal LLM agents and their increasing application demand, I believe it is crucial to develop principled methods and frameworks to ensure these agents are safe, responsible, and high-performing.
 
Previously, I completed my Bachelor of Science in July 2014 and Masters of Science in January 2017 from CSE, BUET. During my M.Sc., I worked on improving the exploration-exploitation tradeoff of Memetic Algorithms—a variant of Genetic Algorithms—to solve complex real-world Combinatorial Optimization problems.

Please find my resume here.

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