Jubayer Ibn Hamid

I am a researcher at Stanford Artificial Intelligence Laboratory (SAIL), advised by Chelsea Finn. I am studying Mathematical Physics (B.S) and Computer Science (M.S) at Stanford University.

I work in artificial intelligence with a focus on the intersection of reinforcement learning and generative models. I am also interested in pure mathematics such as abstract algebra and algebraic geometry.

I was born and raised in the beautiful city of Dhaka, Bangladesh. I am a diehard fan of FC Barcelona.

CV / Google Scholar / Email / Twitter

Research

My current research focuses on two main areas: offline policy evaluation, specifically policies trained using behavioral cloning or offline RL, and test-time policy decoding methods.

(*) denotes co-first authorship

	Bidirectional Decoding: Improving Action Chunking via Closed-Loop Resampling Yuejiang Liu, Jubayer Ibn Hamid, Annie Xie, Yoonho Lee, Max Du, Chelsea Finn (Under review). ArXiv, 2024. Paper / Website / Code / Blog
	Offline Evaluation of Robotic Manipulation Policies (In preparation).
	Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning Kyle Hsu, Jubayer Ibn Hamid, Kaylee Burns, Chelsea Finn, Jiajun Wu ICML, 2024. Paper / Code
	What Makes Pre-trained Visual Representations Successful For Robust Manipulation? Kaylee Burns, Zach Witzel, Jubayer Ibn Hamid, Tianhe Yu, Chelsea Finn, Karol Hausman CoRL, 2024. Paper / Website

Notes

I am sharing notes on various topics that have fascinated me. These are not meant to be in-depth. Rather, they are meant to cover some of the basic constructions that show up periodically and are also interesting in and of themselves.

Algebraic Geometry. Foundational constructions and results in algebraic geometry (Incomplete).

Algebraic Topology. Foundational constructions - fundamental group, homology and cohomology. (Incomplete, will typeset later).

Whitney's Embedding Theorem and Immersion Theorem. Weak versions of Whitney's Embedding and Immersion theorem, which are often sufficient.

Policy Gradient Methods. Building blocks (including the policy gradient theorems for both episodic and continuing tasks) of policy gradient algorithms.

Teaching

CS 224R - Deep Reinforcement Learning : Head CA. Spring, 2025.

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