Jubayer Ibn Hamid

I am an incoming PhD student at Stanford University. Previously, I studied mathematical physics as an undergraduate at Stanford University.

I work in artificial intelligence at the intersection of reinforcement learning and generative models. I am also interested in pure mathematics such as abstract algebra and category theory.

My research is advised by Chelsea Finn and Dorsa Sadigh in Stanford Artificial Intelligence Laboratory (SAIL).

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Research

I am currently interested in deep exploration methods for online reinforcement learning fine-tuning, spanning both language models and embodied agents. My research also focuses on test-time decoding from complex, multimodal policies and training robotic policies with long context. Additionally, I am interested in understanding what kinds of data to scale for improved generalization in robot learning.

Publications:

(*) denotes co-first authorship

Notes

Here are some introductory 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.

Talks

Bidirectional Decoding. OpenAI. 25th February, 2025.

Teaching

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

CS 229 - Machine Learning : CA. Winter, 2025.


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