About - Rabiul Awal

I work on generative models, world models, and reinforcement learning. I'm a PhD student at Mila and University of Montreal, advised by Aishwarya Agrawal. This summer I'll join Qualcomm Research in Amsterdam as an intern.

Research

The central question I work on: can a model learn to simulate the world well enough to act in it? We are entering the era of experience, where the data that matters most is not human-labeled but agent-generated.

My current research focuses on diffusion and flow models as world models. These models are expressive, but sampling from them is slow, which makes them nearly unusable for planning. I work on making them fast, temporally consistent, and structured enough to support a control loop. The adjacent question is representation: what does a model need to internalize about the world for its latent space to be useful for downstream decision-making?

See Google Scholar for a full list. ^*denotes equal contribution.

Grounding Computer Use Agents on Human Demonstrations

Aarash Feizi, Shravan Nayak, Xiangru Jian, Kevin Qinghong Lin, Kaixin Li, Rabiul Awal + 11 others

ICLR'26

Paper

The Promise of RL for Autoregressive Image Editing

Saba Ahmadi*, Rabiul Awal*, Ankur Sikarwar*, Amirhossein Kazemnejad*, Ge Ya Luo, Juan Rodriguez, Sai Rajeswar, Siva Reddy, Chris Pal, Benno Krojer, Aishwarya Agrawal

NeurIPS'25

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Rendering-Aware Reinforcement Learning for Vector Graphics Generation

Juan A. Rodriguez^∗, Haotian Zhang^∗, Abhay Puri, Aarash Feizi, Rishav Pramanik, Pascal Wichmann, Arnab Mondal, Mohammad Reza, Rabiul Awal + 6 others

NeurIPS'25

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