Zewei Zhang

I am Zewei Zhang, a PhD candidate in Electrical & Computer Engineering at McMaster University, supervised by Prof. Jun Chen. I am currently an Applied Scientist Intern at Amazon in Toronto and was a visiting PhD student at the University of British Columbia with Prof. Renjie Liao.

My research lies at the intersection of generative modeling, video and trajectory prediction, controllable editing, and learning-guided search. I am interested in models that reason over motion, structure, and time, and in evaluation methods that reveal how these models behave beyond short, isolated examples.

I am increasingly interested in AI systems that learn from experience, beyond pretraining, retrieval, or static supervision. I view generation, evaluation, and search as an iterative feedback loop, where model outputs, observed failures, and interactions with the environment inform future improvement. This motivates my interest in memory, adaptation, and self-improving systems that turn repeated experience into reusable abstractions, better control, and more reliable decision-making.

• May 2026 Joined Amazon in Toronto as an Applied Scientist Intern, focusing on human-guided video-to-video motion editing.
• Mar 2026 Released TrajLoom, a dense future trajectory generation framework for long-horizon video modeling.
• Jan 2026 Boolean Satisfiability via Imitation Learning was accepted to ICLR 2026.
• Jun 2025 Began a visiting PhD position at UBC with Prof. Renjie Liao, working on trajectory-based video generation and evaluation.
• Mar 2025 GoodDrag was accepted to ICLR 2025.