Hello! Husky here! I'm a MSML student at CMU Locus Lab. Throughout my research journey, I've explored a variety of topics. Currently, my primary focus is on generative world modeling, where I have been fortunate to work closely with Professor Zhiting Hu and Professor Yilun Du on advancing the capabilities of world models. Previously, I collaborated with my amazing advisor Jiaqi W. Ma at the TRAIS Lab, focusing on dataset curation using LLM agents. I also gained valuable research experience in AI interpretability under Professor Quanshi Zhang's XAI Lab.
Within world modeling, I'm particularly(currently) interested in the following directions:
- How can we enable world models to operate effectively in long-sequence scenarios? This includes both looking ahead (simulating long trajectories) and looking back (designing effective memory mechanisms).
- How can we make world models real-time interactive? This is especially crucial for real world applications, and I find both the mathematical and ML systems perspectives fascinating.
- How can we make world models more physically grounded? I'm excited to explore data-driven approaches, RLHF, and other emerging methods.
News
- 2025/11Tech report of PAN World Model is released! 🎉
- 2025/07Magica, a Generative World Engine, is now available online! 🎉
- 2025/05DCA-Bench has been accepted to KDD 2025 DB-Track as an oral paper! See you in Toronto 🎉
Selected Works
Refer to Research page for complete list.
PAN: A World Model for General, Interactable, and Long-Horizon World Simulation
PAN brings imagination to life — fusing language, action, and vision to simulate the world's evolution with stunning realism and consistency.

Awards & Scholarships
National Scholarship
Rui Yuan Hong Shan Scholarship (Top 2%, SJTU)
Shao Qiu Scholarship (Top 4%, SJTU)
Meritorious Winner of MCM/ICM


