Hi! I am a PhD student in the Computer Science Department at Carnegie Mellon University, where I'm very lucky to be advised by Professor Nicholas Boffi.
My research is on generative modeling, where I have lately been focusing on diffusion and flow-based models, particularly building efficient and controllable models in vision and language. In general, I am interested in understanding reasoning in generative models, representations, and multimodal intelligence. I also like to think about creativity in generative models and how humans interface with AI, e.g., via agent harnesses and workflows.
Previously, I received my B.S. at Caltech, where I researched quantum computing and online algorithms under the mentorship of Profs. John Preskill, Hsin-Yuan Huang, Adam Wierman, and Nicolas Christianson.
Outside my PhD, I can be found playing tennis, watching my agents go brrrr, or attempting new hobbies. Recently, I learned some photography, guitar, and dance.
I'm happy to chat about research, potential collaborations, or advice on doing a PhD / getting into AI research. Feel free to reach me at jerryhua [at] andrew [dot] cmu [dot] edu.
Publications
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How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance
Jerry Y. Huang, Justin Lin, Sheel Shah, Kartik Nair, Nicholas M. Boffi
ICML 2026 -
Flow Map Language Models: One-step Language Modeling via Continuous Denoising
Chanhyuk Lee, Jaehoon Yoo, Manan Agarwal, Sheel Shah, Jerry Huang, Aditi Raghunathan, Seunghoon Hong, Nicholas M. Boffi, Jinwoo Kim
Preprint, 2026 -
Sublinear iterations can suffice even for DDPMs
Matthew S. Zhang, Stephen Huan, Jerry Huang, Nicholas M. Boffi, Sitan Chen, Sinho Chewi
Preprint, 2025 -
Predicting adaptively chosen observables in quantum systems
Jerry Huang, Laura Lewis, Hsin-Yuan Huang, John Preskill
PRX Quantum 7, 010347 (2026) -
Online algorithms with uncertainty-quantified predictions
Bo Sun, Jerry Huang, Nicolas Christianson, Mohammad Hajiesmaili, Adam Wierman, Raouf Boutaba
ICML 2024