My name is Haoyang (pronounced as “Hau Yeung”). I am currently a PhD candidate at the School of Mechanical Engineering, Purdue University, advised by Prof. Guang Lin.

I study Generative Modeling and Reinforcement Learning (RL) from a probabilistic modeling perspective. My interests include Large Language Models (LLMs), continuous and discrete diffusion, RL, and sampling/optimization methods that improve latency and robustness. My goal is to build fast and reliable LLMs.

Research Interests

• Generative Models
• Discrete Diffusion Large Language Models
• Reinforcement Learning (Thompson Sampling)
• Markov Chain Monte Carlo

News

• [Sep/2025] 🔥Feel the Ultra-Fast Language Generation in our latest work (60× faster than ARMs): Discrete Diffusion Divergence Instruct
• [Oct/2024] Student Travel Award at 2024 Mathematical and Scientific Foundations of Deep Learning Annual Meeting
• [Aug/2024] Student Travel Award at 2024 SIAM Conference on Mathematics of Data Science (MDS24)
• [Jul/2024] Gave a talk at the Crunch Seminar, Brown University
• [May/2024] 1 paper was accepted by ICML 2024
• [Apr/2024] Passed the preliminary exam and became a Ph.D. candidate
• [Apr/2024] Student Travel Award at the ICERM workshop about Nonlocality and Interacting Particle Systems
• [Jan/2024] 1 paper was accepted by AISTATS 2024
• [Dec/2023] 1 paper was accepted by Journal of Computational Physics
• [Sep/2023] Student Travel Award at 2023 Mathematical and Scientific Foundations of Deep Learning Annual Meeting
• [May-Jul/2023] Givens Associates at Argonne National Laboratory
• [Sep/2022] 1 paper was accepted by NPJ Digital Medicine

Services

Reviewers: ICLR, ICML, NeurIPS, AISTATS, AAAI

Contact

• lastname+528 at purdue dot edu
• 516 Northwestern Ave, West Lafayette, IN 47906