Wei Guo 郭纬
🔥About Me
I am a Machine Learning Ph.D. student at Georgia Institute of Technology starting from fall 2023, advised by Professors Yongxin Chen and Molei Tao. Previously, I obtained my Bachelor’s degree in Statistics from the School of Mathematical Sciences, Peking University in 2023, where I was mentored by Professor Cheng Zhang. I was born in Ningbo, Zhejiang Province, P.R. China in 2001, and grew up there until I left for Beijing in 2019.
🔥 CV Please check here for my CV.
🔥 Academic Interests
I am broadly interested in fields ranging from statistics, probability, and machine learning. My current research interests include but are not limited to:
➡️ Statistics and Probability: Theoretical analysis and practical design of sampling algorithms (Markov chain Monte Carlo, non-equilibrium, or learning-based neural samplers); Applied stochastic analysis with applications to optimal transport, stochastic optimal control, and statistical physics.
➡️ Machine Learning: Generative modeling, with a particular focus on (continuous/discrete) diffusion and flow-based models and with applications to vision, language, and sciences.
🔥 Other Interests
I am also interested in languages (including: la langue française (the French language), vernaculars of Chinese and minority languages in China, and linguistics), political science, China’s railway system, civil aviation, architecture, and video games (in particular, action games such as The Last of Us, Assassin’s Creed, and the Метро (Metro) series). I am a fan of LE SSERAFIM. Finally, I am an enthusiast of traveling. Some of my highly recommended destinations that I have been to, and possessing profound historical and cultural heritage, include Hangzhou, Yangzhou, Datong, Macau, Washington, D.C., and my hometown Ningbo.
News
| May 1, 2026 | Four papers accepted to ICML 2026: Discrete Adjoint Schrödinger Bridge Sampler, Enhancing Reasoning for Diffusion LLMs via Distribution Matching Policy Optimization (Spotlight, top 2.2%), Rethinking the Design Space of Reinforcement Learning for Diffusion Models: On the Importance of Likelihood Estimation Beyond Loss Design, and MetaDNS: Enhancing Exploration in Discrete Neural Samplers via Metadynamics. See you in Seoul 🇰🇷! Please let me know if you also plan to go to the LE SSERAFIM concert on July 11 in Incheon! |
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| May 1, 2026 | I will join the Fundamental Generative AI Research (GenAIR) Group at NVIDIA as a research intern during the summer, working with Morteza Mardani and Arash Vahdat. Looking forward to working on cutting-edge research in generative AI at NVIDIA! |