Scholar
Ying Sheng
Google Scholar ID: xMhGYpgAAAAJ
xAI
Citations & Impact
Citations
17,969
H-index
22
i10-index
27
Publications
20
Co-authors
6
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Received the a16z Open Source AI Grant (2023, 2025), ML Commons Machine Learning and Systems Rising Stars (2023), Human-Centered Artificial Intelligence (HAI) Graduate Fellowship Program at Stanford University (2022-2023), Best Tool Paper Award at the 28th International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS) (2022), Best Paper Award at the International Joint Conference on Automated Reasoning (IJCAR) 2020, School of Engineering Fellowship at Stanford University (2018-2019), ACM International Collegiate Programming Contest (ICPC) World Finalist (2018), Champion in ACM ICPC Greater New York (2017), Course Assistant Fellowship (<2%) at Columbia University (2017), Silver Medal in National Olympiad in Informatics (NOI) 2011, China. Also served as a teaching assistant multiple times.
Research Experience
- Was a member of technical staff at xAI, co-led the inference team (2024.10-2025.08); a visiting researcher at UC Berkeley, working with Ion Stoica and Joseph E. Gonzalez (2023-2024); a Ph.D. resident at X, the moonshot Factory (the team graduated to Labs@Google during residency), working on AI for Code with Michele Catasta (2022); a research intern at Facebook Novi, working on smart contract verification with Prof. David Dill (2021); a quantitative software engineer at Two Sigma (2018); and a research intern at Microsoft Research Asia, working with Chin-Yew Lin (2015). Involved in several open-source projects such as SGLang, S-LoRA, cvc5, FlexGen, FastChat, and Vicuna.
Education
- Received a B.E. in Computer Science and Technology from Shanghai Jiao Tong University (ACM Honored Class) in 2016; an M.S. in Computer Science from Columbia University in 2017; and a Ph.D. in Computer Science at Stanford University (Centaur), advised by Clark Barrett.
Background
- Research Interests: Large Language Models, Machine Learning Systems, Machine Learning for Programs, Formal Methods, Automated Reasoning, Code Generation. Likes collaboration and competition.
Miscellany
- Founded LMSYS as a non-profit corporation to incubate early-stage open-source projects.
