معرفی
Xujie Si is an Assistant Professor in the Department of Computer Science at the University of Toronto. He is also a faculty affiliate at the Vector Institute and an affiliate member at Mila - Quebec AI Institute, holding a Canada CIFAR AI Chair. Previously, he served as an Assistant Professor at McGill University's School of Computer Science.
Education:
- Ph.D., Computer and Information Science, University of Pennsylvania (advised by Mayur Naik)
- M.S., Computer Science, Vanderbilt University
- B.E. (with Honors), Nankai University
Research Focus: His work bridges AI and program reasoning, emphasizing the integration of statistical and logical methods. Key areas include:
- Static analysis and verification using deep learning/reinforcement learning
- Neuro-symbolic systems for urban simulation (e.g., LogiCity)
- Automated theorem proving via LLMs and symbolic reasoning
- Program repair and compiler fuzzing
Recent Article Trends: Recent work focuses on synergizing LLMs with symbolic reasoning (e.g., Olympiad inequality proving), advancing SAT solving with graph neural networks, and applying neuro-symbolic methods to Euclidean geometry formalization.
Awards:
- Canada CIFAR AI Chair (2023)
Lab/Teams: Leads research teams exploring program analysis, neuro-symbolic AI, and formal verification at the University of Toronto and Vector Institute.
