معرفی
Yexiang Xue is an Assistant Professor in the Department of Computer Science at Purdue University, part of the College of Science. He joined Purdue in Fall 2018. His research focuses on integrating machine learning and probabilistic reasoning to enable optimal decision-making in high-dimensional, uncertain environments. Key areas include computational sustainability, materials science, robotics, and medical AI.
Education:
- PhD in Computer Science, Cornell University (2018), advised by Carla Gomes and Bart Selman.
- B.Sc. in Computer Science, Peking University, China (2011).
Research Interests:
Xue develops cross-cutting computational methods for scientific discovery, constraint-embedded machine learning, and AI-driven sustainability. His work spans symbolic regression, probabilistic models, and applications in robotics, healthcare, and materials science. Recent efforts include end-to-end physics model discovery and integrating decision diagrams into neural networks.
Awards:
- NSF CAREER Award (2024).
- IAAI Innovative Application Award (2017) for Phase-Mapper AI platform in materials discovery.
Advising & Grants: Mentored multiple undergraduates (e.g., Luming Tang, Runzhe Yang) pursuing graduate studies. His NSF CAREER grant supports AI-driven scientific discovery.
Teaching & Service: Taught courses like Statistical Machine Learning (CS 578). Serves on AAAI, UAI, and IJCAI program committees. Media coverage includes NSF News, Science, and MIT Technology Review.
