CV
Education
- Ph.D. in Computer Science, University of Utah, 2024
- M.S. in Computer Science, Temple University, 2019
- B.S. in Statistics and Computer Science (double degree), University of Science and Technology of China (USTC), 2018
Work experience
- Summer 2024 - Present: Senior Researcher
- Microsoft Research Asia
- Research focus: Bayesian machine learning, tensor learning, physics-informed machine learning
- 2019 - 2024: Ph.D. Student
- University of Utah, School of Computing
- Scientific Computing and Imaging Institute
- Advisors: Prof. Shandian Zhe and Prof. Mike Kirby
- Research focus: Bayesian machine learning, tensor decomposition, streaming inference
- 2018 - 2019: M.S. Student
- Temple University
- Research focus: Machine learning and data mining
- 2014 - 2018: B.S. Student
- University of Science and Technology of China (USTC)
- School of the Gifted Young (少年班学院)
- Double degree in Statistics and Computer Science
Skills
- Machine Learning: Bayesian methods, deep learning, tensor decomposition, sparse learning
- Programming: Python, C++, MATLAB, R
- Frameworks: PyTorch, TensorFlow, JAX, NumPy, SciPy
- Applications: Time series analysis, computer vision, natural language processing
- Domains: Physics-informed ML, medical AI, quantitative finance
Publications
Talks
LLM-based Auto-evolving Agents for Data-driven R&D
Invited Talk at Yale University, Lulu Group (Online), Online
AI for Science: Foundation Models, Agents, and Scientific Discovery
Invited Talk at Shanghai AI Lab, Shanghai, China
Towards Intelligence Driven by Physical-World Signals
Invited Talk at Huawei, China
The Application of Gaussian Processes in Time Series and PDE-solving
Invited Talk at Renmin University of China, Beijing, China
BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition
Conference Talk at ICML 2024, Vienna, Austria
Solving High Frequency and Multi-Scale PDEs with Gaussian Processes
Conference Talk at ICLR 2024, Vienna, Austria
Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
Conference Talk at NeurIPS 2023, New Orleans, LA, USA
Bayesian Continuous-Time Tucker Decomposition
Conference Talk at ICML 2022, Baltimore, MD, USA
Teaching
Service and leadership
- Reviewer: ICML, NeurIPS, ICLR, UAI, AAAI, IJCAI, KDD, ICDM
- Teaching Assistant: Multiple courses in machine learning and data mining at University of Utah
- Mentor: Undergraduate and graduate students in research projects
- Community: Active contributor to open-source machine learning projects