Biography
Feng is an Assistant Professor in the Science, Mathematics, and Technology Cluster at the Singapore University of Technology and Design. He earned his PhD from the Institute of Theoretical Physics at the Chinese Academy of Sciences in 2022. During his doctoral studies, he pioneered research on developing arbitrary tensor network algorithms and machine learning tools to address complex problems in statistical physics and quantum computing. Following his PhD, he worked as a Research Fellow at the Centre for Quantum Technologies, where he initiated research on combinatorial optimization problems and quantum error correction. Beyond academia, Feng maintains strong collaborations with leading technology companies, including Google and NVIDIA.
Education
- PhD in Theoretical Physics, University of Chinese Academy of Sciences, 2022
- BSc in Mathematics and Applied Physics, Nanjing University of Aeronautics and Astronautics, 2016
Research Interests
My research focuses on applying advanced numerical tools to address challenging problems in physics and real-world applications. These problems can be succinctly summarized as: given complex interactions, how can we perform reasoning, inference, and learning? This scope spans various fields, including physics, quantum computing, chemistry, and biology, while also having profound applications in combinatorial optimization problems and machine learning. The core of my research lies in integrating advanced techniques from machine learning, tensor network algorithms, and high-performance computing to effectively solve such problems.
Awards
- Second Prize of Beijing Natural Science Award, 2023
- Outstanding Doctoral Dissertation Award of Beijing, 2022
- Outstanding Doctoral Dissertation Award of the Chinese Academy of Sciences, 2022
- National Scholarship for Doctoral Students, Ministry of Education of China, 2021
- Principal Scholarship, Chinese Academy of Sciences, 2021
- National Scholarship for Bachelor Students, Ministry of Education of China, 2013
Selected Publications
- Rong Fu, Zhongling Su, Han-Sen Zhong, Xiti Zhao, Jianyang Zhang, Feng Pan, Pan Zhang et al. “Surpassing Sycamore: Achieving Energetic Superiority Through System-Level Circuit Simulation.” In SC24: International Conference for High Performance Computing, Networking, Storage and Analysis, pp. 1-20. IEEE, 2024.
- Yijia Wang, Yuwen Ebony Zhang, Feng Pan, Pan Zhang, Tensor Network Message Passing, Phys. Rev. Lett. 132, 117401. (2024) (Editors’ Suggestion).
- Feng Pan, Keyang Chen, and Pan Zhang, Solving the Sampling Problem of the Sycamore Quantum Circuits, Phys. Rev. Lett. 129, 090502. (2022) (Editors’ Suggestion).
- Feng Pan, and Pan Zhang, Simulation of quantum circuits using the big-batch tensor network method, Phys. Rev. Lett. 128, 030501 (2022). (Editors’ Suggestion).
- Feng Pan, Pengfei Zhou, Sujie Li and Pan Zhang, Contracting arbitrary tensor networks: General approximate algorithm and applications in graphical models and quantum circuit simulations, Phys. Rev. Lett. 125, 060503 (2020).