Dr. Jingwen Fu

Dr. Jingwen Fu Assistant Professor (PI) AI Theory and Foundation Zhongguancun Academy Email: fujingwen@bza.edu.cn Google Scholar GitHub

Biography

Dr. Jingwen Fu is an Assistant Professor and Principal Investigator at Zhongguancun Academy, working in AI Theory and Foundation. He received his Ph.D. in Control Science and Engineering from Xi'an Jiaotong University (2021-2026), advised by Nanning Zheng. During his doctoral studies, he joined the joint Ph.D. program with Microsoft Research Asia (MSRA), mentored by Wenjun Zeng, and spent one year as a national-scholarship visiting Ph.D. student at RIKEN AIP in Japan under Professor Masashi Sugiyama. He previously visited POSTECH (2019).

His research focuses on fundamental problems in artificial intelligence, with current interests in AI for AI (AI4AI), world models, and learning theory. He has published papers in leading venues including ICML, NeurIPS, ICCV, CVPR, AAAI, TPAMI, and related journals.

Research Interest

• AI4AI

• World models

• Learning theory

Experience

• Assistant Professor (PI), Zhongguancun Academy, Apr 2026 - Present

• Visiting Ph.D. Student (China Scholarship Council), RIKEN AIP, Japan, Dec 2024 - Dec 2025
  Advisor: Masashi Sugiyama

• Joint Ph.D. / Research Intern, Microsoft Research Asia, Jun 2020 - Apr 2024
  Advisor: Wenjun Zeng

• Visiting Student, Pohang University of Science and Technology (POSTECH), Feb 2019 - Jul 2019

Educational Background

• Ph.D., Control Science and Engineering, Xi'an Jiaotong University, Sep 2021 - Mar 2026
  Advisor: Nanning Zheng; National Key Laboratory of Human-Machine Hybrid Augmented Intelligence

• B.S., Computer Science and Technology, Xi'an Jiaotong University, Sep 2017 - Jul 2021

Selected Honors

• National Scholarship for Doctoral Students (Top 1%), 2024

• Outstanding Graduate Student / Academic Scholarship, Xi'an Jiaotong University, 2021-2025

Professional Service

• Teaching: Principles of Artificial Intelligence, Zhongguancun Academy (graduate course)

• Workshop: Organizer and Program Chair, NeurIPS 2026 Workshop on Linguistic Principles for Foundation Models

• Reviewer: CVPR, ICCV, NeurIPS, ICML, ICLR, AAAI, and related venues

For Prospective Students

I am always happy to discuss research ideas with motivated students. If you are interested in AI4AI, world models, or learning theory, feel free to email me with your background and research interests.