About Me

I am a master’s student in Health Data Science at Juntendo University, supervised by Prof. Ryutaro Himeno and Prof. Zhe Sun. I am also a research assistant in the Tensor Learning Team at RIKEN AIP, supervised by Dr. Chao Li.

My research focuses on tensor-network-based probabilistic modeling, score-based variational inference, and quantum-inspired machine learning. I am particularly interested in using structured tensor representations to approximate high-dimensional probability distributions and improve the scalability of probabilistic inference.

Previously, I received my B.Eng. in Computer Science and Technology from Qilu University of Technology. My technical background includes Python, PyTorch, C++, Linux, and high-performance computing environments.

🔥 News

• 2026.05: I serve as a reviewer for the ICML 2026 workshop.

📝 Publications and Presentations

-More information can be found on my Google Scholar profile.

• Yuchen Cong, Zhe Sun, Chao Li. Score-based Variational Inference via Quantum Maximally Mixed States. The Annual Conference of the Japanese Society for Artificial Intelligence, 2026. [Oral Presentation]

• Chao Li, Yuchen Cong. Tensor Network and its Structure Search Problem. Mechanism of Brain and Mind Winter Workshop, 2025. [Poster Presentation]

🎖 Honors and Awards

• 2023, National Scholarship, China
• 2022, First Prize, 15th China University Computer Design Competition
• 2020, National Inspirational Scholarship, China
• 2020, Third Prize, 11th Lanqiaobei National Software Competition, C/C++ Track

📖 Educations

• 2025.04 - Present, Juntendo University, Tokyo, Japan

  Master of Health Data Science

  Supervisors: Prof. Ryutaro Himeno and Prof. Zhe Sun

  GPA: 3.74 / 4.00

  Research focus: Variational inference via tensor networks

• 2019.08 - 2023.06, Qilu University of Technology, Shandong, China

  Bachelor of Engineering in Computer Science and Technology

  GPA: 4.13 / 5.00

💻 Research Experience

• 2024.11 - Present, Research Assistant, Tensor Learning Team, Center for Advanced Intelligence Project, RIKEN AIP, Tokyo, Japan

  Supervisor: Dr. Chao Li

  I work on tensor-network-based probabilistic modeling, quantum-inspired machine learning, and score-based variational inference. My current research studies how tensor-network representations can be used to approximate high-dimensional probability distributions and support scalable variational inference. I also investigate tensor network architecture search and its potential applications to quantum circuit architecture search. In addition, I have experience deploying machine learning experiments on HPC clusters, including Fugaku, Hokusai, and Raiden.

🛠 Skills and Languages

• Programming: Python, PyTorch, NumPy, C++, Linux

• High-performance computing: Fugaku, Hokusai, Raiden

• Languages: Chinese, English

• English test: TOEIC 880 / 990