I am a PhD candidate in Computer Science & Engineering (CSE) at Shanghai Jiao Tong University (SJTU), advised by Prof. Junchi Yan. Prior to this, I received my bachelor’s degree from Shandong University (SDU). My research topics include graph neural networks and generative models. Specifically, I am interested in developing robust learning systems of quantum many-body physics.

I am always open for collaboration opportunities and please feel free to contact me via email: yehuitang@sjtu.edu.cn

Recent News

• May 2024: One paper is accepted to ICML.
• Feb 2024: One paper is accepted to CVPR. Congrats to Hao Xiong!
• Jan 2024: Two papers are accepted by ICLR, one of which is accepted as a spotlight (top 5%).
• Sep 2022: One paper is accepted to NeurIPS.

Education

• B.S. in School of Control Science and Engineering, Shandong University, 2016-2020.
• Ph.D in Department of Computer Science and Engineering, Shanghai Jiao Tong University, 2020-Present.

Publications

1. SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification
   Yehui Tang, Nianzu Yang, Mabiao Long, Junchi Yan.
   ICML (2024). [PDF]

2. Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
   Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan.
   ICLR spotlight (2024). [PDF]

3. Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space
   Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan.
   ICLR (2024). [PDF] [Code]

4. Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning
   Hao Xiong^\(\dagger\), Yehui Tang^\(\dagger\) (co-first author), Xinyu Ye^\(\dagger\), Junchi Yan.
   CVPR (2024). [PDF] [Code]

5. Recent Progress and Perspectives on Quantum Computing for Finance
   Yehui Tang, Junchi Yan, Guoqiang Hu, Baohua Zhang, Jinzan Zhou.
   SOCA (2022). [PDF]

6. GraphQNTK: Quantum Neural Tangent Kernel for Graph Data
   Yehui Tang, Junchi Yan.
   NeurIPS (2022). [PDF] [Code]

7. Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach
   Ge Yan, Yehui Tang, Junchi Yan.
   SIGKDD (2022). [PDF]

Academic Services

I serve as Reviewer for NeurIPS 2022-2024, ICLR 2023-2024, ICML 2023-2024, CVPR 2024, SIGKDD 2023.