Hao Xiong
熊昊

I am currently an Assistant Professor of Artificial Intelligence Innovation and Incubation (AI³) Institute at Fudan University. Prior to this, I received my Ph.D. from ReThinklab at the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU), under the supervision of Prof. Junchi Yan (严骏驰).

My research interests include

• quantum artificial intelligence in the AGI era
• tensor network for efficient and expressive machine learning
• graph learning and mining (for recommendation/bio-infomatics)
• combinatorial problem solving via neural and heuristic methods

I am actively recruiting self-motivated Master’s and Ph.D. students, as well as research assistants, to join us in exploring the exciting topics mentioned above. Your resume is highly welcome! 招募有自驱力的硕士和博士生以及科研助理，研究方向以上述方向为主，欢迎简历投递！

My google scholar page is here.

Publications

Quantum(-Inspired)/Tensor-Network-Based Machine Learning

[Efficient LLM/Next-Generation NNs] Reinvent the Operation not the Architecture: Quantum-inspired High-order Product for Compatible and Improved LLMs Training. SIGKDD 2025 (CCF-A) Research Track
Hao Xiong*, Yebin Yang*, Huaijin Wu, Xiaoqiu Zhong, Yehui Tang, Zhuo Xia, Xiaoxing Wang, Junchi Yan.
[paper] [slides]

[Tensor Network] Tensor Network: from the Perspective of AI4Science and Science4AI. IJCAI 2025 (CCF-A) Survey Track
Junchi Yan, Yehui Tang, Xinyu Ye, Hao Xiong, Xiaoqiu Zhong, Yuhan Wang, Yuan Qi.
[paper]

[Quantum Neural Networks] On Designing General and Expressive Quantum Graph Neural Networks with Applications to MILP Instance Representation. ICLR 2025 (Tsinghua-A)
Xinyu Ye, Hao Xiong, Jianhao Huang, Ziang Chen, Jia Wang, Junchi Yan.
[paper]

[Quantum Computing] Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning. CVPR 2024 (CCF-A)
Hao Xiong*, Yehui Tang*, Xinyu Ye*, Junchi Yan.
[code] [paper]

[AI4Quantum] Q-TAPE: A Task-Agnostic Pre-Trained Approach for Quantum Properties Estimation. ICLR 2024 (Tsinghua-A) Spotlight (5%)
Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan.
[paper]

[Tensor/Quantum-inspired Network Embedding] Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space. ICLR 2024 (Tsinghua-A)
Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan.
[code & data] [paper]

Network Embedding

[Interpretability] Learning Regularized Noise Contrastive Estimation for Robust Network Embedding. TKDE 2022 (CCF-A)
Hao Xiong, Junchi Yan, Zengfeng Huang.
[code & data] [paper] [a brief intro. (知乎)]

[Multi-Graph Alignment] Contrastive Multi-View Multiplex Network Embedding with Applications to Robust Network Alignment. SIGKDD 2021 (CCF-A)
Hao Xiong, Junchi Yan, Li Pan.
[poster] [slides] [video] [paper] (sorry for missing code, the machine was formatted by accident without being backed up)

[Cross-Graph Alignment] BTWalk: Branching Tree Random Walk for Multi-order Structured Network Embedding. TKDE 2020 (CCF-A)
Hao Xiong, Junchi Yan.
[code & data] [paper]

Neural Combinatorial Optimzation

[DL-Based Neural Solver] UniCO: On Unified Combinatorial Optimization via Problem Reduction to Matrix-Encoded General TSP. ICLR 2025 (Tsinghua-A)
Wenzheng Pan*, Hao Xiong*, Jiale Ma, Wentao Zhao, Yang Li, Junchi Yan.
[paper] [code]

[ML-Enhanced Heuristic] From Graph Embedding to LKH: Bridging Learning and Heuristics for a Streamlined General TSP Solver.
Hao Xiong, Wenzheng Pan, Jianhao Huang, Zhuo Xia, Junchi Yan.
[paper]

Knowledge Graph Embedding & System

[Knowledge Embedding] DGL-KE: Training Knowledge Graph Embeddings at Scale. SIGIR 2020 (CCF-A)
Da Zheng, Xiang Song, Chao Ma, Zeyuan Tan, Zihao Ye, Jin Dong, Hao Xiong, Zheng Zhang, George Karypis.
[code] [paper]

Education

• Ph.D., Computer Science and Engineering, Shanghai Jiao Tong University, 2021 - 2025
  Advisor: Prof. Junchi Yan 严骏驰
  
• M.S., Cyber Science and Engineering, Shanghai Jiao Tong Universeity, 2019 - 2021
  Advisor: Prof. Li Pan 潘理, Prof. Junchi Yan 严骏驰
  
• B.E., Cyber Science and Engineering, Shanghai Jiao Tong University, 2015 - 2019
  Advisor: Prof. Junchi Yan 严骏驰
  

Academic Activities

• Conference reviewer: NeurIPS in 2022-2023, SIGKDD in 2022-2024, ICML in 2022, AAAI in 2021-2022, 2024, SDM in 2022, 2024, ICLR in 2024
• Journal reviewer: Pattern Recognition in 2023, and Intelligent Computing in 2023.

Working Experience

• Applied Scientist Intern @AWS Shanghai AI Lab, Oct. 2019 - Apr. 2020
  Advisor: Prof. Zheng Zhang & Mentor: Dr. Xiang Song, Dr. Da Zheng
  I implemented DGL-DeepWalk[code]/LINE[code] for scalable/distributed training on multi-GPUs.
• (Part-time) fitness coach & manager @Huoyingdong Gym, SJTU, 2019.09-2025.06
• Teaching assistant of the C++ class @School of Cyber Science and Engineering, SJTU, 2019

Awards

• Outstanding Doctorial Graduate of SJTU, 2025 (上海交通大学优秀毕业生)
• Chanmpion of Pull-Up at the 50th School Olympics of SJTU (40 pull-ups one time, the first record of pull-up in the event), May 2024 (上海交通大学校运会引体向上首个校记录)
• Wuwenjun Scholarship, 2021-2025 (吴文俊奖学金)
• China National Scholarship for Ph.D Students, 2021 (博士生国家奖学金)
• Honorable Bachelor Degree of Engineering, June 2019 (致远荣誉学士学位)
• The Second Prize of National College Student Information Security Contest, Aug. 2018, Advisor: Prof. Gongshen Liu (全国大学生信息安全大赛二等奖)
• Honorary Scholarship of Zhiyuan Institute, 2016-2018 (致远荣誉奖学金)
• The Third-Level Scholarship, 2016-2018 (校级三等奖学金)
• The First Prize of National College Physics Competition, Dec. 2016 (全国大学生物理竞赛上海赛区非物理专业组一等奖)