Keke Huang (黄柯柯)

I am looking for highly self-motivated undergraduate and graduate students to join my group. If you are interested, please send me your CV with a clear email subject line. Thanks!

Short Bio

I am currently a Professor in the School of Computer Science and Technology at Huazhong University of Science and Technology (HUST). I previously worked as a Postdoctoral Researcher in the Department of Computer Science at the University of British Columbia (UBC) and a Research Fellow in the School of Computing at the National University of Singapore (NUS). I received my Ph.D. from Nanyang Technological University (NTU), under the supervision of Prof. Xiaokui Xiao and Prof. Aixin Sun. Before that, I got my B.Eng. from Huazhong University of Science and Technology (HUST). I am a long-term visiting scholar of the AI Group of Prof. Pietro Liò at University of Cambridge.

Research Interests

My research is centered on the domains of data management & analysis, and machine learning. My work to date has been dedicated to developing scalable, efficient, and theoretically robust algorithms to enhance both the efficiency and effectiveness of graph analytics and graph learning. In graph learning, I have a particular interest in designing scalable and effective Graph Neural Networks. I also study strategies to optimize the ensemble of Large Language Models, focusing on improving their cost-efficiency and overall performance with guarantees. More recently, I have started exploring AI for Science, with a particular interest in data-driven and learning-based methods for scientific discovery.

Academic Services

Conference Program Committee Member：

• International Conference on Very Large Data Bases (VLDB): 2026, 2027
• International Conference on Learning Representations (ICLR): 2025, 2026
• ACM Web Conference (WWW): 2022, 2023, 2024, 2025
• ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD): 2022, 2023, 2024, 2025
• Conference on Neural Information Processing Systems (NeurIPS): 2023, 2025
• ACM International Conference on Web Search and Data Mining (WSDM): 2023
• ACM International Conference on Information and Knowledge Management (CIKM): 2023, 2024, 2025, 2026
• Learning on Graphs Conference (LoG): 2022, 2023, 2024

Journal Reviewer of VLDBJ, TKDE, Pattern Recognition, Neurocomputing, Journal of Global Optimization, ACM Computing Surveys, Applied Network Science, Mathematics.

Invited Talks

• Spectral Graph Neural Network: Polynomial Approximation and Optimization by Prof. Lio at University of Cambridge.
• Spectral Graph Neural Network: Polynomial Approximation and Optimization by Prof. Laks at The University of British Columbia.
• Node-wise Diffusion for Scalable Graph Learning by Prof. Xuanhua Shi at Huazhong University of Science and Technology.

Teaching Assistant

• Database System
• Java and the Internet
• Computer Organization and Architecture