Shichang Zhang

alt text 

About Me

I am currently a forth-year Ph.D. student in Computer Science at University of California, Los Angeles (UCLA) Data Mining Lab working with Professor Yizhou Sun. Before joining UCLA, I received my B.A. and M.S. both in Statistics from Berkeley and Stanford respectively. [CV]

I am organizing the UCLA Data Mining Reading Group. We cover interesting graph machine learning papers every week. Please check the past slides and recordings here. The reading group also dig deep into one interesting AI topic each quarter. The topic for this quarter is diffusion models. In the past, we have covered large language models, differential geometry, graphical models, and spectral graph theory. Please find past slides and recordings here. My personal presentations at the reading group can be found under Talks.

Contact

3551 (ScAI Lab), Bolter Hall, UCLA, CA, 90095
E-mail: shichang AT cs DOT ucla DOT edu
[Google Scholar] [GitHub] [Twitter] [LinkedIn]

What's New

Research Interests

My research interests include

  • Graph Neural Network

  • Explainable AI

  • Model Efficiency

  • Self-supervised Learning

  • Generative Models

  • Data Mining in General

Publications and Pre-prints

  1. Linkless Link Prediction via Relational Distillation (preprint)
    Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao [PDF]

  2. Explaining Graph Neural Networks with Structure-Aware Cooperative Games (NeurIPS 2022)
    Shichang Zhang, Neil Shah, Yozen Liu, Yizhou Sun [PDF] [code]

  3. Graph-less Neural Networks, Teach Old MLPs New Tricks via Distillation (ICLR 2022)
    Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah [PDF] [code]

  4. Graph Condensation for Graph Neural Networks (ICLR 2022)
    Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah [PDF] [code]

  5. Motif-driven Contrastive Learning of Graph Representations (SSL@WWW2021)
    Shichang Zhang, Ziniu Hu, Arjun Subramonian, Yizhou Sun [PDF]

Full list of publications