Shichang (Ray) Zhang

Tutorial

• Explain AI Models: Methods and Opportunities in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
  

  • [Dec 2025] NeurIPS 2025 [website][slides]

Invited Talks of My Research

• How Post-Training Reshapes LLMs
  

  • [April 2025] New England NLP Meeting [slides]
    

• Peering into The Mind of AI
  

  • [April 2025] Seminar at Georgia Institute of Technology [slides]
    

• Interpreting AI Systems Through Features, Data, and Model Components
  

  • [April 2025] Data Mining Seminar at Emory [slides]
    

• Explainable AI for Graph Data and More
  

  • [Feb 2024] AI4LIFE Group at Harvard [slides may be shared upon request]
    

• Graph Neural Network Explanation for Heterogeneous Link Prediction
  

  • [July 2023] Amazon Trans.AI Research Talks [slides]

  • [May 2023] International World Wide Web Conference [slides] [video]
    

• Structure-Aware Graph Neural Network Explanation
  [Feb 2023] AI Time NeurIPS Talk Series [slides][video (in Chinese, starting from 00:19:05)]

• Graph-less Neural Networks
  [May 2022] NVIDIA GNN Reading Group [slides]

Talks at UCLA Data Mining Reading Group

• [Feb 2024] Explain AI Models by Locating and Editing Knowledge [slides][video]

• [Nov 2022] Recent Progress in GNN Explainability [slides]

• [Oct 2022] Diffusion Models For Text To Image Generation [slides]

• [April 2022] The Lottery Ticket Hypothesis and Its Application on GNNs [slides]

• [Nov 2021] GNN Explainability [slides][mind map]

• [April 2021] Gaussian Process and Determinantal Point Process [slides]

• [Jan 2021] Analyzing GNNs, A Spectral Perspective [slides]

• [May 2020] From Variational Inference to Variational Auto Encoder [slides]

• [Sept 2019] Probability and Sampling Methods [slides part1] [slides part2]

Other Talks

• [Oct 2023] A Watermark for Large Language Models at UT Austin LLM research seminar [slides]