[Feb 2024] Give a talk on Explainable AI for Graph Data and More at the AI4LIFE Group at Harvard.
[Dec 2023] Our paper on LLM-based explainable molecular concept learning is accepted by the XAI4Sci workshop at AAAI 2024. [PDF]
[Dec 2023] Our paper on GNNs for explainable material science is accepted by the AI4Mat workshop at NeurIPS 2023.
[PDF]
[Aug 2023] Certified Excellence in Reviewing for KDD 2023 (30 in 1551).
[July 2023] I am excited to be selected as one of the 2023 Amazon Fellows.
[July 2023] I am excited to receive the J.P. Morgan Chase AI Ph.D. Fellowship.
[July 2023] Give a talk on the PaGE-Link paper at Amazon Trans.AI Research Talk Series. [slides]
[June 2023] Our survey paper on GNN acceleration is on arXiv now, which covers algorithms, systems, and customized hardware. [PDF]
[April 2023] One paper on GNN distillation for link prediction is accepted by ICML 2023. [PDF]
[Feb 2023] Give a talk on the GStarX paper at AI TIME NeurIPS Talk Series. [slides][video (in Chinese, starting from 00:19:05)]
[Jan 2023] One paper on GNN explanation for link prediction is accepted by WWW 2023. [PDF]
[Sept 2022] One paper on GNN explanation is accepted by NeurIPS 2022. [Paper]
[July 2022] Selected as the top 10% of reviewers for ICML 2022.
[April 2022] A draft chapter of A Trip from Machine Learning to Measure and Probability.
[Jan 2022] Two papers on graph distillation and graph condensation are accepted by ICLR 2022. [Paper1] [Paper2]
[Nov 2021] The first draft of Explainability Mind Map.
[Nov 2019] First launch of my website.