Hi there! I’m a 4-th (final) year Ph.D. student of Computer Science and Engineering at Michigan State University (MSU), advised by Prof. Jiliang Tang. I completed my B.E. degree in Electrical Engineering at Zhejiang University. My research interests lie in Data-Centric AI (a nice definition by Andrew Ng) and Graph Machine Learning. Revolving around these, I recently study the following topics:
- Data-Centric AI for GNN Scalability: ICLR’22, KDD’22
- Data-Centric AI for GNN Security: KDD’20, AAAI’21, WSDM’22, arXiv’22
- Interdisciplinary Research (Sinlge-Cell Analysis): KDD’22, arXiv’22, bioRxiv’22
- Model-Centric Robust Graph Machine Learning: WSDM’21, ICML’21, NeurIPS’21, KDD Explorations’20.
I am on the academic job market for faculty positions! Please feel free to reach out if you have potential job opportunities.
- [11/2022] We won a Kaggle Silver Medal at NeurIPS’22 Multimodal Single-Cell Integration (Top 2% ≈ 24/1266)!
- [11/2022] We won the second place at [NeurIPS’22 OGB-LSC], MAG240M Track!
- [11/2022] Our paper on Graph Data Augmentation is accepted by SDM’23!
- [11/2022] Our paper on Attacking GNN Explainer is accepted by ICDE’23!
- [10/2022] Thrilled to release our survey Deep Learning in Single-Cell Analysis!
- [10/2022] Thrilled to release our paper for DANCE package!
- [10/2022] New preprint “Test-Time Graph Transformation”
- [09/2022] Invited to serve as PC Members for AISTATS’23 and WWW’23
- [08/2022] We release our Python toolkit DANCE for analyzing single-cell gene expression via deep learning!
- [06/2022] Invited to serve as Senior PC Member for AAAI’23 and PC Member for WSDM’23
- [05/2022] Three papers accepted to KDD’22: [Faster Graph Condensation], [Overcorrelation in GNNs] and [GNN for Single Cell Analysis]!
- [04/2022] One paper accepted to SIGIR’22!
- [02/2022] I gave invited talks at Sheffield Univeristy and University of Notre Dame.
- 🐯[01/2022] Three papers accepted to ICLR’22: [Graph Condensation], [AutoSSL for Graphs] and [GNN As Kernel] !
- [01/2022] Our book chapter “Graph Neural Networks: Self-supervised Learning” is published in the new edited Springer book “Graph Neural Networks: Foundations, Frontiers, and Applications”!
- [12/2021] Our GNN solution for OpenProblems-NeurIPS’21 Single-Cell Multimodal Data Integration wins the first place in the task of modality prediction!
- [10/2021] New preprint “Graph Condensation for Graph Neural Networks”.
- [10/2021] One paper on robust GNN (againt noisy features) is accepted by NeurIPS’21. Check here for more details.
- [10/2021] I gave an invited talk at Emory University.
- [09/2021] Thrilled to start my fall internship at Amazon!
- [08/2021] Check out our KDD’21 tutorial “Graph Representation Learning: Foundations, Methods, Applications and Systems”
- [08/2021] Our work “Graph Feature Gating Network” is accepted by CIKM’21!
- [06/2021] Preprint “Automated Self-Supervised Learning for Graphs”.
- [05/2021] Thrilled to start my summer internship at Snap Inc., mentored by Neil Shah and Yozen Liu!
- [05/2021] The Chinese version of book “Deep Learning on Graphs” is out. Please check here to know more details :)
- [05/2021] Our paper Elastic GNN is accepted as a long talk by ICML’21!
- [04/2021] One paper is accepted by Findings of ACL 2021. Check here for more details.
- [04/2021] Honored to present a tutorial about graph neural networks in SDM 2021 [slides]
- [02/2021] Honored to present a tutorial about graph neural networks in AAAI 2021 [slides/video]
- [10/2020] Our graph attack survey “Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies” is accepted by SIGKDD Explorations
- [10/2020] Our demo “DeepRobust: a Platform for Adversarial Attacks and Defenses” is accepted by AAAI2021!
- [10/2020] Our paper “Node Similarity Preserving Graph Convolutional Networks” is accepted by WSDM2021
- [08/2020] Our new book about “Deep Learning on Graphs” is coming out soon!
- [06/2020] Preprint “Self-supervised Learning on Graphs: Deep Insights and New Direction”
- [05/2020] Our paper “Graph Structure Learning for Robust Graph Neural Networks” is accepted by KDD2020
- [05/2020] Our tutorial “Adversarial Attacks and Defenses: Frontiers, Advances and Practice” is accepted by KDD2020
- [05/2020] Preprint “DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses”
- [03/2020] Preprint “Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study”
- [02/2020] Check our repository DeepRobust here, which is a pytorch library for adversarial attacks and defenses on images and graphs
- [02/2020] Honored to present our tutorial in AAAI 2020 [website]
- [09/2019] Our tutorial “Graph Neural Networks: Models and Applications” is accepted by AAAI2020
- [08/2019] Start my Ph.D. life at Michigan State University!
- [07/2019] Graduate from Zhejiang University with the awards of Outstanding Graduate of ZJU and Zhejiang Province, China
I enjoy many different kinds of sports including running, basketball, ping-pong and tennis. During my undergrad, I got several champions in 400m, 400m hurdles and 4*400m relay races at the university sports meet.
Now my goal is to bulk up
and hopefully get a certificate of personal trainer. Let’s see what will happen 5 4 3 2 years later :)