[05/2025] Invited talk at French Consortium of Infectious Disease Modellers

[05/2025] One paper on GraphODE for Epidemic Modeling has been accepted to ICML’25!

[05/2025] Check out our KDD’25 survey on Graph + Differential Equations (ODE/PDE/SDE)

[04/2025] Excited to receive Emory URC Award!

[03/2025] Invited talk “Epidemic Time Series Forecasting in the Era of Machine Learning” at University of Notre Dame

[03/2025] Excited to share that our workshop on LLMs for Scientific and Societal Applications has been accepted by KDD’25!

[03/2025] Excited to release TimeDistill, the first framework for cross-architecture knowledge distillation in time series forecasting! We effectively transferred knowledge from teacher models (e.g., Transformers, CNNs) to MLP, achieving better forecasting performance and higher effiency

[02/2025] Check out our new preprint on Scalable Graph Condensation with Evolving Capabilities! We provide a scalable framework for compressing graph data into a signicantly smaller version (up to 1,000 times faster than previous methods)

[02/2025] Check out our recent preprint on Pre-Training on Epidemic Time Series! We demonstrated that pre-training on diverse epidemic data can effectively improve forecasting performance for new diseases!

[02/2025] Invited to serve as the co-chair for CIKM 2025 AnalytiCup!

[01/2025] Excited to share that Data Packing for LLMs and LLM for Decision-Making are accepted by NAACL’25!

[01/2025] Excited to share that our paper on Graph Data Valuation is accpeted by ICLR’25!

[12/2024] Excited to receive MP3 INITIATIVE SEED GRANTS to support our research in AI for Epidemiology!

[12/2024] Excited to share that Emory Artificial Intelligence and Data Association (EAIDA) has been officially recognized as a student organization by Emory University! I am serving as the faculty advisor; please check out our website if you are interested in joining us!

[12/2024] Our tutorial on Time Series Analysis is accepted by WWW’25!

[11/2024] Our On-Device Dataset Condensation paper is accepted by Design Automation and Test in Europe (DATE)

[11/2024] Two papers (Diffusion Model for Link Prediction and Graph Pre-Training) accepted by LoG

[11/2024] Invited talk at Statistical Advisory Group at Centers for Disease Control and Prevention (CDC) on “Deep Learning Methods and Toolkits for Epidemic Modeling”

[11/2024] Our paper Neural Networks for Endemic Measles Dynamics is accepted by PLOS Computational Biology!

[10/2024] Invited to serve on an NSF Panel

[10/2024] Invited talk at University of Queensland. We will talk about “Graph Neural Networks in Epidemic Modeling: An In-Depth Review and Toolkit”

[10/2024] Invited talk at Kennesaw State University

[09/2024] One paper on Graph-LLM accepted by NeurIPS Benchmark and Dataset Track!

[09/2024] Starting to work with McNair Middle School through Science ATL to design teaching materials focused on Grades K-8. Our mission is to enhance access to STEM learning resources and careers for students from groups underrepresented in the STEM fields!

[07/2024] Delivered the Machine Leanring for Infectious Disease Modeling module at the SISMID summer course

[07/2024] We will deliver a tutorial on Graph for Epidemiology at KDD 2024! Welcome to our session to learn this exiciting direction!

[07/2024] Excited to receive the INNS Doctoral Dissertation Runner-up Award!

[06/2024] Excited to announce the release of our Python package, EpiLearn, for Machine Learning in Epidemiology ! We would greatly appreciate your attention and feedback!

[05/2024] Our survey on GNNs for Epidemic Modeling has been accepted by KDD 2024!

[05/2024] Our exploration on Graph OOD has been accepted by KDD 2024!

[04/2024] Lossless Graph Condensation has been accepted by ICML 2024!

[04/2024] Our survey on graph reduction has been accepted by IJCAI 2024!

[04/2024] Our team has won Kaggle Bronze medal (top 7%) at Harvard - Harmful Brain Activity Classification!

[04/2024] Invited talk at University of Georgia

[03/2024] Our benchmark DANCE is published in Genome Biology! Join us to analyze single-cell gene expression via deep learning!

[02/2024] Invited talk at Rising Stars in AI Symposium, KAUST, Saudi Arabia

[01/2024] Invited talk at Georgia Tech CSE

[01/2024] Check out our recent survey on graph reduction, covering sparsification, coarserning and condensation!

[01/2024] One paper on [Graph Condensation for Interpretation] has been accepted by WWW(TheWebConf)’24

[01/2024] Two papers accepted by ICLR’24

[12/2023] Excited to be selcted for AAAI-2024 New Faculty Highlights .!

[11/2023] Our workshop on Data-Centric AI is accepted by WWW’24!

[09/2023] Two papers accepted to NeurIPS’23

[08/2023] One paper on single-cell analysis accepted by CIKM’23

[07/2023] Check out our new preprint on LLMs for Graph!

[07/2023] My dissertation is now available online [link]!

[06/2023] KDD Cup 2023 Workshop is now calling for paper submissions!

[05/2023] Our paper “Enhancing Graph Representations Learning with Decorrelated Propagation” got accepted by KDD’23!

[05/2023] Thrilled to receive the Fitch H. Beach Award (Highest Honor at MSU College of Engineering)!

[04/2023] Thrilled to receive the Best Poster Award (Honorable Mention) at SDM’23!

[04/2023] Invited to serve as an undergraduate mentor at UNLV & Google ExploreCSR Program. We encourage students from historically-underrepresented groups to apply!

[03/2023] Thrilled to receive the Outstanding Graduate Student Award at MSU!

[03/2023] We have launched the Amazon KDD Cup’23 Competition, featuring a multilingual recommendation challenge. Feel free to submit your solutions and potentially win thousands of dollars!

[01/2023] Our work on Data Augmentation for KG is accepted by WWW’23!

🐰[01/2023] Our work Test-Time Graph Transformation is accepted by ICLR’23!

[12/2022] Invited to serve as a PC Member for KDD’23 as well as a reviewer for ICML’23

[12/2022] Thrilled to receive Snap Research Fellowship!

[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 tutorial 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!

[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] 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!

[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