Jiliang Tang

Jiliang Tang is a University Foundation Professor in the computer science and engineering department at Michigan State University since 2022. He was an associate professor (2021-2022) and an assistant professor (2016-2021) in the same department. Before that, he was a research scientist in Yahoo Research and got his PhD from Arizona State University in 2015 under Dr. Huan Liu. His research interests include graph machine learning,trustworthy AI and their applications in education and biology. He was the recipient of various awards including 2022 AI's 10 to Watch, 2022 IAPR J. K. AGGARWAL Award, 2022 SIAM/IBM Early Career Research Award, 2021 IEEE ICDM Tao Li Award, 2021 IEEE Big Data Security Junior Research Award, 2020 ACM SIGKDD Rising Star Award, 2020 Distinguished Withrow Research Award, 2019 NSF Career Award, and 8 best paper awards (or runner-ups). His dissertation won the 2015 KDD Best Dissertation runner up and Dean's Dissertation Award. He serves as conference organizers (e.g., KDD, SIGIR, WSDM and SDM) and journal editors (e.g., TKDD, TOIS and TKDE). He has published his research in highly ranked journals and top conference proceedings, which have received tens of thousands of citations with h-index 85 (Google Scholar) and extensive media coverage (Links). Email: tangjili at msu dot edu Office: Engineering Building 2148 Mail: 428 S Shaw Ln Rm 3115, East Lansing, MI 48824 Lab: Data Science and Engineering Lab (Webpage, and Twitter )

Research Interests

• Graph Neural Networks, Deep Learning on Graphs
• Trusworthy AI: Safety, Robustness and Fairness
• AI+X: Education and Biology

News in 2023( More)

• My student Dr. Jamell Dacon will join Morgan State University (a public historically black research university) as a tenure-track AP. He is the #9 PROFESSOR from my group

• My student Dr. Xiaorui Liu got the 1st Runner Up of SIGKDD Dissertation Award

• My student Dr. Tyler Derr got the NSF Career Award

• Received the JP Morgan Faculty Award.

• My student Wei Jin will join Emory as a tenure-track assistant professor. He is the #8 PROFESSOR from my group

• MSU researchers get $1.2M to improve 911 call security. News from MSUToday, TV Interview from Wilx TV, TV Interview from WoodTV, Ratio Interview from WILS,

• Received the AI’s 10 to Watch Award.

• Appointed as an Associate Editor of ACM TOIS.

• Received the Amazon Faculty Award.

• My student Wei Jin won a SNAP Fellowship, the Outstanding Graduate Student Award, the Best Poster Award (Honorable Mention) at SDM’23, and the 3rd place in Fitch H. Beach Award (Highest Honor at MSU College of Engineering).

• Our new book: Deep Learning on Graphs. (English Version for Sale from Amazon) , (Chinese Version for Sale)

Preprints

• Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs,arXiv:2307.03393
• Recommender Systems in the Era of Large Language Models (LLMs),arXiv:2307.02046
• Empowering Molecule Discovery for Molecule-Caption Translation with Large Language Models: A ChatGPT Perspective,arXiv:2306.06615
• DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models ,arXiv:2306.04642
• Sharpness-Aware Data Poisoning Attack, arXiv:2305.14851
• Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation, arXiv:2302.03038
• Deep Learning in Single-Cell Analysis, arXiv:2210.12385
• Whole Page Unbiased Learning to Rank, arXiv:2210.10718
• Towards Fair Classification against Poisoning Attacks, arXiv:2210.09503
• DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis, bioRxiv
• Test-Time Training for Graph Neural Networks, arXiv:2210.08813
• A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability, arXiv:2204.08570
• Decentralized Composite Optimization with Compression , arXiv:2108.04448
• DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses, arXiv:2005.06149
• Self-supervised Learning on Graphs: Deep Insights and New Directions, arXiv:2006.10141
• Non-IID Graph Neural Networks, arXiv:2005.12386

Recent Publications ( Full List)

• Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?,NeurIPS2023
• Towards Label Position Bias in Graph Neural Networks, NeurIPS2023
• Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking , NeurIPS2023 Data
• Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation , NeurIPS2023 Data
• XES3G5M: A Knowledge Tracing Benchmark Dataset with Auxiliary Information, NeurIPS2023 Data
• Single-Cell Multimodal Prediction via Transformers , CIKM2023
• Towards the Memorization Effect of Neural Networks in Adversarial Training, KDD23
• Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?, ACL23
• Probabilistic Categorical Adversarial Attack and Adversarial Training, ICML23
• Alternately Optimized Graph Neural Networks, ICML23
• Generative Diffusion Models on Graphs: Methods and Applications , IJCAI23
• Graph Enhanced BERT for Query Understanding, SIGIR23
• Adversarial Attacks for Black-box Recommender Systems via Copying Transferable Cross-domain User Profiles, TKDE
• Empowering Graph Representation Learning with Test-Time Graph Transformation, ICLR2023
• Transferable Unlearnable Examples, ICLR2023
• Toward Degree Bias in Embedding-Based Knowledge Graph Completion,WWW2023
• Jointly attacking graph neural network and its explanations, ICDE2023