Wei Jin’s Homepage
Hi there! I am an Assistant Professor of Computer Science at Emory University. I obtained my Ph.D. from Michigan State University in 2023 under the supervision of Prof. Jiliang Tang. Prior to that, I completed my B.E. degree at Zhejiang University in 2019. I have notable accomplishments such as Snap Research Fellowship, Most Influential Papers in KDD and WWW by PaperDigest, SDM Best Poster Award Honorable Mention, 3rd Place of Fitch H. Beach Award, and top finishes in three NeurIPS competitions. In addition, I regularly serve as organizers, (senior) PC members, and reviewers for multiple international conferences and journals in machine learning and data science such as ICLR, KDD, ICML, NeurIPS, AISTATS, AAAI, IJCAI, WWW, WSDM, CIKM, TKDE, TKDD and TNNLS.
I am actively seeking highly-motivated students for PhD positions starting Fall’24. For Emory students, we have the opportunity to collaborate starting from Fall’23. If you are interested, please send me your CV and all transcripts.
Research Interests:
- Graph Neural Networks, Graph Machine Learning
- Data-Centric AI (a nice definition by Andrew Ng)
- Trustworthy AI: Robustness, Privacy, Fairness
- AI for Science, AI for Healthcare
Email: wei.jin At emory.edu. Find me on Github, Twitter and Linkedin.
Open-Source Projects
DeepRobust: A Platform for Adversarial Attacks and Defenses
In AAAI 2021
[Website] [Paper] [Code]
DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis
[Website] [Code] [paper] [reading list]
News
Call for Paper: We are organizing a new research topic Graph Machine Learning at Large Scale in Frontiers in Big Data. If you are working in relevant directions, don’t hesitate to submit your paper to Frontiers!
- [11/2023] Our workshop on Data-Centric AI was accepted by WWW’23!
- [09/2023] Two papers accepted to NeurIPS’23
- [08/2023] One paper on single-cell analysis accepted to CIKM’23
- [07/2023] Check out our new preprint on LLMs for Graph!
- [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 3rd place in 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!
More news
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[01/2023] Our work on Data Augmentation for KG is accepted by WWW’23!
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🐰[01/2023] Our work Test-Time Graph Transformation is accepted by ICLR’23!
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[12/2022] Invited to serve as a PC Member for KDD’23 as well as a reviewer for ICML’23
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[12/2022] Thrilled to receive Snap Research Fellowship!
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[11/2022] We won a Kaggle Silver Medal at NeurIPS’22 Multimodal Single-Cell Integration (Top 2% ≈ 24/1266)!
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[11/2022] We won the second place at NeurIPS’22 OGB-LSC, MAG240M Track!
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[11/2022] Our tutorial on Graph Data Augmentation is accepted by SDM’23!
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[11/2022] Our paper on Attacking GNN Explainer is accepted by ICDE’23!
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[10/2022] Thrilled to release our survey Deep Learning in Single-Cell Analysis!
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[10/2022] Thrilled to release our paper for DANCE package!
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[09/2022] Invited to serve as PC Members for AISTATS’23 and WWW’23
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[08/2022] We release our Python toolkit DANCE for analyzing single-cell gene expression via deep learning!
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[06/2022] Invited to serve as Senior PC Member for AAAI’23 and PC Member for WSDM’23
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[05/2022] Three papers accepted to KDD’22: [Faster Graph Condensation], [Overcorrelation in GNNs] and [GNN for Single Cell Analysis]!
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[04/2022] One paper accepted to SIGIR’22!
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[02/2022] I gave invited talks at Sheffield Univeristy and University of Notre Dame.
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🐯[01/2022] Three papers accepted to ICLR’22: [Graph Condensation], [AutoSSL for Graphs] and [GNN As Kernel] !
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[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”!
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[12/2021] Our GNN solution for OpenProblems-NeurIPS’21 Single-Cell Multimodal Data Integration wins the first place in the task of modality prediction!
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[10/2021] One paper on robust GNN (againt noisy features) is accepted by NeurIPS’21. Check here for more details.
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[10/2021] I gave an invited talk at Emory University.
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[09/2021] Thrilled to start my fall internship at Amazon!
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[08/2021] Check out our KDD’21 tutorial “Graph Representation Learning: Foundations, Methods, Applications and Systems”
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[08/2021] Our work “Graph Feature Gating Network” is accepted by CIKM’21!
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[05/2021] Thrilled to start my summer internship at Snap Inc., mentored by Neil Shah and Yozen Liu!
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[05/2021] The Chinese version of book “Deep Learning on Graphs” is out. Please check here to know more details :)
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[05/2021] Our paper Elastic GNN is accepted as a long talk by ICML’21!
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[04/2021] One paper is accepted by Findings of ACL 2021. Check here for more details.
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[04/2021] Honored to present a tutorial about graph neural networks in SDM 2021 [slides]
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[02/2021] Honored to present a tutorial about graph neural networks in AAAI 2021 [slides/video]
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[10/2020] Our graph attack survey “Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies” is accepted by SIGKDD Explorations
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[10/2020] Our demo “DeepRobust: a Platform for Adversarial Attacks and Defenses” is accepted by AAAI2021!
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[10/2020] Our paper “Node Similarity Preserving Graph Convolutional Networks” is accepted by WSDM2021
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[08/2020] Our new book about “Deep Learning on Graphs” is coming out soon!
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[06/2020] Preprint “Self-supervised Learning on Graphs: Deep Insights and New Direction”
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[05/2020] Our paper “Graph Structure Learning for Robust Graph Neural Networks” is accepted by KDD2020
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[05/2020] Our tutorial “Adversarial Attacks and Defenses: Frontiers, Advances and Practice” is accepted by KDD2020
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[05/2020] Preprint “DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses”
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[03/2020] Preprint “Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study”
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[02/2020] Check our repository DeepRobust here, which is a pytorch library for adversarial attacks and defenses on images and graphs
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[02/2020] Honored to present our tutorial in AAAI 2020 [website]
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[09/2019] Our tutorial “Graph Neural Networks: Models and Applications” is accepted by AAAI2020
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[08/2019] Start my Ph.D. life at Michigan State University!
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[07/2019] Graduate from Zhejiang University with the awards of Outstanding Graduate of ZJU and Zhejiang Province, China
Personal
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 :)