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.

[Recruiting Ph.D. students and interns] I am actively seeking highly-motivated students for Ph.D. or Research Intern positions. If you are interested, please send me your CV, transcripts, and brief descriptions about why you want to work with me. Due to the substantial volume of emails I receive daily, I would like to apologize in advance as I may not be able to respond to each of them. I appreciate your understanding.

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

GitHub starsGitHub forks
DeepRobust: A Platform for Adversarial Attacks and Defenses
In AAAI 2021
[Website] [Paper] [Code]

GitHub starsGitHub forks
DANCE: A Deep Learning Library and Benchmark for Single-Cell Analysis
[Website] [Code] [paper] [reading list]


Call for Paper: We are organizing the Data-Centric Artificial Intelligence Workshop at WWW 2024. If you are working in relevant directions, don’t hesitate to submit your paper (the paper can be under review or published)!
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!

More news * [03/2023] Thrilled to receive the Outstanding Graduate Student Award at MSU! * [03/2023] We have launched the [Amazon KDD Cup'23 Competition](https://www.aicrowd.com/challenges/amazon-kdd-cup-23-multilingual-recommendation-challenge), 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](https://chandlerbang.github.io/files/Survey_GraphReduction.pdf) is accepted by WWW'23! * 🐰[01/2023] Our work [Test-Time Graph Transformation](https://openreview.net/forum?id=Lnxl5pr018) 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](https://research.snap.com/fellowships.html)! * [11/2022] We won **a Kaggle Silver Medal** at [NeurIPS'22 Multimodal Single-Cell Integration](https://openproblems.bio/neurips_2022/) (Top 2% ≈ 24/1266)! * [11/2022] We won **the second place** at [NeurIPS'22 OGB-LSC](https://ogb.stanford.edu/neurips2022/results/#winners_mag240m), 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](https://arxiv.org/pdf/2210.12385.pdf)! * [10/2022] Thrilled to release our paper for [DANCE package](https://www.biorxiv.org/content/biorxiv/early/2022/10/21/2022.10.19.512741.full.pdf)! * [09/2022] Invited to serve as PC Members for AISTATS'23 and WWW'23 * [08/2022] We release our Python toolkit [DANCE](https://github.com/OmicsML/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]](https://arxiv.org/abs/2206.07746), [[Overcorrelation in GNNs]](https://arxiv.org/abs/2206.07743) and [[GNN for Single Cell Analysis]](https://arxiv.org/abs/2203.01884)! * [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]](https://www.cs.emory.edu/~wjin30/files/GCond_.pdf), [[AutoSSL for Graphs]](https://cse.msu.edu/~jinwei2/files/AutoSSL.pdf) and [[GNN As Kernel]](https://openreview.net/forum?id=Mspk_WYKoEH) ! * [01/2022] Our book chapter ["Graph Neural Networks: Self-supervised Learning"](https://link.springer.com/chapter/10.1007/978-981-16-6054-2_18) 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](https://openproblems.bio/neurips_2021/) wins **the first place** in the task of modality prediction!


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 :)