Publications
Preprint
Zero-shot Drug Repurposing with Geometric Deep Learning and Clinician Centered Design
Kexin Huang*, Payal Chandak*, Qianwen Wang, Shreyas Havaldar, Akhil Vaid, Jure Leskovec, Girish Nadkarni, Benjamin S. Glicksberg, Nils Gehlenborg, Marinka Zitnik
Paper / GitHub / Website / TxGNN Explorer
STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases
Shirley Wu*, Shiyu Zhao*, Michihiro Yasunaga, Kexin Huang, Kaidi Cao, Qian Huang, Vassilis N. Ioannidis, Karthik Subbian, James Zou*, Jure Leskovec*
2024
[ ICML ] Relational Deep Learning: Graph Representation Learning on Relational Databases
Matthias Fey*, Weihua Hu*, Kexin Huang*, Jan Eric Lenssen*, Rishabh Ranjan*, Joshua Robinson*, Rex Ying, Jiaxuan You, Jure Leskovec.
[ RECOMB ] Sequential Optimal Experimental Design of Perturbation Screens Guided by Multimodal Priors
Kexin Huang, Romain Lopez, Jan-Christian Hütter, Takamasa Kudo, Antonio Rios, Aviv Regev
Paper / GitHub / Oral at MLCB 2023
2023
[ NeurIPS ] Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
Kexin Huang, Ying Jin, Emmanuel Candès, Jure Leskovec
Paper / GitHub / Spotlight (Top 3.1%)
[ NeurIPS ] Enabling Tabular Deep Learning When d≫n with an Auxiliary Knowledge Graph
Camilo Ruiz, Hongyu Ren, Kexin Huang, Jure Leskovec
[ Nature Biotechnology ] GEARS: Predicting Transcriptional Outcomes of Novel Multi-gene Perturbations
Yusuf Roohani, Kexin Huang, Jure Leskovec
Paper / GitHub / Innovation Award at Society for Lab Automation and Screening (SLAS 2023) / Best Poster Award at Intelligent Systems For Molecular Biology (ISMB 2022)
[ Nature ] Scientific Discovery in the Age of Artificial Intelligence
Hanchen Wang*, Tianfan Fu*, Yuanqi Du*, Wenhao Gao+, Kexin Huang+, Ziming Liu+, Payal Chandak, Shengchao Liu, Peter Van Katwyk, Andreea Deac, Anima Anandkumar, Karianne Bergen, Carla P. Gomez, Shirley Ho, Pushmeet Kohli, Joan Lasenby, Jure Leskovec, Tie-Yan Liu, Arjun Manrai, Debora Marks, Bharath Ramsundar, Le Song, Jimeng Sun, Jian Tang, Petar Velickovic, Max Welling, Connor W. Coley, Yoshua Bengio, Marinka Zitnik
[ Scientific Data ] Building a Knowledge Graph to Enable Precision Medicine
Payal Chandak*, Kexin Huang*, Marinka Zitnik
2022
[ Nature Chemical Biology ] Artificial Intelligence Foundation for Therapeutic Science
Kexin Huang,* Tianfan Fu*, Wenhao Gao*, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
[ Nature Biomedical Engineering ] Graph Representation Learning in Biomedicine and Healthcare
Michelle M. Li, Kexin Huang, Marinka Zitnik
[ IEEE VIS ] Towards Usable Explanations: Extending the Nested Model of Visualization Design for User-Centric XAI
Qianwen Wang, Kexin Huang, Payal Chandak, Marinka Zitnik, Nils Gehlenborg
Paper / Best Paper Honorable Mentions Award
[ NeurIPS ] Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks
Arian Rokkum Jamasb, Ramon Viñas Torné, Eric J Ma, Yuanqi Du, Charles Harris, Kexin Huang, Dominic Hall, Pietro Lio, Tom Leon Blundell
[ UAI ] Uncertainty-Aware Pseudo-labeling for Quantum Calculations
Kexin Huang, Vishnu Sresht, Brajesh Rai, Mykola Bordyuh
*Work done at Pfizer
[ Patterns ] HINT: Hierarchical Interaction Network for Clinical Trial Outcome Predictions
Tianfan Fu, Kexin Huang, Cao Xiao, Lucas Glass, Jimeng Sun
2021
[ NeurIPS ] Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development
Kexin Huang*, Tianfan Fu*, Wenhao Gao*, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
Website / NeurIPS Paper / White Paper / GitHub, 800 Stars! / Twitter / Mailing List / Video / Slides / 300K+ Data Downloads / 100K+ Package Downloads / Talk at the National Symposium on Drug Repurposing for Future Pandemics / Oral at ELLIS Molecular Machine Learning Workshop / Presented at BayLearn / Press: QbitAI
Track on Datasets and Benchmarks (NeurIPS Proceeding)
[ Patterns ] Machine Learning Applications for Therapeutic Tasks with Genomics Data
Kexin Huang*, Cao Xiao*, Lucas M. Glass, Cathy W. Critchlow, Greg Gibson, Jimeng Sun
Paper / GitHub / Editor’s Pick / Most Read
[ Bioinformatics ] SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization
Yue Yu*, Kexin Huang*, Chao Zhang, Lucas M. Glass, Jimeng Sun, Cao Xiao
[ Bioinformatics ] MolTrans: Molecular Interaction Transformer for Drug Target Interaction Prediction
Kexin Huang, Cao Xiao, Lucas Glass, Jimeng Sun
2020
[ NeurIPS ] Graph Meta Learning via Local Subgraphs
Kexin Huang, Marinka Zitnik
Paper / GitHub / Website / Slides / Poster / Talk Video
[ Bioinformatics ] DeepPurpose: a Deep Learning Library for Drug-Target Interaction Prediction
Kexin Huang, Tianfan Fu, Lucas Glass, Marinka Zitnik, Cao Xiao, Jimeng Sun
Paper / GitHub, 800 Stars! / Poster / Slides / IQVIA Blog / Medium Blog / Zhihu Blog / Press: QbitAI
[ Scientific Reports ] SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks
Kexin Huang, Cao Xiao, Lucas Glass, Marinka Zitnik, Jimeng Sun
[ AAAI ] CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Kexin Huang, Cao Xiao, Nghia Hoang, Lucas Glass, Jimeng Sun
Paper / GitHub / Poster / Slides / IBM Website / Press: MIT Technology Review, TechRepublic
2019
[ CHIL ] ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
Kexin Huang, Jaan Altosaar, and Rajesh Ranganath
Paper / GitHub, 250 stars! / Press: VentureBeat, Medium1, Medium2
*Equal Contribution
Workshops, demos, and abstracts list can be found here.
Please see my Google Scholar page for more information.
Academic Services:
Co-organizer for Learning on Graph Conference / NeurIPS 2021 AI for Science Workshop / ICML 2022 AI for Science Workshop
Journal reviewer for Bioinformatics / Briefings in Bioinformatics / JAMIA / Computers in Biology and Medicine / IEEE Transaction on Computational Biology and Bioinformatics
Conference reviewer for ICLR 2024 / ICML 2024 / NeurIPS 2023 / KDD 2023 / UAI 2023 / ISMB 2023 / IJCAI 2023 / CHIL 2023 / PSB 2022 / MLHC 2022 / ISMB 2022 / IJCAI 2022 / CHIL 2022 / NeurIPS 2022 Datasets and Benchmarks / NeurIPS GL Frontier 2020 / ICML Pre-training 2022 / ICML AI4Science 2022 / ACL BioNLP 2022 / NeurIPS ML4H 2021 / KDD 2021 / ISMB 2021 / NeurIPS ML4H 2020 / KDD 2020 / ACM-BCB 2020