Publications
Preprint
Biomni: A General-Purpose Biomedical AI Agent
Kexin Huang*, Serena Zhang*, Hanchen Wang*, Yuanhao Qu, Yingzhou Lu*, Yusuf Roohani, Ryan Li, Lin Qiu, Gavin Li, Junze Zhang, Di Yin, Shruti Marwaha, Jennefer N. Carter, Xin Zhou, Matthew Wheeler, Jonathan A. Bernstein, Mengdi Wang, Peng He, Jingtian Zhou, Michael Snyder, Le Cong, Aviv Regev, Jure Leskovec
Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph
Kexin Huang, Tony Zeng, Soner Koc, Alexandra Pettet, Jingtian Zhou, Mika Jain, Dongbo Sun, Camilo Ruiz, Hongyu Ren, Laurence J Howe, Tom Richardson, Adrian Cortes, Katie Aiello, Kim Branson, Andreas R Pfenning, Jesse Engreitz, Martin Jinye Zhang, Jure Leskovec
Paper / GitHub / Website / Reviewer Choice Award at ASHG 2024 / Best Poster Award at Stanford Bio-X Interdisciplinary Initiative / Outstanding Poster Award at NeurIPS 2024 AI DrugX Workshop
SpatialAgent: An autonomous AI agent for spatial biology
Hanchen Wang, Yichun He, Paula P. Coelho, Matthew Bucci, Abbas Nazir, Bob Chen, Linh Trinh, Serena Zhang, Kexin Huang, Vineethkrishna Chandrasekar, Douglas C. Chung, Minsheng Hao, Ana Carolina Leote, Yongju Lee, Bo Li, Tianyu Liu, Jin Liu, Romain Lopez, Tawaun Lucas, Mingyu Ma, Nikita Makarov, Lisa McGinnis, Linna Peng, Stephen Ra, Gabriele Scalia, Avtar Singh, Liming Tao, Masatoshi Uehara, Chenyu Wang, Runmin Wei, Ryan Copping, Orit Rozenblatt-Rosen, Jure Leskovec, Aviv Regev
2025
[ ICML ] Automated Hypothesis Validation with Agentic Sequential Falsifications
Kexin Huang*, Ying Jin*, Ryan Li*, Michael Y. Li, Emmanuel Candès, Jure Leskovec
[ ICLR ] BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments
Yusuf H Roohani, Andrew H. Lee, Qian Huang, Jian Vora, Zachary Steinhart, Kexin Huang, Alexander Marson, Percy Liang, Jure Leskovec
2024
[ Nature Medicine ] A Foundation Model for Clinician-centered Drug Repurposing
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 / Highlighted in White House Rare Disease Forum / Featured in Forbes, WIRED, The Harvard Gazette, NVIDIA Technical Blog / Evaluated by the Rare As One Program at the Chan Zuckerberg Initiative / Commentary in Nature Medicine News and Views
[ 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
[ NeurIPS ] RelBench: A Benchmark for Deep Learning on Relational Databases
Joshua Robinson*, Rishabh Ranjan*, Weihua Hu*, Kexin Huang*, Jiaqi Han, Alejandro Dobles, Matthias Fey, Jan Eric Lenssen, Yiwen Yuan, Zecheng Zhang, Xinwei He, Jure Leskovec
[ NeurIPS ] 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*
[ NeurIPS ] AvaTaR: Optimizing LLM Agents for Tool-Assisted Knowledge Retrieval
Shirley Wu*, Shiyu Zhao*, Qian Huang, Kexin Huang, Michihiro Yasunaga, Kaidi Cao, Vassilis N. Ioannidis, Karthik Subbian, Jure Leskovec*, James Zou*
[ 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.
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) / Featured in journal cover
[ 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