Hi! I am Kexin. I am a PhD student at Stanford Computer Science, advised by Prof. Jure Leskovec and affiliated with Stanford AI Lab. My research is supported by Stanford Bio-X fellowship.
I work on enabling AI to produce novel, deployable, and interpretable biomedical and therapeutic discoveries. Questions that I am excited about:
How to model across massive, diverse, multi-modal, and multi-scale biological experiments to generate novel hypotheses and discoveries?
How to make these discoveries reliable, trustworthy, and overall aligned with what scientists truly value?
How to build a helpful AI that assists day-to-day workflows for biologists? What does it take to build a fully autonomous AI biologist?
I answer these questions on diverse and difficult biomedical problems throughout the therapeutics discovery and development pipeline.
Previously, I worked with Prof. Marinka Zitnik, Dr. Cao Xiao, Prof. Jimeng Sun, and Prof. Rajesh Ranganath. I have spent time researching at Genentech, Pfizer, IQVIA, Dana-Farber, Flatiron Health, and Rockefeller University. I did my undergrad at NYU in math & CS & studio art, and master at Harvard in health data science.
What’s new:
2024.09 Excited to be the head TA at Stanford CS 224W!
2024.09 Won the Best Poster Award at Stanford Bio-X Interdisciplinary Initiative!
2024.08 Received the Reviewer’s Choice Award at ASHG!
2024.06 Co-organize Stanford AI+Biomedicine Seminar!
2024.06 Cover article at Nature Biotechnology!
2024.04 Guest lecture at CMU Machine Learning for Scientists!
2023.12 Spotlight at NeurIPS 2023 and Oral at MLCB 2023!
2023.12 Guest lecture at Stanford CS 224W!
2023.06 Excited to work with Prof. Aviv Regev and Dr. Romain Lopez at Genentech this summer!
2022.07 Co-organize the inaugural LoG conference!
2022.07 Best paper honorable mentions award at IEEE VIS!
2022.07 Co-organize AI for Science Workshop at ICML & NeurIPS!
Latest publications:
Check out this page to learn more about my research!
[ 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
[ 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
[ NeurIPS, Spotlight ] Uncertainty Quantification over Graph with Conformalized Graph Neural Networks
Kexin Huang, Ying Jin, Emmanuel Candès, Jure Leskovec
[ Nature Biotechnology ] GEARS: Predicting Transcriptional Outcomes of Novel Multi-gene Perturbations
Yusuf Roohani, Kexin Huang, Jure Leskovec
[ Nature Chemical Biology & NeurIPS ] Therapeutic Data Commons: 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
Latest Talks:
Check out this page for past talks and send an email for talk opportunity!
2024.09 Oxford Clinical Informatics Group Seminar
2024.04 CMU 02-620 Machine Learning for Scientists, Guest Lecture
2024.02 Prof. Jonathan Pritchard’s Journal Club at Stanford University
2024.01 Roche R&D Center AI Club
2024.01 Retro Biosciences
2023.12 Rising Star Seminar Series at UC-Berkeley and UCSF, hosted by Alaa lab
2023.11 Stanford CS 224W: Machine Learning with Graphs, Guest Lecture
2023.05 IBM Research Accelerated Discovery Seminar
2023.05 GSK.ai & Entos AI
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Artworks:
Learn more about my artworks: Photography / Clay / Metalsmithing / Painting