James Zou     

My new website is www.james-zou.com


Department of Biomedical Data Science
Department of Computer Science
Department of Electrical Engineering


Email: jamesyzou at gmail dot com      Office: Packard 258  




























































































Hi! I am an Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and Electrical Engineering at Stanford University. I work on a wide range of problems in machine learning (from proving mathematical properties to building large-scale algorithms) and am especially interested in applications in genomics and computational health. I received a Ph.D. from Harvard in 2014 and was a member of Microsoft Research New England. Before this, I completed Part III in math at the University of Cambridge and was a Simons fellow at U.C. Berkeley. I joined Stanford in Fall 2016 and am excited to be an inaugural Chan-Zuckerberg Investigator. I lead the Stanford Laboratory for Machine Learning, Genomics and Health and am the faculty director of the new university-wide AI for Health program. We are also a part of the Stanford AI Lab and sometimes I discuss our research @james_y_zou
         








































NEWS  










































11/19: Our paper on how sex and gender analysis improves science and engineering is published in Nature.
9/19: Our papers on deleting data from ML (spotlight) and learning human meaningful concepts will be presented at NeurIPS.
7/19: Our machine learning for genome editing paper is published in Nature Biotechnology 









5/19: AdaFDR won the Best Paper Award at RECOMB. Extended version in Nature Communications        




5/19: At ICML we'll present papers on data valuation, concrete autoencoder, conditional features and adaptive Monte Carlo.    
4/19: Check out our two knockoff papers in AISTATS
























2/19: Interpretation of neural network is fragile in AAAI and VetTag in Nature Digital Medicine.         








1/19: Feedback GAN for protein design published in Nature Machine Intelligence.                                                                           
11/18: Check out our interactive deep learning for genomics primer in Nature Genetics.  












9/18: Excited to receive a NIH Center for Excellence in Genomics and a NIH R21. Thanks for the generous support! 
7/18: Our paper on designing fair AI is published in Nature.  





















6/18: Honored to receive a Google Faculty Award and a Tencent AI award.  
4/18: Word embedding reveals 100 years of stereotypes is published in PNAS and highlighted in Science