Photo of Chris Chute

Chris Chute

GitHub: @chrischute
Google Scholar: here
CV/Resume: here


I'm a second-year master's student at Stanford studying computer science. I'm most interested in machine learning and networks. During my time at Stanford, I've had the privilege of working with the Stanford ML Group and the Ermon Group. I did my undergrad at Yale and graduated in 2017 with degrees in math and computer science. I previously interned at Microsoft (summer 2017, 2016) and did math research at Yale (summer 2015).



  1. Deep Learning-Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model
    Allison Park*, Christopher Chute*, Pranav Rajpurkar*, Joe Lou, Robyn L. Ball, Katie Shpanskaya, Rashad Jabarkheel, Lily H. Kim, Emily McKenna, Joe Tseng, Jason Ni, Fidaa Wishah, Fred Wittber, David S. Hong, Thomas J. Wilson, Safwan Halabi, Sanjay Basu, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng, Kristen W. Yeom
    JAMA Network Open, 2019

  2. CheXpert: A Large Chest Radiograph Dataset with Uncertainty Labels and Expert Comparison
    Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Christopher Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng
    AAAI, 2019

  3. Query complexity of mastermind variants
    Aaron Berger, Christopher Chute, Matthew Stone
    Discrete Mathematics, 2018


  1. AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows
    Aditya Grover*, Christopher Chute*, Rui Shu, Zhangjie Cao, Stefano Ermon
    ArXiv Preprint, 2019