Neil Jethani

NYU MD/PhD | Courant Institute | Department of Population Health

60 5th Ave

New York, NY 10012

I am an MD/PhD candidate at the NYU Grossman School of Medicine. My work focuses on building machine learning tools for healthcare. Specifically, I am interested in developing methods that help explain machine learning predictions to physicians and expand the diagnostic utility of the ECG. I am fortunate to be advised by Dr. Rajesh Ranganath and Dr. Yindalon Aphinyanaphongs.

Before graduate school, I earned a BS from the University of California, San Diego in Bioengineering. As an undergraduate student, I worked on projects investigating biomaterials for biomimetic systems and analyzing sequencing data.

In general, I try to have an active life outside of research. I enjoy doing anything that puts me in nature: hiking, biking, rock climbing, surfing, swimming, etc.


Aug 31, 2021 New work introducing a method that estimates Shapley values to provide model explanations in real-time with a single forward pass is added to arXiv.
Feb 25, 2021 Our work on developing a new machine learning explanation method and explanation evaluation method is accepted to AISTATS 2021.
Oct 22, 2020 Our work on characterizing myocardial injury in patients hospitalized With COVID-19 is accepted to Circulation.

selected publications

  1. Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
    Jethani, Neil, Sudarshan, Mukund, Aphinyanaphongs, Yindalon, and Ranganath, Rajesh