About Me

I am a fifth year PhD student in the Johns Hopkins Computer Science Department, advised by Ilya Shpitser. I work on developing observational causal inference and machine learning methods for resource allocation. I am interested in translational work in health and public policy settings. Presently (Summer 2021), I am interning at IBM Research with Zach Shahn, Yoonyoung Park, and Stacy Hobson.

I am affiliated with the Malone Center for Engineering in Healthcare and the Mathematical Institute for Data Science (MINDS). I am a Google PhD Fellow. Previously, I was funded by a TRIPODS PhD Fellowship. I earned an MSE in Computer Science from Hopkins in 2019 and I graduated from the University of Michigan in 2017 with a B.S. in Computer Science with Honors.

Selected Publications

Computer Science Conference Papers

Eli Sherman, et at. (2021). "Towards Understanding the Role of Gender in Deploying Social Media-Based Mental Health Surveillance Models" 7th Workshop on Computational Linguistics and Clinical Psychology (CLPsych).
Paper and Supplement

Eli Sherman, David Arbour, and Ilya Shpitser (2020). "General Identification of Dynamic Treatment Regimes Under Interference" 23rd Annual Conference on Artificial Intelligence and Statistics (AIStats).
Paper and Supplement

Eli Sherman and Ilya Shpitser (2019). "Intervening on Network Ties." Proceedings of the 35th Annual Conference on Uncertainty in Artificial Intelligence (UAI).
PDF   Supplement

Eli Sherman and Ilya Shpitser (2018). "Identification and Estimation of Causal Effects from Dependent Data." Proceedings of the 32nd Annual Conference on Advances in Neural Information Processing Systems (NeurIPS) Spotlight Presentation.
PDF   Supplement   Talk

Ilya Shiptser and Eli Sherman (2018). "Identification of personalized effects associated with causal pathways." Proceedings of the 34th Annual Conference on Uncertainty in Artificial Intelligence (UAI) Plenary Presentation.
PDF   Supplement   Talk

Eli Sherman, et al. (2017) "Leveraging Clinical Time-Series Data for Prediction: A Cautionary Tale." AMIA Annual Symposium Proceedings Best Student Paper Award Winner KDD Subgroup Oral Presentation.

Medical Conference Abstracts

Eli Sherman, et al. (2021). "Leveraging Machine Learning to Predict 30-day Hospital Readmission after Cardiac Surgery". Society of Thoracic Surgeons Annual Meeting.

Lindsey Sloan, et al. (2019). "Multi-time point evaluation of peripheral blood myeloid-derived suppressor cell and lymphocyte populations in patients with newly diagnosed glioblastoma receiving adjuvant therapy". Society of Neuro-Oncology Annual Meeting.


Johns Hopkins University
  • Spring 2021: Instructor, EN 133 Bootcamp: Python
  • Fall 2019: Teaching Assistant, CS 677 Causal Inference
  • Spring 2018: Teaching Assistant, CS 295 Developing Health IT Applications
University of Michigan


I am an avid fan (perhaps unhealthily so!) of classical music. I have played cello since I was 8 (violin before that, and a foray into double bass in the middle). See a some recent performances with the Homewood Chamber Seminar below. Additionally, I am an occassional hiker, climber, tennis player, and golfer. In undergrad a was a play-by-play announcer and studio host for WCBN Sports, calling games for a variety of University of Michigan varsity sports.


Email: [first initial] + [last name] + [at symbol] + jhu + [dot] + edu