About Me

I am a third year PhD student at the MIT Institute for Data Systems and Society (IDSS), co-advised by Marzyeh Ghassemi and Nikhil Agarwal. Broadly, my research focuses on questions at the intersection of machine learning, healthcare, and inequity. My current work is driven by two goals: identifying racial and other disparities in healthcare using statistical and causal inference, and investigating novel ways to use machine learning to create more equitable systems.

I interned at Microsoft Research New England in Summer 2022, hosted by Allison Koenecke and Lester Mackey. Prior to starting my PhD at MIT, I earned a Bachelor’s in Applied Mathematics at Yale and a Master’s in Data Science at Columbia. I also spent two years working in strategy consulting at Altman Vilandrie & Company.

Outside of work, I’m a huge sports fan, and spend a little too much time watching Liverpool FC and the Boston Celtics. I’ve also recently fallen in love with curling, the perfect way to get through the Boston winter.

Publications

Should I Stop or Should I Go? Early Stopping with Heterogeneous Populations
NeurIPS, 2023. Spotlight Presentation (top ~3% of submitted papers)
Hammaad Adam, Fan Yin, Mary Hu, Neil Tenenholtz, Lorin Crawford, Lester Mackey, Allison Koenecke.
Presented at CoDE@MIT 2023 and IC2S2 2023

Machine Learning for Demand Estimation in Long Tail Markets
Management Science, 2023 Hammaad Adam, Pu He, Fanyin Zheng.
Talks: Presented at INFORMS in 2021 and 2020

Mitigating the impact of biased artificial intelligence in emergency decision-making
Communications Medicine, 2022
Also presented at two NeurIPS 2022 workshops: Trustworthy and Socially Responsible ML and Deploy and Monitor ML
Hammaad Adam, Aparna Balagopalan, Emily Alsentzer, Fotini Christia, Marzyeh Ghassemi.
Featured in MIT News.

Write It Like You See It: Detectable Differences in Clinical Notes By Race Lead To Differential Model Recommendations
AIES, 2022
Hammaad Adam, Ming Ying Yang, Kenrick Cato, Ioana Baldini, Charles Senteio, Leo Anthony Celi, Jiaming Zeng, Moninder Singh, Marzyeh Ghassemi.
Featured in STAT and MIT News.

Prediction of protein–ligand binding affinity from sequencing data with interpretable machine learning
Nature Biotechnology, 2022
H Tomas Rube, Chaitanya Rastogi, Siqian Feng, Judith F Kribelbauer, Allyson Li, Basheer Becerra, Lucas AN Melo, Bach Viet Do, Xiaoting Li, Hammaad Adam, Neel H Shah, Richard S Mann, Harmen J Bussemaker.

Working Papers

Improving Organ Procurement for Health Equity
In preparation. Received MIT Racism Research Award, 2023.
Hammaad Adam, Nikhil Agarwal, Marzyeh Ghassemi.

Fair Organ Allocation Learning
In preparation. Presented at Jameel Clinical Seminar (with Marzyeh Ghassemi).
Hammaad Adam, Rene Bermea, Leo Anthony Celi, Marzyeh Ghassemi.

CV

Curriculum Vitae (updated 11/2023)