Zeshan Hussain
MD Candidate
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolZeshan Hussain is an MD-PhD candidate in the Harvard-MIT HST program who recently completed a PhD in EECS at MIT, where he developed clinical machine learning methods with Prof. David Sontag. He focuses on deep generative models for clinical sequential data, causal inference, and physician-AI interaction, aiming to translate robust models into scalable clinical decision support systems. With prior MS and BS degrees in Computer Science from Stanford, his background spans deep learning for medical imaging and data augmentation under Dr. Daniel Rubin and Prof. Chris Re. Based in Cambridge, MA, he blends frontline medical training with rigorous ML research, giving him practical insight into clinician workflows that many ML researchers lack. Over 11 years of experience across academia positions him to bridge research and deployment in healthcare AI.
11 years of coding experience
Doctor of Philosophy - PhD, Electrical Engineering and Computer Science, Doctor of Philosophy - PhD, Electrical Engineering and Computer Science at Massachusetts Institute of TechnologyDoctor of Medicine - MD, Doctor of Medicine - MD at Harvard Medical SchoolMaster of Science - MS, Computer Science, Master of Science - MS, Computer Science at Stanford University
Github Skills (13)
predictive10
ensembles9
survey9
uncertainty9
generative9
uncertainty-quantification8
pytorch6
deep-learning6
machine-learning6
medicine3
crowd2
electrophysiology2
clinical-trials2
Programming languages (2)
Github contributions (5)
zeshanmh/ief
Jul 2020 - Feb 2022
Train pharmacodynamic deep generative models to model disease progression
Contributions:75 commits, 41 pushes, 1 branch in 1 year 7 months
disease-progressiondeep-learningdeep-generative-modelsgenerativedisease
clinicalml/ml_mmrf
Jul 2020 - May 2021
Contributions:70 commits, 3 pushes in 10 months
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