Medical AI Bootcamp
A Harvard-Stanford Program for closely mentored research at the intersection of AI and Medicine
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About

The Medical AI Bootcamp provides Harvard and Stanford students an opportunity to do cutting-edge research at the intersection of AI and medicine. Over 6 months, members receive training to work on high-impact research problems in small interdisciplinary teams.

This bootcamp is a joint effort between Harvard and Stanford led by faculty Pranav Rajpurkar and Andrew Ng.

Collaborating drawing
Setup

What we do

We tackle important problems in medicine that require artificial intelligence solutions. Our projects are often in close collaboration with clinicians at both Stanford and Harvard. We work on problems across clinical domains including radiology, emergency medicine, and cardiology, and develop computer vision and natural language processing solutions.

What you learn

You tackle a scoped-out research project in a small team from conception to co-authoring a manuscript. You receive mentorship from faculty in team meetings on project execution and direction. You develop knowledge of cutting-edge medical AI research in reading groups, and machine learning tools in skills building sessions.

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Team

Directors

Pranav Rajpurkar, PhD
Assistant Professor
Harvard Medical School

Andrew NG, PhD
Adjunct ProfessoR
Stanford University

Clinical Mentors

David Kim, Md, PhD
‍Assistant Professor
Stanford Medicine

Agustina Saenz MD, MPH
Academic Hospitalist, Brigham and Women's Hospital

Technical Mentors

Alex Tamkin
PhD Student in AI
Stanford University

Henrik Marklund
PhD Student In AI
Stanford University

Cohorts

Summer 2022 Cohort + SIBMI

Farah Dadabhoy MD MSC

Jonathan Williams

Nathan Chi

Vignav Ramesh

Vishwanatha Rao

Spring 2022 Cohort

Benjamin Chang

FanG Cao

Jaehwan Jeong

Julie Chen

Lauren Chen

Priya Khandelwal

Lucy He

Raja Narayan MD MPh

Schwinn Saereesitthipitak

Sina Hartung

Winter 2022 Cohort

Amy Zhang

Arvind Saligrama

Brian Soetikno, MD PhD

Elaine Liu

KaT Tian

Andrew Li, MD

Sameer Sundrani

Xinyi Wang

Apply

Harvard and Stanford affiliates can apply to any of the artificial intelligence, medicine, or web development specializations based on their experience. Candidates are expected to be able to dedicate ~20 hours a week; undergraduates and graduate students are expected to sign up for research credits for one semester / quarter.

We actively seek and welcome candidates from historically underrepresented groups, candidates without previous research experiences, and candidates with primary fields of study outside STEM.

AI Specialization

Candidates with practical machine learning knowledge, and ability to code in Python.

Medicine Specialization

Candidates with clinical knowledge at least at the level of Step 2 and some clinical rotations. We are also particularly looking for radiology residents and fellows.

Web Specialization

Candidates with web stack expertise, covering both front-end and back-end for web applications.

Submit your application

The applications for the next cycle are now open. We have two cohorts to account for different starts to the semester and academic quarters.

Cohort A
Early Applications due Aug 14th, 2022 at 11:59p PT.
Regular Applications due Aug 21st, 2022 at 11:59p PT.

Cohort B
Early Applications due Aug 15th, 2022 at 11:59p PT.
Regular Applications due Aug 27th, 2022 at 11:59p PT.
Late Applications due Sep 21st, 2022 at 11:59p PT.


Cohort A starts on Aug 26th, 2022 and Cohort B on Sep 23rd, 2022. We will reach out to you if you are selected for the interview round. We conduct rolling interviews and selections until the application deadlines.

Submit Application