I am a PhD candidate in Computer Science at Stanford University.
I am advised by Nigam Shah and Chris Ré. My research focus is on developing and operationalizing AI models in healthcare.
I graduated summa cum laude from Harvard in 2020 with a double major in Computer Science and Statistics, and am fortunate to be supported by an NSF Graduate Research Fellowship and Stanford HAI Graduate Fellowship.
Research
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Michael Wornow, Avanika Narayan, Ben Viggiano, Ishan S. Khare, Tathagat Verma, Tibor Thompson, Miguel Angel Fuentes Hernandez, Sudharsan Sundar, Chloe Trujillo, Krrish Chawla, Rongfei Lu, Justin Shen, Divya Nagaraj, Joshua Martinez, Vardhan Agrawal, Althea Hudson, Nigam H. Shah, Christopher Ré
Under review (2024)
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Automating the Enterprise with Foundation Models
Michael Wornow*, Avanika Narayan*, Krista Opsahl-Ong, Quinn McIntyre, Nigam H. Shah, Christopher Ré
VLDB (2024)
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Zero-Shot Clinical Trial Patient Matching with LLMs
Michael Wornow*, Alejandro Lozano*, Dev Dash, Jenelle Jindal, Kenneth W. Mahaffey, Nigam H. Shah
Under review (2024)
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EHRSHOT: An EHR Benchmark for Few-Shot Evaluation of Foundation Models
Michael Wornow*, Rahul Thapa*, Ethan Steinberg, Jason Fries, Nigam H. Shah
NeurIPS: Benchmarks (2023) — Spotlight
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HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
Eric Nguyen*, Michael Poli*, Marjan Faizi*, Armin W. Thomas, Callum Birch Sykes, Michael Wornow, Aman Patel, Clayton Rabideau, Stefano Massaroli, Yoshua Bengio, Stefano Ermon, Stephen A. Baccus, Christopher Ré
NeurIPS (2023) — Spotlight
Tweet | Blog | Github | Huggingface
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Michael Wornow, Yizhe Xu, Rahul Thapa, Birju Patel, Ethan Steinberg, Scott Fleming, Michael A. Pfeffer, Jason Fries, Nigam H. Shah
NPJ Digital Medicine (2023)
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APLUS: A Python Library for Usefulness Simulations of Machine Learning Models in Healthcare
Michael Wornow, Elsie Ross, Alison Callahan*, Nigam H. Shah*
Journal of Biomedical Informatics (2023)
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Jonathan C. Chen, Jonathan P. Chen, Max W. Shen, Michael Wornow, Minwoo Bae, Wei-Hsi Yeh, Alvin Hsu, David R. Liu
Nature Communications (2022)
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Cut out the annotator, keep the cutout: better segmentation with weak supervision
Sarah Hooper, Michael Wornow, Ying Hang Seah, Peter Kellman, Hui Xue, Frederic Sala, Curtis Langlotz, Christopher Ré
ICLR (2021)
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Medical Event Data Standard (MEDS): Facilitating Machine Learning for Health
Bert Arnrich, Edward Choi, Jason Alan Fries, Matthew B.A. McDermott, Jungwoo Oh, Tom Pollard, Nigam H. Shah, Ethan Steinberg, Michael Wornow, Robin van de Water
ICLR: TS4H Workshop (2024)
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Bedi et al. (+ many authors)
Under review (2024)
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Callahan et al. (+ many authors)
Under review (2024)
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Tianyun Liu, Shiyin Wang, Michael Wornow, Russ B. Altman
PLOS Computational Biology (2022)
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Inter-region transfers for pandemic surges
Kenneth A Michelson, Chris A Rees, Jayshree Sarathy, Paige VonAchen, Michael Wornow, Michael C Monuteaux, Mark I Neuman
Clinical Infectious Diseases (2020)
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Wei-Hsi Yeh, Olga Shubina-Oleinik, Jonathan M. Levy, Bifeng Pan, Gregory A. Newby, Michael Wornow, Rachel Burt, Jonathan C. Chen, Jeffrey R. Holt, David R. Liu
Science Translational Medicine (2020)
Experience
Microsoft Research
Machine Learning Research Intern Summer 2023 |
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Insitro
Machine Learning Intern Summer 2021 |
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Broad Institute of MIT & Harvard
Research Assistant, David Liu Lab Fall 2018 - Spring 2020 |
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Bain & Company
Associate Consultant Intern Summer 2019 |
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Goldman Sachs
Global Investment Research Summer Analyst Summer 2018 |
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Facebook
Software Engineering Intern Summer 2017 |
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Joint Genome Institute
Bioinformatics Intern Summer 2017 |
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Joint BioEnergy Institute
Bioinformatics Intern Summer 2015 |
Education
Stanford University | 2020 - Present
PhD Candidate, Computer Science |
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Harvard College | 2016 - 2020
AB, Double Major in Computer Science & Statistics |
Projects
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Applying Deep Learning to Discover Highly Functionalized Nucleic Acid Polymers that Bind to Small Molecules Computational Biology
Spring 2019 - Spring 2020
Undergraduate senior thesis. A conditional variational autoencoder (CVAE), after training on one run of SELEX, learned to embed aptamers in a latent space from which novel aptamers with strong binding affinities for a target molecule could be generated through conditional sampling.
Links: Thesis
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myScheduleShare Website
Fall 2013 - Summer 2015
A school-centric, collaborative scheduling system for students and faculty. Allows users to share schedules with friends, track classes, plan meetings, stay updated on homework, and more. More flexible scheduling features than Google Calendar and Microsoft Outlook.
Links: Website | PDF Overview
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Improved Harvard QGuide Website
Winter 2018
Improved version of Harvard's course evaluation system, the "QGuide." A searchable, sortable interface containing all comments, evaluations, and courses offered at Harvard University from Fall 2006 - Spring 2019.
Links: Website
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College Essay Management Dashboard Website
Summer 2019
Built a free, mobile-friendly dashboard in React for college counselors to better manage their students' essays. Includes support for Google Docs/Microsoft Word/PDFs, automated payment processing, and a sophisticated permissioning system.
Links: Website
Teaching
Artificial Intelligence: Principles and Techniques (CS 229)
Course Assistant Summer 2024 |
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Artificial Intelligence: Principles and Techniques (CS 221)
Course Assistant Fall 2023 |
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Graduate Cybersecurity (CS 263)
Teaching Fellow Fall 2019 |
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Machine Learning (CS 181)
Teaching Fellow Spring 2019, Spring 2020 |
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Introduction to Computer Science (CS 50)
Teaching Fellow Fall 2017 |
Talks
Automating Enterprises With Foundation Models
May 2024 Links: Video |
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Large Language Models (LLMs) for Healthcare
May 2024 Links: Video |
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Shaky Foundations of Clinical LLMs
March 2024 Links: Video |
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Foundation Models for EHRs
November 2023 Links: Video |