Michael Yao is an MD-PhD candidate at the University of Pennsylvania passionate about engineering solutions to improve human health and wellbeing.

Currently

Second-year medical student, ML graduate student

I am an MD-PhD candidate advised by Osbert Bastani and James Gee in the Department of Bioengineering at the University of Pennsylvania. Previously, I was a research scientist intern at Microsoft Research advised by Michael Hansen.

My research focuses on building safe and interpretable neural networks for medical image analysis and patient healthcare data. I explore problems related to distributional shift and domain generalization for tasks such as lesion detection, uncertainty quantification, and out-of-distribution detection. I am also interested in developing methods to improve patient accessibility to healthcare.

self.Timeline

"""Some professional and life milestones."""

2022PhD Intern at Microsoft Research, Health Futures Image Reconstruction Team 2021MD-PhD candidate at the University of Pennsylvania, HHMI-NIH Interfaces graduate student 2021Interned on Hyperfine's Sequence Development Team as a Software Engineer 2021Graduated from Caltech 3rd in my class, BS Applied Physics

self.Changelog

"""Recent news and publications."""

2023Will be giving a talk on our recently accepted work on a novel MRI pulse sequence method for high-resolution imaging of neurocognitive disease at the upcoming ISMRM annual meeting. 2022Excited to share our new work on fully supervised prediction of patient diabetes risk from abdominal CT scans! 2022New work on developing ML methods to enhance accelerated MRI reconstruction techniques in Proceedings of Machine Learning for Health (ML4H) 2022.

self.Handles

"""Where to find me on the internet."""

self.Teaching

Head TA, ACM95a: Complex Analysis and ODEs (Caltech) Winter 2021
TA, Ph106a: Graduate-Level Mechanics and Special Relativity (Caltech) Fall 2020
TA, ACM95b: PDEs (Caltech) Spring 2020
TA, Ph12b: Quantum Mechanics (Caltech) Winter 2020
TA, Ph12a: Waves and ODEs (Caltech) Fall 2019
TA, CS 24: Computer Operating Systems (Caltech) Fall 2019
TA, Ph1c: Freshman E&M (Caltech) Spring 2019
TA, Ph1b: Freshman E&M and Special Relativity (Caltech) Winter 2019

self.Outreach

I currently serve as the full-stack developer and a volunteer mentor for MD Collective, a 501(c)(3) nonprofit aimed at making medical school admissions more accessible for underrepresented students. I have also been a mentor in the Step-Ahead Mentorship Program at the University of Pennsylvania since 2021. I am also the Director of Data Science and AI for MD+, a community of over 2,500 medical students and physicians.

During college, I served as editor-in-chief of the Caltech Undergraduate Research Journal, and was a volunteer tutor for Caltech students through the Deans' tutoring program, and for local high school students through the RISE Tutoring Program. I also helped develop the freshman core curriculum while serving on the Caltech Academics and Research Committee and was also a student ambassador for the Summer Undergraduate Research Program.

I am actively involved in Penn's interview and recruitment process for medical school admissions. I set aside an hour a week to meet with current students for pro bono feedback on applications and general college advice, especially for underrepresented students from minority backgrounds. If you're interested in connecting, feel free to reach out to me via email or Twitter.