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

Currently

ML graduate student

I am an MD-PhD candidate advised by 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 robust 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."""

2023Excited to share our new work on predicting diabetes risk from abdominal CT scans in PRIME-MICCAI 2023. 2023Giving a talk on our recent work on developing a novel MRI spectroscopic method for high-resolution imaging of neurocognitive disease at the 2023 ISMRM annual meeting. 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, CIS 7000: Health, Healthcare and Technology (University of Pennsylvania) Fall 2023
TA, Introduction to Clinical Ultrasound Skills (University of Pennsylvania) Fall 2023
TA, Student Report in Pre-Clinical Medicine (University of Pennsylvania) Fall 2023
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 am currently working as Vice Chair of the Technology Committee for the American Physician Scientists Association (APSA). I am also the Director of Data Science and AI for MD+, a community of over 3,000 medical students and physicians. I 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.

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.