Michael Yao is an MD-PhD candidate at the University of Pennsylvania leveraging AI to improve human health.
ML graduate student
I am an MD-PhD candidate advised by Osbert Bastani and James Gee. My research focuses on trustworthiness and robustness for deep learning, offline optimization, meta-learning, and bandit problem formulations. I am broadly interested in developing methods that leverage prior knowledge and data to help algorithms better generalize to new distributions. I explore these problems in the setting of generative design, medical imaging, and reducing health disparities.
I am grateful to be supported by an NIH F30 NRSA Fellowship from the National Institute on Minority Health and Health Disparities (NIMHD).
self.Timeline
"""Some professional and life milestones."""
self.Changelog
"""Recent news and publications."""
self.Handles
"""Where to find me on the internet."""
self.Teaching
"""Mentorship and education efforts."""
self.Outreach
I designed and run a short course on the fundamentals of ML for medical students. I have previously served as Vice Chair of the Technology Committee for the American Physician Scientists Association (APSA) and as Director of Data Science and AI for MDplus. At Penn, I am involved in a number of mentorship and outreach initiatives and have served on both the Admissions Committee and AI Curriculum Steering Committee for the School of Medicine.
I am actively involved in Penn's interview and recruitment process for medical school admissions. I set aside half 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.