About Me
21 Jul 2022This is an old version of my website.
Visit here for my machine learning notes
Hello! I’m Daniel Shao. I’m a first year student at MIT-Harvard’s Health Sciences and Technology (HST) Program in Medical Engineering and Medical Physics (MEMP). I’m broadly interested in developing machine learning algorithms with clinical applications. I’m hoping to use this blog as an opportunity to document and share various concepts I learn along the way. Hopefully it can serve as guidance for those interested in getting started on similar career paths in the future! In my free time I love to play chess, so I’ll also include some details of what I’m studying there! If I’m not studying or researching, you can probably find me playing chess at Harvard Square.
My research
I’ve done a variety of research projects in my undergrad. Including
- Bacterial shape regulation at the Rutgers-Camden Klein lab
- Malaria proteomics at the Center for Global Health and Disease
- Chemical electrophoresis for drug polymerization at Primera Inc.
- Cholestatic liver pathology at the University of Pittsburgh’s Nejak-Bowen Lab
- Computational pathology to prognosticate Disease Free Survival at the Madabhushi Lab
I’m a fortunate member of Faisal Mahmood’s Lab at the Brigham and Women’s Hospital, where I’m studying the analysis of longitudinal data for patient prognosis.
Coursework
As part of the MEMP graduation requirements, I’m required to take 4 Technical electives in computer science, along with a variety of clinical courses at Harvard Medical School. This semester, I’ll be taking the following and hopefully sharing some of what I learn along the way!
- 6.867 Machine Learning (MIT)
- HST.030 Human Pathology (HMS)
- HST.590 Biomedical Engineering Seminar Series (HST)
- HST.160 Genetics in Modern Medicine (HMS)
Head to the readme to learn more.
Chess
I got into chess after watching the Queen’s Gambit in December 2020. Since then, I’ve been studying intently and improving pretty quickly. I’m now 1800 rated (99.3 percentile) on chess.com. You can find my notes in the sidebar to facilitate your own learning.