About Me
Hi there! I am a first-year medical student at Queen’s university. My path here was rather non-linear - I have long-standing interests in both math and medicine, and I am still on the journey of finding my place at their intersection.
Although my research interests are an ongoing discovery, I am currently drawn to the world of computational biology and to applications of computer vision to medical imaging. My goal is to merge the clinical knowledge I’ll gain in the next few years with my statistical and computational experience in a way that can positively impact patient care.
My Career Path
My career started off in the Faculty of Math at the University of Waterloo, where I studied Computer Science and Statistics. I completed 6 internships in the technology sector with focuses ranging from application development to machine learning. My last internship was at Bloomberg (News AI), where I worked on NLP models for predicting news persistence based on textual and quantitative features. I was also an intern at Stripe, where I worked on object detection models and text extraction on the Identity team.
I took my first full-time role at Stripe as a software engineer after graduating. I worked on the Risk Tooling team, where I built tools that help risk analysts detect fraud. I worked in languages like Ruby and ReactJS to build data pipelines, backends, and user-friendly interfaces for processing and displaying sensitive financial data.
After that, I completed my Masters in Statistics and became involved in biostatistics research. I was supervised by Dr. Gabriela V. Cohen Freue, and my Masters thesis is titled Robust sparse covariance-regularized regression for high-dimensional data with Casewise and Cellwise outliers. I’m also passionate about teaching, and thoroughly enjoyed my time first as a graduate TA, then as an instructor for DSCI 100 at UBC.
Publications
- Liu, Yitong Maggie. Robust sparse covariance-regularized regression for high-dimensional data with Casewise and Cellwise outliers. Diss. University of British Columbia, 2023.
- Liu, Maggie, Jing Wang, and Daniel Preoţiuc-Pietro. “Analyzing and Predicting Persistence of News Tweets.” Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers). 2023.
Teaching
- Sessional Lecturer at UBC, DSCI 100 (Introduction to Data Science) | S23, F23, W24
- Head TA at UBC, STAT 251 (Elementary Statistics) | W23
- Grad TA at UBC, STAT 301 (Statistical Modeling for Data Science) | F22
- Grad TA at UBC, STAT 251 (Elementary Statistics) | F21, W22
Education
- MD (Candidate), Queen’s University, 2024-2028
- MSc in Statistics, University of British Columbia, 2021-2023
- BMath in Computer Science and Statistics, University of Waterloo, 2015-2020
For Fun
Outside of school and work, you might find me climbing, snowboarding, playing piano, or drawing. You can find some of my art here. I dabble in digital drawing but also enjoy colored pencils and ink media.
