While I was raised here in North Carolina, I pursued my undergraduate degree in statistics and mathematics at the University of Toronto (UofT) at the St. George Campus. While at UofT, I took courses in machine learning theory, measure-theoretic statistics, and survival analysis to broaden and deepen my knowledge of statistics. My research extends from in-silico protein engineering with machine learning under Dr. Keith Pardee to novel biostatistical methods under Dr. Clement Ma.
From left to right: Dr. Nathan Taback, myself, Steven Cheng, Kaylen Wei, Eudora Hong, Dr. Ryan Webb, and Dr. Samantha-Jo Caetano.
I gave a presentation at the Duke Industry Statistics Symposium on my work with Dr. Ma. This poster presentation featured new results not presented in JSM, including simulations showing how, under the fastest possible scheme, our trial generalization still drastically reduced the trial duration at a negligible loss in power.
Poster: https://drive.google.com/file/d/1HJDRbUJEcHCBndTdom9BdAF6JtlhPakn/view?usp=sharing
I gave a presentation at the Joint Statistical Meetings on my research into a generalization of a basket trial method I built under the supervision of Dr. Clement Ma. The presentation lasted 15 minutes and was attended by upwards of 30 people. More information can be found in the research tab of this website about what was presented.
In the image: myself (on the left) and Dr. Cyrus Mehta (session chair, on the right)
I competed in DataFest as a senior at the University of Toronto while completing my bachelor's degree. My teammates were Steven Cheng, Eudora Hong, and Kaylen Wei (4th-year students in statistics with me), and we called ourselves "Team Survivors," considering that we had just survived UofT's statistics program and were interested in biostatistics. We received the "Best Presentation" award.
More Information: https://www.statistics.utoronto.ca/past-datafest-at-UofT#past-datafest-accordion-1