Teaching
For slides, source code, and additional sample teaching materials see my projects page.
Guest Lectures
Exploring & Explaining Data in the Wild
AI & Data Science Post-Graduate Program, Loyalist College
Invited by Prof. Peter Papadakos as an annual guest lecturer in 2023 & 2024
Data Collection & Analysis
PRISM research & mentorship program, University of Toronto
Invited by Prof. Sadia Sharmin
Environmental & Life Sciences Workshop Series
STEMHub Foundation
R for bioinformatics workshop
Global Society for Genetics and Genome Biology
Research Mentorship
Kiki Zhang
Combined BS/MSE Student; Biomedical Engineering. Research internship via Computational Biology Student Program at MSKCC
Topic: Mutational signatures in the context of branching evolution
Fedir Zhydok
BS Student; Computer Science. Artificial intelligence in medicine, global classroom program at University of Toronto
Topic: Identifying metastatic tumours from mutational signatures
Caitlin Timmons
BA Student; Statistical and Datasciences, Biology. Research internship via Computational Biology Student Program at MSKCC. Went on to a Research Technician position at Dana-Farber Cancer Institute.
Topic: Modelling spatial distribution of mutational signatures in cancer genomes.
Haritha Lakshmanan
Highschool Student. Independent study at MSKCC. Went on to a combined BA/MD at Brooklyn College.
Topic: Automatic discovery of mutations predictive of survival in breast cancer patients
Testimonials
“I was fortunate to work with Cait for almost a year and had a wonderful experience. She was patient, supportive, and skilled at explaining complicated concepts in biology and programming. As a mentor, she has a great sense of when to guide you through a problem and when to let you work through challenges on your own. She helped me grow as a researcher and writer and I’m grateful for everything I learned from her.”
“As a mentor, Caitlin has greatly enhanced my ability to conduct research. She also provided valuable resources and aimed to make sure that I understood the fundamental concepts behind all the research conducted by breaking down difficult principles into easily comprehensible statements and thoughts. Additionally, she helped me find any sources of error as the research progressed. I enjoyed researching under her guidance, and I had an overall positive experience.”
Teaching Assistant Positions
CSC2541: Topics in Machine Learning: AI for Drug Discovery
Head prep TA
CrossTALK drug discovery bootcamp
Head TA
JSC370: Data Science II
JSC270: Data Science I
STA313: Data Visualization
PRISM: Preparation for Research through Immersion, Skills, and Mentorship
JSC370: Data Science II
CSC197: Privacy in the Age of Big Data Collection
STA4273: Minimizing Expectations
CSC197: Privacy in the Age of Big Data Collection
JSC270: Data Science I
CSC373: Algorithm Design, Analysis & Complexity