I'm a 2nd year PhD student in the Laboratory for Metabolic Systems Engineering at the University of Toronto.
My research merges machine learning with metabolic engineering to develop computational models that predict the behavior of microorganisms. Ultimately, the goal of these models is to accelerate biotechnology innovation, from biomanufacturing to drug discovery.
In addition to research, I enjoy sharing this knowledge as a Teaching Assistant for the graduate courses CHE1147 Chemical Data Science and Engineering and CHE118 Artificial Intelligence for Applied Chemistry and Chemical Engineering.
Coding aside, fitness is a big passion of mine. I’ve been weightlifting for over six years, and hold a 1:47:00 personal best in the La Jolla Half Marathon.
Publications & Conferences
Machine Learning for Sequence‐to‐Function Approaches
Machine Learning and Big Data‐enabled Biotechnology
kinGEMs: A Robust and Scalable Framework for Resource-Constraint Models through Stochastic Tuning of Deep Learning-Predicted Kinetic Parameters
Preprint
Bridging Sequence and Kinetics: Utilizing Multi-scale Representations for Genome-Scale Metabolic Models,
ICLR 2025: Learning Meaningful Representations of Life Workshop