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 cellular behavior. Ultimately, the goal of these models is to accelerate biotechnology innovation, from biomanufacturing to drug discovery. Check out published work here.
Through past and current projects, I've polished my skills in machine learning and mechanistic modeling. In addition to research, I enjoy sharing this knowledge as a Teaching Assistant for the Graduate Course CHE1147 (Chemical Data Science and Engineering).
When taking a break from the code, I recharge through fitness. I’ve been passionate about weightlifting for over five years, and recently picked up interval running.
Publications
Bridging Sequence and Kinetics: Utilizing Multi-scale Representations for Genome-Scale Metabolic Models,
Poster Presentation
ICLR 2025: Learning Meaningful Representations of Life Workshop
Enhancing Compound-Protein Interaction Prediction with Confidence Assessment
Oral Presentation
American Institute of Chemical Engineers Annual Meeting (AIChE) 2024
kinGEMs: Advancing Enzyme-Constrained Genome-Scale Models with Deep Learning Predicted Kinetic Parameters
Oral Presentation
9th Conference on Constraint-Based Reconstruction and Analysis (COBRA)
Skills
Models
- Neural Networks
- Deep Learning
- Constraint-Based Optimization
Languages
- Python
- MATLAB
- HTML
- CSS
Tools
- NumPy
- Pandas
- scikit-learn
- Bash/Shell Scripting
- PyTorch
- Git
- LaTeX
Graphic Design
- Adobe (Photoshop, Illustrator, Premiere Pro)
- Affinity (Photo, Designer, Publisher)