Research

My research focuses on building ML systems for scientific problems — particularly at the intersection of AI, chemistry, and structural biology. I’ve worked across protein design, RNA folding, molecular modeling, and LLM-driven bioengineering.

Acceleration Consortium — Matter Lab/Organic Small Molecule Self-Driving Lab

Summer Undergraduate Research Program in Accelerated Discovery - Machine Learning Research Intern | May – August 2026 | Toronto, ON

• Developing data-driven agentic platforms to optimize complex organic synthesis in a self-driving lab for pharmaceuticals, catalysis, and functional materials.
• Contributing to the El Agente Fármaco project, developing agentic AI systems for early-stage drug discovery.

University of Toronto — Chemspace Lab

Research Student — Algorithm and Machine Learning | May 2024 – August 2024, January 2026 - Present | Toronto, ON

• Investigated methods for designing chemical features for molecular energy curves by comparing interpolation-based 3D sorting with ML-based approaches, analyzing how ordering/representation of atoms affects downstream model interpretability.
• Implemented algorithms such as A*, locality-sensitive hashing, and genetic algorithms on molecular energy curve sorting. Developed a KNN classifier to group molecules for generating smooth 3D molecular energy curves.
• Explored how a generative Gaussian mixture model with cross-validation using PyTorch could predict low-energy conformers of 4-atom molecules.
• Researching alchemical invariant exchange molecular representation and data efficient machine learning.

Yale University — Gerstein Lab

Research Assistant — Protein Design | August – September 2025 | Remote

• Contributed to an inverse-folding based protein design paper (under review at Nature Computational Science), including designing evaluation experiments and writing sections of the manuscript and point-to-point rebuttal letter.
• Researched and implemented experiments to test model performance against protein design benchmarks (PepMerge for peptide design, SAbDab for antibody design) to address reviewer concerns.
• Analyzed sources of poor model performance on specific proteins in the CATH 4.2 test set, providing explanations to guide further refinement.
• Improved model performance by addressing benchmark limitations, including implementing new evaluation metrics informed by chemistry and biology background.

National University of Singapore — SERIUS Internship

Research Internship — Large Language Models | May – August 2025 | Singapore

• One of thirty students from North America selected for the 2025 SERIUS internship program at NUS.
• Defined the project scope and led end-to-end research on evaluating and fine-tuning LLMs for metabolite pathway engineering.
• Engineered a complete dataset pipeline by converting a newly published metabolite database into graph representations and generating chain-of-thought prompts to improve reasoning over bioengineering data.
• Designed and conducted experiments evaluating table-, graph-, and text-based fine-tuning using models such as Google Gemma and DeepSeek, benchmarking with BLEU, ROUGE, and custom biological reasoning metrics.
• Secured $8,000 CAD in research funding from the University of Toronto to support project execution.

Pioneer Academics

Researcher — Computational Chemistry | May – September 2022 | Remote

• Modeled the secondary and tertiary structures of the HIV-1 RNA terminal loop hairpin, integrating computational chemistry and molecular structural analysis under the mentorship of Professor Leckta (Johns Hopkins University). Achieved a grade of A.
• Utilized Gaussian, GAMESS, and Spartan to optimize 3D RNA conformations and studied how hairpin folding influences key molecular properties, including polarity, energy, intramolecular forces, and interactions with other molecules.

University of Alberta — Brown Lab

Research Assistant — Computational Chemistry | October 2021 – July 2023 | Edmonton, AB

• Assisted in the research of the effects of distance and location of a charge on a HBDI chromophore molecule’s excitation energy in different solvent environments.
• Wrote scripts to automate DFT/Hartree-Fock calculations of molecules on Compute Canada with Bash.