Jonathan Woo

I’m a Research Engineer at Isomorphic Labs where I work on advancing the structure prediction capabilities of AlphaFold.

I’m driven by the potential of AI to transform drug discovery. Having taken part in clinical trials myself and experienced the impact of life-changing therapeutics, I know how helpless it feels when no effective treatment exists. That experience fuels my commitment to accelerate drug development and help relieve suffering.

My interests lie in fundamental deep learning research, AI for scientific discovery, and the engineering systems that make these advances possible. Recently, I’ve developed a fascination with electronic structure theory and quantum chemistry.

I earned my Bachelor’s in Engineering Science from the University of Toronto, where my thesis — Adaptive xTB — explored Bayesian optimization and machine learning for adapting empirical xTB parameters to individual molecules. Between my third and fourth years, I spent a year at MIT’s Lab for Translational Engineering, developing a deep learning–driven platform for mRNA lipid nanoparticle (LNP) drug discovery.

I love to learn — and I’m fortunate that so many things capture my curiosity. I find deep satisfaction in sitting down to think, reason, and solve hard problems, both old and new. Currently, I’m working through Modern Quantum Chemistry and participating in a Geometric Deep Learning study group. Learning at this level of depth gives me a sense of clarity and confidence to take on whatever challenges come next.