Sophia Tang

Hi! I’m a third-year undergraduate student at the University of Pennsylvania conducting research at the intersection of ML and biological discovery! Aside from research, I’m also a dual degree student studying computer science and business in the Jerome Fisher Program in Management & Technology.

I’m part of the Chatterjee Lab, developing theoretical ML frameworks for biological design, and the Mitchell Lab, designing lipid nanoparticle (LNP)-based delivery vehicles to transport mRNA across the blood-brain barrier. Working across two labs has taught me so much about both the computational and wet-lab sides of bioengineering research, which you can explore on my publications page.

One of my favourite aspects of research is gaining a deep understanding of the theory behind the mechanisms governing the algorithms or biological processes that I study. To share this interest, I began writing in-depth technical guides on my Substack, Alchemy Bio. My most read article, “A Complete Guide to Spherical Equivariant Graph Transformers” is a 2.5-hour long read breaking down the mathematics and physics underlying the structural deep learning architectures for molecules and proteins.

If you’re also passionate about any of these topics, I would love to connect via LinkedIn or X.