I am a senior principal scientist at Vertex Pharmaceuticals, where I lead data and computational strategy for one of the company’s highest-priority therapeutic programs.
My work integrates physics-based modeling and machine learning to guide molecular design from early discovery through clinical candidate selection and regulatory submission. I have contributed to multiple clinical candidates and have authored sections of Investigational New Drug (IND) and New Drug Application (NDA) documents.
In addition to hands-on scientific work, I serve on a project leadership team and cross-functional task forces that advise senior leaders on strategy, modeling direction, and portfolio-level decisions. I am particularly interested in developing computational methods that bridge rigorous physical modeling with modern AI approaches to improve decision-making in drug discovery.
Before joining Vertex, I was a postdoctoral fellow with Mike Gilson at UC San Diego and the Open Force Field Initiative, where I worked on nonequilibrium statistical mechanics of protein dynamics, binding free energy methods, and force field development.
I earned a Ph.D. in Biochemistry & Biophysics at Penn, where I was advised by Paul Janmey and Ravi Radhakrishnan, and an A.B. in Physics from Kenyon College.
For more professional information, find me on LinkedIn, GitHub, or Google Scholar.