I work in computational materials science and chemistry leveraging new techniques in machine learning to understand and predict the behavior of molecular systems accurately and efficiently.
With Prof. Boris Kozinsky in Harvard Engineering , I use machine learning and molecular dynamics simulation to acquire atomistic insights into materials and molecules.
With Prof. Yu-Shan Lin in Tufts Chemistry , I used molecular dynamics with enhanced sampling to understand the relationships between sequence and structure in cyclic peptides.
To push the boundaries of high throughput structural analysis, the lab uses machine learning to learn the structural ensemble of cyclic peptides observed in MD so that we can replace the need to perform MD after training an ML model (
J. Chem. Theory Comput.
With Prof. Cristian Staii in Tufts Physics and Astronomy, I developed
theoretical models to explain why neuron axons tend to align themselves with and grow along periodic patterns in their substrate
(
PLOS One.
With Dr. Jugal Sahoo in Prof. David Kaplan's lab in Tufts Biomedical Engineering ,
I worked to create silk-fibroin-based hydrogels and understand how their physical and chemical properties and biocompatibility changed
when prepared with different methods (
Biomater. Sci.