I am a biomedical software developer with a background in biochemistry and computer science. My interests are varied, including machine learning, distributed and high-performance computing systems, and molecular and mathematical models of cells and disease. I am interested in developing tools to enable large-scale simulation and analysis of biology through the application of computational technologies, with the ultimate goal of allowing predictive tools that can elucidate molecular pathways and enable personalized medicine.
Currently, I am the lead developer for the BioSimulations project and am working towards a Master’s degree in computer science, focusing on machine learning.
I enjoy biking and hiking in my free time, along with raising a cat and many houseplants.
BA in Biochemstry, 2019
Columbia University
MS in Computer Science, 2022 (expected)
Georgia Institute of Technology
I trained an agent in the OpenAI Gym LunlarLander-v2 environment using Double DQN, a Q-learning algorithm that uses two deep neural networks to estimate the value of each action in a given state.
RunBioSimulations is an extensible, standards-driven web application for executing models across a broad range of modeling frameworks, simulation algorithms, and model formats and visualizing and sharing their results.
To facilitate biochemical research, we developed Datanator, an integrated database and set of tools for finding clouds of multiple types of molecular data about specific molecules and reactions in specific organisms and environments, as well as data about chemically-similar molecules and reactions in phylogenetically-similar organisms in similar environments.