Austin Atsango

Agents data: Deep Research, Model Context Protocol (MCP)

- Developed machine-learned potentials to run molecular dynamics (MD) simulations of reactive defects in water with Density Functional Theory (DFT)-level accuracy but at a fraction of the cost of the reference simulations - Explored the use of generative models, namely diffusion models and normalizing flows, for the conditional generation of three-dimensional molecular structures with target properties - Collaborated with an experimental group to study the catalytic effect at an enzyme active site by conducting simulations of a vibrational probe that measured electric field orientations - Performed MD simulations that model the quantum mechanical nature of both electrons and nuclei in order to elucidate the proton transport mechanism in hydrogen-bonded liquids such as imidazole and triazole - Developed quantum-classical simulation techniques that accurately model linear and nonlinear electronic spectra in open quantum systems such as the Fenna–Matthews–Olson photosynthetic complex Thesis title: Developing Methods for Simulating Reactive Condensed-Phase Chemical Systems via Quantum Dynamics and Machine Learning

Teaching assistant for quantum mechanics, statistical mechanics, thermodynamics, and computational chemistry. Developed course material, held office hours, led class discussions, administered dry lab sessions, and delivered stand-in lectures

Developed and implemented a novel contrastive learning framework that incorporates structural 3D molecular data in property prediction tasks. Work resulted in a workshop paper for the 2022 NeurIPS conference.

Studied the transfer of energy between inorganic quantum dots and organic molecules in order to better understand the mechanism of exchange-mediated photon-photon upconversion. Photon-photon upconversion in such hybrid organic-inorganic interfaces has found applications in biological imaging and data storage.

Studied the photocatalytic potential of interfaces between nanosheet Cadmium Sulfide and graphene. Presented the results of my research at the Vassar URSI symposium and at the Mid-Hudson ACS Undergraduate Research Symposium.

Graduated with both general and departmental honors. Inducted into Sigma Xi (The Scientific Research Honor Society), and received the Jeffrey Chance Memorial Award for excellence in both coursework and research in chemistry.