Projects

Autonomous Discovery for Materials and Molecules

We develop AI agents powered by large language models to autonomously explore, design, and optimize new materials and molecules. Our research includes autonomous catalyst discovery, 2D material design, and molecular synthesis planning, aiming to accelerate breakthroughs in energy, electronics, and sustainable technologies.

Scalable Screening with AI and Simulation

We build large-scale datasets and machine learning models grounded in quantum chemistry simulations. These scalable frameworks enable rapid screening of vast chemical and materials spaces, reducing the time and cost required for identifying candidates with desired performance and stability.

AI Frameworks for Experimental Characterization

Our group builds foundation models that integrate various modalities from experiments, including spectroscopy, microscopy, and scattering techniques. These models enable more accurate interpretation of experimental data, uncover hidden structure–property relationships, and guide the design of novel functional materials.

Open Software for Reproducible Science

The Ock Research Group is committed to advancing open science by developing accessible, well-documented computational tools that ensure reproducibility and transparency. Our software efforts focus on enabling the broader scientific community to reuse, validate, and extend our methods.