Welcome to the Kitchin Group

Our group utilizes data science and machine learning to solve problems in catalysis and engineering. Our current focuses include developing machine learned potentials for molecular simulations, and design of experiments for high-throughput experimentation.

News

• June 17, 2025 New Publication - Solving an inverse problem with generative models
• May 07, 2025 New publication - The Evolving Role of Programming and Llms in the Development of Self-Driving Laboratories
• April 11, 2025 New publication - A Classification-based Methodology for the Estimation of Binary Surfactant Critical Micelle Concentrations
• March 17, 2025 New publication - CatTsunami Accelerating Transition State Energy Calculations With Pretrained Graph Neural Networks
• February 11, 2025 New publication - Accessing Numerical Energy Hessians With Graph Neural Network Potentials and Their Application in Heterogeneous Catalysis

Current post (615 and counting)

New Publication - Solving an inverse problem with generative models June 17, 2025

Inverse problems—where we aim to find inputs that produce a desired output—are notoriously challenging in science and engineering. In this study, I explore how generative AI models can tackle t ... click here for more