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
- July 09, 2025 New publication - Hyperplane decision trees as piecewise linear surrogate models for chemical process design
- 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
Current post (617 and counting)
New publication - Hyperplane decision trees as piecewise linear surrogate models for chemical process design July 09, 2025
We’ve developed a new kind of decision-tree model that’s both smart and practical for tackling tough engineering problems. First, we take raw data and "lift" it into a richer feature space so w ...
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