John Kitchin
John E. Swearingen Professor, Chemical Engineering
Courtesy Appointment, Materials Science and Engineering
John Kitchin works at the intersection of machine learning, data science, and scientific programming with science and engineering. He develops software for modeling materials, solving engineering problems, and writing scientific documents. He uses these tools to model catalysts with applications in energy, to solve inverse problems in engineering, and to find new approaches in developing surrogate models for engineering systems.
Kitchin completed his B.S. in chemistry at North Carolina State University. He completed an M.S. in materials science and a Ph.D. in chemical engineering at the University of Delaware in 2004 under the advisement of Dr. Jingguang Chen and Dr. Mark Barteau.
He received an Alexander von Humboldt postdoctoral fellowship and lived in Berlin, Germany for 1½ years studying alloy segregation with Karsten Reuter and Matthias Scheffler in the Theory Department at the Fritz Haber Institut. Kitchin began a tenure-track faculty position in the Chemical Engineering Department at Carnegie Mellon in January 2006. He was awarded a DOE Early Career award in 2010. He received a Presidential Early Career Award for Scientists and Engineers in 2011. He completed a sabbatical in the Accelerated Science group at Google learning to apply machine learning to scientific and engineering problems in 2018. In 2023, he was the recipient of the AIChE Award for Innovation in Chemical Engineering Education.
Using Machine Learning to Improve Molecular Simulations
Education
2004 Ph.D., Chemical Engineering, University of Delaware
2002 MS, Materials Science and Engineering, University of Delaware
1996 BS, Chemistry, North Carolina State University
Media mentions
Chemical Engineering
A more efficient training workflow for hybrid modeling
Researchers apply long-standing optimization methods to new technology, creating a workflow that effectively and efficiently trains scientific machine learning models.
CMU Engineering
Training students to bring fundamentals to AI frontiers
Chemical engineering students learn to fuse domain knowledge with machine learning and data science, a combination of skills that puts them at the forefront of changes in industry.
Chemical Engineering
Recent alums advance AI for science at startups
Adeesh Kolluru, Yuri Sanspeur, Brook Wander, and Xiaoxiao (Lory) Wang apply their chemical engineering training at the intersection of AI, computational chemistry, and materials science.
Colombo Tedesco and Stinchfield receive travel awards for AIChE
ChemE Ph.D. students Carolina Colombo Tedesco and Georgia Stinchfield received Women in Chemical Engineering (WIC) Travel Awards to attend the 2025 American Institute of Chemical Engineers (AIChE) annual meeting. Colombo Tedesco also received a Travel Award from the AIChE Catalysis & Reaction Engineering Division.
Chemical Engineering
Agentic science and the rise of the self-driving lab
In a Q&A, John Kitchin and collaborators discuss how AI that can think and act like a junior scientist could revolutionize science and how the technology can be used responsibly.
Chemical Engineering
Prototyping generative approaches with Claude-Light
A learning tool built by John Kitchin helps researchers use generative models and autonomous labs to reshape traditional approaches to research.
Three Ph.D. students recognized by American Chemical Society
ChemE Ph.D. students Andrew Ashmar, Carolina Colombo Tedesco, and Sarah Sonbati were selected as recipients of the 2025 ACS Graduate Student and Postdoctoral Scholars Recognition Program. Ashmar works with ChemE’s Daphne Chan. Colombo Tedesco works with ChemE’s John Kitchin and Carl Laird. Sonbati works with ChemE’s Anne Skaja Robinson.
Chemical Engineering
Machine learning model predicts magnetic properties of materials
With state-of-the-art prediction accuracy and data efficiency, a new model makes it more feasible to design magnetic materials and understand the effects of magnetism in catalysis.
TechVibe Pittsburgh
Kitchin discusses Carnegie Mellon joining MDS-Rely
ChemE/MSE’s John Kitchin was featured on the TechVibe Pittsburgh podcast to discuss Carnegie Mellon joining the MDS-Rely research cooperative.
Chemical Engineering
Carnegie Mellon University announced as third MDS-Rely site
Led by John Kitchin, the CMU team brings expertise at the intersection of data science and artificial intelligence to an industry-university collaboration that is advancing materials development.
Chemical Engineering
Kitchin awarded Swearingen Professorship
The College of Engineering has awarded the John E. Swearingen Professorship of Chemical Engineering to John Kitchin.
Chemical Engineering
New tool brings vector search to the scientific literature
John Kitchin created litdb, a Python package that helps researchers curate and use their own literature database.