John Kitchin studies catalysis on metals and metal oxides using density functional theory. He develops software for modeling materials, solving engineering problems, and writing scientific documents. He also studies new materials for CO2 capture applications.
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.
Using Machine Learning to Improve Molecular Simulations
Data science and machine learning approaches to catalysis
In a keynote at the AIChE annual meeting, John Kitchin illustrated what is possible when we think broadly about data science and machine learning.
Kitchin to receive the Award for Innovation in Chemical Engineering Education
ChemE’s John Kitchin will receive the Award for Innovation in Chemical Engineering Education from the American Institute of Chemical Engineers.
Kitchin to receive Award for Innovation in Chemical Engineering Education
AIChE recognizes John Kitchin for his impact on modern chemical engineering pedagogy and computational research.
Making sense of too much data
With hundreds of research papers published each day, synthesizing all of the available information for literature reviews has become increasingly difficult. Now, professors and librarians at Carnegie Mellon University are teaming up to find and teach unique techniques to uncover pertinent information for academic studies.
Kitchin develops STEM-focused Python course
Carnegie Mellon Chemical Engineering Professor, John Kitchin, is carving out a path for scientists and engineers to learn the computer programming language, Python. His new nine-booklet series combines over 20 years of knowledge with an easy-to-follow, step-by-step approach.
Researchers develop package to accelerate geometry optimization in molecular simulation
John Kitchin is speeding up molecular simulation by providing a neural network-based active learning method that accelerates geometric optimization.
Move to remote research invites innovation
While much of our lives can now function remotely, the transition to online poses unique challenges for academia—particularly for research universities like Carnegie Mellon.
New software makes science more replicable
John Kitchin has developed a comprehensive scientific reporting software, known as SCIMAX, which aims to make studies more reliable and more replicable.
Kitchin discusses hurdles in machine learning
ChemE’s John Kitchin was a keynote speaker at the Pacific Northwest National Laboratory conference and discussed issues in applying computations from machine learning to experimental research.
Kitchin receives grant from DOE’s Office of Science
ChemE’s John Kitchin received a grant from the U.S. Department of Energy’s Office of Basic Energy Sciences to study selectivity in the single atom alloy limit.