Heather J. Kulik | |
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Alma mater | Cooper Union B.E. (2004) Massachusetts Institute of Technology Ph.D. (2009) |
Scientific career | |
Institutions | Massachusetts Institute of Technology |
Thesis | First-principles transition-metal catalysis : efficient and accurate approaches for studying enzymatic systems (2009) |
Doctoral advisor | Nicola Marzari |
Other academic advisors | Judith Klinman, Todd Martinez |
Website | hjkgrp |
Heather J. Kulik is an American computational materials scientist and engineer who is an associate professor of chemical engineering at the Massachusetts Institute of Technology. Her research considers the computational design of new materials and the use of artificial intelligence to predict material properties.
Kulik earned her bachelor's degree in Chemical Engineering at Cooper Union in 2004. She moved to the Massachusetts Institute of Technology for her graduate studies, where she joined the Department of Materials Science and Engineering and worked under the supervision of Nicola Marzari.[1] During her doctoral research, she introduced a Hubbard U term to density functional theory calculations, which improved the study of transition metal complexes.[2] Density functional theory allows for the prediction and study of new materials with limited computational cost. Amongst these materials, Kulik concentrated on transition metal complexes, as their highly localized electrons make the unphysical decollimation that occurs in the simplifications of DFT inappropriate.[2] She graduated in 2009 with her Ph.D. in Materials Science and Engineering.
Kulik then conducted postdoctoral research with Felice Lightstone at the Lawrence Livermore National Laboratory. She then worked alongside Todd Martínez at Stanford University and Judith Klinman at the University of California, Berkeley on the large-scale electronic structures of biomolecules.[3]
In 2013, Kulik joined the faculty at the Massachusetts Institute of Technology as the Joseph R. Mares Career Development Chair.[3] She specializes in computational modeling and artificial intelligence to accelerate the discovery of new materials and catalysts. In particular, Kulik develops new strategies to improve the accuracy of density functional theory.[4][5]
Original source: https://en.wikipedia.org/wiki/Heather Kulik.
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