
About
Heather J. Kulik is a Full Professor in the Departments of Chemical Engineering and Chemistry at the Massachusetts Institute of Technology (MIT). She received her B.E. from Cooper Union (2004) and Ph.D. from MIT (2009), followed by postdoctoral training at Lawrence Livermore and Stanford. Her research focuses on computational workflows and machine learning for materials discovery, particularly in catalysis and enzyme modeling.
Research interests include
- Electronic structure and density functional theory
- Machine learning in chemical discovery
- Transition metal chemistry and catalysis
- Computational modeling of functional materials
Recent publications emphasize
- Machine learning-driven catalyst optimization
- Stable metal-organic frameworks (MOFs)
- Electronic structure of transition metal complexes
- Enzyme mechanistic modeling
- Energy materials design
- Quantum chemistry applications
Scientific awards include the NSF CAREER Award (2019), Sloan Research Fellowship (2021), and AIChE CoMSEF Impact Award (2023).
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