Regular biography
Heather J. Kulik is a Professor in the Department of Chemistry at the Massachusetts Institute of Technology. Her research focuses on leveraging multi-scale modeling, electronic structure calculations, and machine learning to discover new molecules and mechanisms in materials such as metal-organic frameworks, enzymes, and organometallics. Her group develops computational workflows and novel representations for machine learning accelerated materials discovery, aiming to improve the efficiency of traditional discovery approaches. Additionally, her work explores enzyme catalysis and the development of systematic modeling techniques to achieve predictive chemical accuracy in enzyme catalysis. She also investigates methods to enhance the accuracy and reliability of computational chemistry through artificial intelligence models and wavefunction descriptors.
Scholar-generated biography
Heather J. Kulik is a computational chemist specializing in transition metal chemistry, molecular design, and density functional theory. Her research focuses on leveraging computational methods to advance the understanding and design of transition metal complexes, with applications in catalysis and materials science. She develops and applies machine learning techniques to accelerate chemical discovery, particularly in the context of metal-organic frameworks and spin crossover complexes. Her work also addresses challenges in density functional theory, such as electron over-delocalization and the treatment of strongly correlated systems. Kulik's research bridges theoretical and experimental approaches to solve complex chemical problems.