Sean Griesemer, Ph.D. is a research scientist in the computational theoretical chemistry group. His work focuses on building computational infrastructure and developing scalable simulation and machine learning workflows to accelerate materials discovery for renewable energy and eco-remediation applications. Griesemer joined the Materials Discovery team in 2025.

During his time at Northwestern University, Griesemer conducted Ph.D. research in computational materials science, including density functional theory modeling of inorganic materials and machine learning approaches to discovering new thermodynamically stable compounds. He later served as a postdoctoral associate at Duke University, where he modeled the optical properties of complex high-entropy ceramics.

Griesemer holds a B.A. in physics from the University of Chicago and a Ph.D. in materials science and engineering from Northwestern University.