Each Element, Best-in-class

Nima is a Quantum Chemist who loves building products that leverage quantum simulation to solve big problems. A McKinsey and Rigetti alum, Nima holds a PhD in computational chemistry from Princeton.

Isaac is an Assistant Professor of Computer Science at UC Davis. He studies the structure of entanglement in quantum many-body systems that allows efficient simulation of such systems on classical and near-term quantum computers.

Frank is a professor at Freie Universitat, Berlin, Germany. He has done pioneering work in applying machine learning across physical sciences, including chemistry and biophysics. Among the wide range of contributions his interdisciplinary team has made to the field, they recently published a novel approach to leverage machine learning to perform high-accuracy quantum chemistry calculations.

Adrian is Professor of Chemistry at the University of Florida. His main research interest is in accurate calculations of biologically relevant molecular systems using quantum mechanics, statistical mechanics, molecular dynamics, and machine learning algorithms. He has made significant contributions to the development of molecular dynamics simulation techniques. Also, he is the inventor of ANI, one of the most widely used machine learning frameworks for simulating organic molecules.

Paul is a Professor of Chemistry at the University of Michigan, the inventor of the iFCI method, and the founding member of our scientific advisory board. iFCI recently paved the way for us to perform high-accuracy simulations on large molecules and is the first module available in the QEMIST cloud.