Our group works at the interface of theoretical chemistry with physics, computer science, and applied mathematics. In particular, we are interested in approaches that can be disruptive to the field. We develop and apply quantum computer algorithms for applications in the physical sciences such as the simulation of molecules and materials. We also are working towards the acceleration of molecular discovery by the combination of robotics, artificial intelligence, and high-throughput quantum chemistry to create what we call “materials acceleration platforms” or “self-driving laboratories”. We are a multidisciplinary team composed of chemists, physicists, computer scientists, etc. working both on theory and experiment.
Accelerating the discovery of new functional materials through the integration of high-throughput computation, machine learning, and chemical intuition.
Leveraging statistical patterns in chemical data we seek to explore and optimize in chemical space and improve the predictive power of theoretical methods to better match reality.
Self driving chemical laboratories
Orchestrating artificial intelligence and robotic solutions in “self-driving laboratories” to accelerate autonomous material discovery.
Developing quantum algorithms to access high-accuracy and high-throughput quantum chemical and machine learning calculations.