Our AI for Science research aims at advancing quantum chemistry with cutting edge computational techniques from the past decade’s AI development. Computationally solving quantum chemistry is fundamental to many real world chemistry and material science applications such as catalysis (designing efficient chemical reactions), next-gen energy storage (optimizing lithium-ion batteries and solid-state electrolytes), smart materials (discovering high-performance superconductors or lightweight alloys).

While data driven methods are the current trend, we emphasize the importance to stay close to first principles. We believe the future of quantum chemistry to be an organic integration of ab-initio physics complemented with models learned with data for the best trade-off on speed and accuracy.

Alongside the problem solving, we develop general mathematical methods and computational tools with the belief that they are equally likely to be applied back and advance artificial intelligence.