Our research group is dedicated to pushing the boundaries of quantum chemistry by blending the power of quantum computing with traditional many-body methods. We’re also making quantum chemistry calculations smarter and faster using advanced machine learning and generative Artificial Intelligence. Our other approaches draw on non-linear dynamics and many-body theories to create efficient tools for the computation of accurate molecular properties for ground and excited states. With scalable fragment-based methods, we’re unlocking the chemistry of complex molecular systems, paving the way for transformative breakthroughs in materials science and beyond.