Sustainable chemical synthesis design hinges on efficiency and deep mechanistic insight-two intimately linked principles.

Our research focuses on the development of advanced catalytic strategies, encompassing transition metal catalysis, organocatalysis, photocatalysis and electrocatalysis. We design and implement versatile multicomponent reactions to access complex molecular architectures in a step- and atom-economical fashion.

We perform in-depth mechanistic investigations using complementary experimental and analytical techniques, with a particular emphasis on elucidating the behavior of metal-catalyzed transformations. These studies guide the rational tuning of catalysts, conditions and reactor setups toward more robust and sustainable processes.

Most recently, we have integrated machine learning tools to accelerate reaction optimization and guide catalyst and condition selection. This data-driven approach uncovers hidden reactivity patterns across our multicomponent and catalytic manifolds, thereby streamlining synthetic planning.

Collectively, these efforts expand the synthetic chemist’s toolkit through rational design, enabling more efficient and sustainable routes to valuable molecular targets.