Our group is interested in the development and application of computational tools to address challenges in organic chemistry. This includes exploring new techniques in data science and machine learning to streamline analysis, optimization, and discovery tasks. We are also interested in the application of applied quantum chemistry for mechanistic interrogation of chemical reactions.
Data-Driven Analysis, Optimization, and Discovery
One prominent research area in our group will be the development of customized automation technology for organic synthesis. Two applications we are particularly interested in are autonomous high-throughput experimentation platforms and on-demand synthesis in flow. We envision these platforms will be fully integrated with our data-science tools, enabling closed-loop reaction optimization, reaction discovery, and molecular design campaigns.
Automation Technology for Organic Chemistry
New Approaches to Reaction Development
Our group is interested in the application of new technology to enable synthetic method development. We are particularly interested in applying data-driven approaches, flow technology, and high-throughput experimentation to create new synthetic transformations. Current areas of interest include (but are not limited to) synthetic electrochemistry and asymmetric phase transfer catalysis.
