The Soc(AI)ety Seminars, hosted by the Lucy Family Institute for Data & Society, are a collection of talks with a vision for AI’s present and future impact on society. Each session is meant to inspire a dialogue on ethical and socially responsible Data & AI innovation. For more information, and to view previous Soc(AI)ety Seminars sessions, please visit the Soc(AI)ety Seminars webpage.
The sessions will be held in Room 101, Jordan Hall of Science (map).
Please RSVP if you plan to attend.
Description:
We are thrilled to host Connor Coley, the Class of 1957 Career Development Professor and an Associate Professor at MIT in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science.
In this session of the Soc(AI)ety Seminars, Coley will discuss the AI in science.
The role of AI in scientific discovery is ever-expanding, particularly in the domains of chemistry and biology where the use of machine learning is nearly ubiquitous in early-stage small molecule discovery. Our own contributions to this field include new methods and applications of AI to synthesis planning, generative molecular design, and structural elucidation through mass spec. In this talk, Coley will provide an overview of these efforts, their capabilities, their limitations, and their implications for dual use. AI does not obviate the complexity of molecular discovery; it merely provides us with additional tools to facilitate its pursuit.
Reception after talk to follow 4:30pm to 5:30pm. Indicate on RSVP form if you will attend either seminar only or both seminar and reception.For questions about event please send us an email at lucyinstitute@nd.edu
Guest Speaker Bio:
Connor W. Coley is the Class of 1957 Career Development Professor and an Associate Professor at MIT in the Department of Chemical Engineering and the Department of Electrical Engineering and Computer Science. He received his B.S. and Ph.D. in Chemical Engineering from Caltech and MIT, respectively, and did his postdoctoral training at the Broad Institute. His research group at MIT works at the interface of chemistry and data science to develop models that understand how molecules behave, interact, and react and use that knowledge to engineer new ones, with an emphasis on therapeutic discovery. Connor is a recipient of C&EN’s “Talented Twelve” award, Forbes Magazine’s “30 Under 30” for Healthcare, Technology Review’s 35 Innovators Under 35, the NSF CAREER award, the ACS COMP OpenEye Outstanding Junior Faculty Award, the Bayer Early Excellence in Science Award, the 3M NTFA, and was named a Schmidt AI2050 Early Career Fellow and a 2023 Samsung AI Researcher of the Year.