Title:: Materials Day 2025: From Automation to Collaboration: The Future of Self-Driving Labs

Abstract: Self-driving labs (SDLs) are powerful tools for materials research in which experiments are performed by robots and chosen by machine learning or artificial intelligence. This combination makes them highly effective at rapidly executing many consistent experiments that are intelligently chosen to best achieve a user-specified goal. This field has rapidly progressed with advances in machine learning algorithms, the automation powering the experiments, and ultimately the discovery of new materials. However, realizing a new self-driving lab still requires a tremendous investment in terms of equipment and expertise, which limits their ubiquity. This workshop is organized to bring together developers of SDL hardware, SDL software, and users of SDLs to share success stories, lessons learned, and collaboratively build a community of practice that spans the academy, national labs, and industry. The workshop will feature eight keynote speakers, lightning talks from trainees, and networking events. The event is co-hosted by the Boston University Division of Materials Science and Engineering and the Rafik B. Hariri Institute for Computing and Computational Science and Engineering.

Speakers: Tonio Buonassisi, MIT; Douglas Densmore, Boston University DAMP Lab; Peter Frazier, Cornell University; Gabe Gomes, Carnegie Mellon University; John M. Gregoire, Lila Scientific; Malte Jung, Cornell University; Nadya Peek, University of Washington; Joerg Werner, Boston University