Make Self-Driving Labs Work:
Orchestration, Optimization, and Upgrades

About 

This tutorial introduces self-driving laboratories (SDLs) and software tools required to operate them, focusing on orchestration, optimization, and closed-loop experimentation. Through a demo-driven, hands-on format, attendees will work through notebooks or hosted tutorials to explore key concepts in practice. We begin with IvoryOS, which demonstrates how abstraction and a drag-and-drop interface produce reproducible workflows and reduce barriers for experimental teams. We then move to optimization. NIMO will then present a unified interface for invoking a variety of algorithms for closed-loop experimentation. NextSample turns Bayesian optimization into a customizable app layer for experiment-specific planning workflows. Finally, we introduce “legacy displacement,” a conceptual software development framework for upgrading SDL software without interrupting ongoing operation. The tutorial concludes with a panel discussion to interrogate limitations, clarify implementation, and identify opportunities for adoption. 

Check the tutorial page on the AI4X website

Program (tentative)

• 9:00 - 9:15 Introduction (Willi Gottstein)

• 9:15 - 9:45 IvoryOS (Wenyu Zhang)

• 9:45 - 10:15 NIMO (Ryo Tamura)

• 10:15 - 10:25 Break

• 10:25 - 10:55 NextSample (Mehrdad Mokhtari)

• 10:55 - 11:25 Legacy displacement (Ryan Oldford)

• 11:30 - 12:00 Panel discussion

Recordings

Organizers

• Mehrdad Mokhtari, Ryan Oldford, Zahra Azimi Dijvejin, Curtis P. Berlinguette, Wenyu Zhang (University of British Columbia)

• Willi Gottstein (University of Toronto)

• Naruki Yoshikawa, Ryo Tamura, Shoichi Matsuda (National Institute for Materials Science)