[AI Seminar Series] Seminar by Dr. Aldair Gongora (LLNL), Friday February 6th, 12-1pm, MRB Seminar Room

[Vassilis Tsotras]

The next AI Seminar will be on Friday February 6th, 12-1pm, in the MRB
Seminar Room (1st floor).

*** Pizza and refreshments will be provided ****

To keep track of the number of attendees, please *register* at:
https://www.eventbrite.com/e/ai-seminar-series-tickets-1982203305446

The talk will be given by *Dr. Aldair Gongora*, Lawrence Livermore National
Laboratory (LLNL)

TITLE: Accelerating Research in the Experimental Sciences: Enabling the
Shift from Automation to Autonomy through Self-Driving Laboratories

ABSTRACT:
The experimental sciences have long relied on labor-intensive, manual
workflows that limit scalability and slow the pace of research and
discovery. Despite advances in instrumentation and data analysis, the act
of performing physical experiments remains time-consuming and resource-
intensive, ultimately limiting the pace of exploration and innovation. The
emerging field of self- driving laboratories (SDLs) and autonomous labs
seeks to overcome these challenges by integrating robotics, automated
experimentation, and artificial intelligence (AI) to design and execute
experiments with minimal human intervention. Through this integration, SDLs
are redefining how research is conducted across scientific domains,
enabling a more adaptive, data- driven, and efficient approach to
scientific discovery.

In this talk, we first outline the foundational principles of SDLs and
discuss the critical transition from automated experimentation to
autonomous experimentation. Next, through a series of case studies, we
illustrate how increasing levels of autonomy transform experimental
workflows and enable systems that not only execute tasks but also make
data-driven decisions to guide discovery. We then examine emerging
challenges in autonomous laboratories, particularly the limited flexibility
and adaptability of systems that are often designed for narrow or limited
experimental workflows. As SDLs expand in scale and complexity, they become
increasingly vulnerable to unanticipated faults, underscoring the need for
resilient architectures that maintain performance under changing or complex
conditions. Finally, we highlight how integrating approaches such as
tele-robotic operation, large language models (LLMs), and agentic AI
frameworks may enhance adaptability and fault tolerance in these systems.
Together, these advances pave the way for the next generation of SDLs,
where intelligence and reasoning span both the system and instrument levels
of autonomous labs.


Bio:
Aldair Gongora is a staff scientist at Lawrence Livermore National
Laboratory (LLNL) and also serves as a deputy director for LLNL’s Data
Science Institute’s Consulting Service. His research work centers on
accelerating scientific discovery by developing next-generation research
platforms and capabilities, such as self-driving labs and autonomous robots
for science. His research work enables the adoption of modern tools to
tackle complex challenges across materials science, life sciences, and
advanced manufacturing. Aldair earned a B.S. in Mechanical Engineering from
Rockhurst University and a Master's and Ph.D. in Mechanical Engineering
from Boston University, where he conducted research on self-driving labs
and autonomous experimentation for mechanical design.

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Sponsored by the RAISE at UCR Institute, the AI Seminar Series presents
speakers working on cutting edge Foundational AI or applying AI in their
research. The goal of these seminars is to inform the UCR community about
current trends in AI research and promote collaborations between faculty in
this emerging field. These seminars are open to interested faculty and
graduate/undergraduate students. Please forward this email to other
colleagues or students in your lab that may be interested. After the seminar a
discussion will follow for questions, open problems, ideas for possible
collaborations etc.

Sincerely,
Vassilis Tsotras
Professor, CSE Department
co-Director, RAISE at UCR Institute

Amit Roy-Chowdhury
Professor, ECE Department
co-Director, RAISE at UCR Institute
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