IEEE BigData 2026 Workshop · AI4AutoSci

AI for Autonomous Experimental Science:
From Instrument Design & Operation
to Scientific Discovery

A workshop bringing together AI/ML researchers and experimental scientists to advance the automation of scientific processes — from self-driving labs to hypothesis generation.

In-Person Workshop Physics & Materials Science Autonomous Laboratories AI for Science
Paper Submission
October 31, 2026
Notification of Acceptance
November 21, 2026
Camera-Ready Deadline
November 28, 2026
Workshop Date
TBD

Automation at the frontier of experimental science

Recent advances in artificial intelligence have opened exciting new directions for the natural sciences. This workshop focuses on the automation of actual experimental pipelines — from AI-guided instrument design to autonomous, self-driving laboratories conducting end-to-end experiments.

Our goal is to provide a platform for AI/ML researchers and experimental scientists to share ongoing work across physics, materials science, and biology. By facilitating discussion between researchers, we aim to address current challenges and identify emerging directions in this rapidly evolving space.

Unlike broader "AI for Science" workshops, our workshop places a targeted emphasis on the design and operation of experiments — a niche but timely sub-community that is currently underserved at top-tier AI and data science venues.

We welcome submissions on

Instrument & Experiment Design

Simulation, surrogate models, Bayesian optimization, and generalizing from simpler to complex experimental setups.

Instrument Operation & Maintenance

AI-based control systems, failure mode identification and mitigation, and driving systems to desirable states.

Autonomous Laboratories

Self-driving lab data analysis, agentic approaches for lab automation, and managing failure modes at scale.

Hypothesis Generation

Scientific reasoning from multi-modal data, AI-driven hypothesis formation, and cross-domain adaptation.

Agentic AI Systems

LLM-based agents for experimental planning, multi-agent coordination in scientific workflows, and tool use.

Domains & Applications

Physics, gravitational wave detection, materials science, chemistry, biology, accelerator tuning, and more.

Distinguished speakers

Speaker announcements coming soon. We are assembling an outstanding lineup of researchers spanning experimental physics, machine learning, autonomous laboratories, and materials science.

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Submit your work

We welcome original research papers on all aspects of AI for autonomous experimental science. Submission details and the portal link will be announced shortly. Papers should follow the IEEE BigData 2026 formatting guidelines.

Submission Details
Format: IEEE 2-column
Length: Up to 10 pages
Review: Double-blind
Proceedings: IEEE BigData
Presentation: In-person

Organizing Committee

E

Evangelos Papalexakis

Computer Science & Engineering, UC Riverside

Workshop Chair
J

Jonathan Richardson

Physics & Astronomy, UC Riverside

Workshop Chair
A

Aldair Gongora

Lawrence Livermore National Laboratory

Workshop Chair
S

Shaan Pakala

Computer Science & Engineering, UC Riverside

Logistics & Workflow Co-Chair
P

Paimon Goulart

Computer Science & Engineering, UC Riverside

Logistics & Workflow Co-Chair
S

Siddharth Soni

Physics & Astronomy, UC Riverside

Logistics & Workflow Co-Chair

Program Committee

To be announced.