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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To Be AnnouncedSubmit 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.
Organizing Committee
Evangelos Papalexakis
Computer Science & Engineering, UC Riverside
Workshop ChairJonathan Richardson
Physics & Astronomy, UC Riverside
Workshop ChairAldair Gongora
Lawrence Livermore National Laboratory
Workshop ChairShaan Pakala
Computer Science & Engineering, UC Riverside
Logistics & Workflow Co-ChairPaimon Goulart
Computer Science & Engineering, UC Riverside
Logistics & Workflow Co-ChairSiddharth Soni
Physics & Astronomy, UC Riverside
Logistics & Workflow Co-ChairProgram Committee
To be announced.