Fast Machine Learning for Science Conference 2026

Session

Birds-of-a-Feather Sessions

3 Sept 2026, 11:00

107. Beyond Fast Inference: Toward Adaptive Scientific Systems

Nhan Tran (Fermi National Accelerator Lab. (US))

Topical session

Scientific AI has made tremendous progress in accelerating inference, compressing models, and deploying machine learning at the edge. However, most scientific systems remain fundamentally open-loop: AI analyzes data or makes predictions, while scientists remain responsible for interpreting results, recalibrating instruments, updating models, and adjusting control strategies. The next frontier...

79. hls4ml Developers Forum

Benjamin Ramhorst (Imperial College (GB)), Jan-Frederik Schulte (Purdue University (US))

Topical session

[hls4ml][1] is a flexible, open-source platform that addresses these hardware development challenges by converting high-level neural networks from PyTorch, Keras, or similar frameworks into high-level synthesis (HLS) kernels suitable for deployment on FPGAs and ASICs. During this topical session, developers and users will discuss the evolving roadmap, open issues and challenges,...

108. LLM Agents for Science: Vibe Coding, Autonomous Scientists, and Beyond

Eric Anton Moreno (Massachusetts Institute of Technology (US)), Nan Huang (UC San Diego), Yue Ma

Topical session

LLM agents are reshaping how particle physicists interact with data, code, and the research process itself. From "vibe coding" to autonomous scientist frameworks capable of hypothesis generation and experiment design, these tools are beginning to transform workflows in high-energy physics.

This BoF session invites practitioners, skeptics, and enthusiasts to share experiences and openly...

111. SONIC - Inference as a Service

Yuan-Tang Chou (University of Washington (US))

Topical session

We would like to invite participants interested in working on or exploring the use of Inference as a Service in their experiments to present their use cases and ideas. The goal is to develop a Fast ML community vision that supports and encourages cross-experiment R&D efforts. The session is expected to consist of a series of lightning talks, with plenty of discussion in between to foster new...