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Fast Machine Learning for Science Conference 2026

31 August 2026 to 4 September 2026
US/Pacific timezone
We are offering in-person registration fee waivers (subject to funding availability) for graduate students on a first come first serve basis.

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Call for Abstracts

  • Opening day
  • Submission deadline

The Fast Machine Learning for Science Conference is an all-plenary conference. Tutorials and topical sessions are parallel.

We welcome abstract submissions for the following presentation formats:

  • Presentations and/or Posters: Posters will be shown during 1.5-hour poster sessions. The committee will select the 15-minute spotlight presentations. New for 2026: Submitters will also have the option to submit a 4-page extended abstract (paper) through OpenReview (details to follow).
  • Tutorials: In-depth tutorials (1.5-3 hours) on Monday, August 31. Specify level (beginner/intermediate/advanced).
  • Birds-of-a-Feather (BoF) Sessions: Topical, participant-driven discussions (1.5-3 hours) on Thursday, September 3 or Friday, September 4.

Topics

Topics include, but are not limited to

Machine Learning Algorithm Design & Optimization

  • Novel efficient architectures  
  • Hyperparameter optimization and tuning  
  • Model compression (quantization, sparsity)  
  • Hardware/software co-design for ML efficiency 
  • Large language model optimization and implementation

Accelerated Inference & Real-Time Processing

  • Low-latency ML for scientific experiments
  • FPGA/NPU/GPU-based ML acceleration 
  • ML for trigger systems and data acquisition  
  • On-detector and edge inference

Scientific Applications of Fast ML

  • High-energy physics, astrophysics, and astronomy
  • Space science and satellite-based ML  
  • Genomics and medical imaging  
  • Climate and environmental modeling
  • Biological science and  neuroscience
  • Fusion
  • Quantum computing   
  • Material science
  • Robotics

Scalable & Distributed ML Systems

  • Cloud-based, accelerated ML processing  
  • Distributed inference
  • Acceleration-as-a-service
  • ML compilers and runtimes
  • Benchmarks and datasets

Advanced Hardware & Computing Architectures

  • Specialized AI accelerators
  • Tools and methodologies for accelerating ML algorithms
  • Heterogeneous computing platforms for ML  
  • Beyond CMOS

Extended Abstracts

We will also accept 4-page extended abstracts to be submitted and reviewed through OpenReview. Accepted contributions will be displayed on OpenReview and Indico. Check the conference webpage for additional details on submitting an extended abstract.

Important Deadlines

  • Abstract Submission: June 1, 2026 June 15, 2026
  • (Optional) Extended Abstract Submission: June 15, 2026 July 1, 2026
The call for abstracts is open
You can submit an abstract for reviewing.
Submit new abstract