The Fast Machine Learning for Science Conference 2025 will take place from September 1–5, 2025, at ETH Zurich, bringing together researchers and industry experts to explore the latest advancements in machine learning (ML) for scientific discovery.
As experimental techniques advance, generating increasingly complex and high-resolution datasets, machine learning (ML) has quickly become a fundamental tool for analyzing vast amounts of data across various scientific fields.
With the rapid development of deep learning algorithms, significant efforts are being made to enhance processing technologies and accelerate deep learning and inference. These advancements are transforming experimental design and data analysis, driving scientific discovery at an unprecedented pace. This workshop will focus on both established and emerging methods in deep learning and inference acceleration, covering topics such as efficient ML algorithm design, ultra-fast on-detector inference, real-time processing, acceleration-as-a-service, specialized hardware platforms, coprocessor technologies, distributed learning, and hyperparameter optimization.
Important Deadlines
– Abstract Submission: July 1, 2025
– Registration Deadline: August 1, 2025
For more details and updates on abstract submission, keynote speakers, and registration, please visit the conference website: https://indi.to/fastml25 .
You can submit your abstracts for scientific talks, posters, 2-4 hour Monday tutorials, and 2-3 hour Wednesday topical (birds-of-a-feather) sessions.