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Symbolic Models Discovery from Time-Series Data Workshop

Key Details:

Time: Exact timing tbc 
Date: 22 & 23 September 2025
Location: In-person | I-X Level 6 
Translation and Innovation Hub
Imperial White City Campus
84 Wood Lane
W12 0BZ

09:00 - 17:00
22/09/2025
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Speakers

Miles Cranmer

Miles Cranmer is Assistant Professor in Data Intensive Science at the University of Cambridge, joint between the Department of Applied Mathematics and Theoretical Physics and the Institute of Astronomy. He received his PhD from Princeton University, spending time at Google DeepMind and Flatiron Institute, and before that, his BSc from McGill University. Miles is interested in automating scientific research in the physical sciences with machine learning, and works on a variety of pure and applied machine learning projects in pursuit of this goal. His ML research has concentrated on symbolic regression, graph neural networks, and physics-motivated architectures, while his applied projects have looked at multi-scale physics, planetary dynamics, and cosmology.

Urban Fasel

Urban Fasel is a lecturer in the Department of Aeronautics at Imperial College London. His research interests range from co-design optimization and machine learning for modeling and control of complex systems to adaptive structures and autonomous flight systems. Before joining Imperial, Urban was a Postdoc in Mechanical Engineering with the University of Washington, mentored by Steve Brunton, and closely collaborating with Bing Brunton and Nathan Kutz. Urban received his Doctor of Science in Mechanical Engineering at ETH Zurich, developing co-design optimization and data-driven control methods for morphing wings applied to Airborne Wind Energy.

Talk Summary

Join us for an exciting two-day workshop focused on symbolic model discovery, a potentially transformative AI tool for scientific discovery. Whether you’re from physics, engineering, biology, or beyond, this workshop is designed to introduce you to powerful, interpretable, and efficient modelling methods and meet the leading developer in person!

The workshop targets academics (especially ECRs/PhD/Post-Docs) who are interested in symbolic regression.

The registration closes on 15 August 2025. 

For more information, please contact info@symbolicmodel.org

 

Highlights

  • Interactive Lectures: Learn foundational theories of cutting-edge packages from leading experts and developers in symbolic model discovery.
    • PySR (Symbolic Regression) – Miles Cramer (Cambridge)
    • PySINDy/Ensemble-SINDy – Urban Fasel (Imperial)
  • Practical Tutorials and Exercises: Step-by-step guidance using symbolic regression packages guided by experts!
  • Benchmark Hackathon: Tackle real-world datasets in predator-prey dynamics, epidemiology, fluid dynamics, or control system identification. Alternatively, you can bring your own data to work together!
  • Publication: For those interested in a joint publication, we aim to write up our hackathon results as part of a benchmarking paper!

Who is the event for? 

The event is for researchers who want to:

  • Apply explainable AI techniques in their research.
  • Explain some time-series data with an interpretable ML model.
  • Know more about explainable AI for Sciences and interpretable Scientific ML.
  • Know which symbolic model discovery tool is more suitable for their work.
  • Use AI techniques that are explainable, robust, generalisable and mathematical.
  • Network with leading developers in symbolic and interpretable AI.
  • Gain immediate practical skills and valuable insights into symbolic/sparse regression.
  • Become part of a vibrant community focused on advancing scientific understanding through AI.

Prerequisite

  • Familiar with Python and Python Notebook environment
  • (optional) Familiar with MATLAB or JULIA
  • No prior knowledge on symbolic regression is required!

Not able to join physically?

All workshop materials, including lecture videos and Python notebooks, will be openly available via YouTube and GitHub.

Find out more

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