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.