Scientific Machine Learning for Fundamental Physics - ML4Jets2026
Over the past years, High Energy Physics (HEP) has made significant strides by developing and applying machine learning (ML) and artificial intelligence (AI) approaches. These advancements have greatly improved particle and event identification, reconstruction, simulation, experiments operations, and more.
The workshop will highlight the latest progress and ongoing challenges in these areas. It isopen to the entire community, including participants from LHC experiments (detector and accelerator), theorists, and phenomenologists. We welcome contributions from method scientists and experts in related fields such as astronomy, astrophysics, cosmology, astroparticle physics, hadron and nuclear physics, and other domains facing similar challenges as well as computer scientists in research, industry and academia.
Join us to explore new ideas and advance the future of particle physics and science through ML/AI.
The following topics accross the various fields are foreseen:
- Classification and reconstruction
- Experiment simulation
- Event generation
- Inverse problems
- Uncertainties
- Anomaly detection
- Interpretability
- FastAI / EdgeAI systems for trigger applications
- Detector/accelerator monitoring, control, and data acquisition
More information: https://indico.global/event/15240/
Information
Date:
14 - 18 September 2026
Venue:
Campus of the University of Vienna
Hörsaalzentrum
Lecture halls C1 + C2