Unlocking the potential of synchrotron radiation and neutron science through autonomous control systems, intelligent decision-making, and FPGA-based hardware acceleration.

Self-adjusting parameters based on rapid, automated data analysis. Overcoming the limits of traditional manual control systems for complex phase diagram exploration.
Real-time data pipelines for automatic background subtraction, noise reduction, and beam damage detection linked directly to end-station control systems.
Implementing Bayesian optimization and reinforcement learning to navigate multi-dimensional experimental landscapes and maximize data quality.
Meeting real-time feedback demands where conventional CPU or ML algorithms are too slow. AI accelerators integrated directly into hardware.
Running computationally intensive analyses directly on chip to enable low-latency inference for XPCS and other high-volume use cases.
Integration into established beamline environments like BLISS and Sardana to ensure modularity and transferability across research facilities.
X-ray Photon Correlation Spectroscopy focus.
X-ray and Neutron reflectivity exploration.
Time-resolved Reciprocal Space Mapping (TR-RSM).
Designing solutions for global synchrotron applications.
Our project aligns with the key funding policy goals for large-scale research infrastructures.
Our consortium brings together world-class experts from synchrotron and neutron science, accelerator technology, electrical engineering, and industry leaders to pioneer a new era of autonomous experimentation.