Patrick Van Workum
Artificial Intelligent for Light Detection
Single-photon counting is a high-precision detection method critical for applications ranging from medical imaging to ultraviolet, optical, and infrared imaging systems.
Traditional X-ray photon detection methods face limitations in high-density scenarios, because signals spreads into neighboring pixels, reducing image sharpness and making precise localization difficult.
Patrick Van Workum and his team have developed a neural-network-based computational approach that enhances photon localization, enabling super-resolution mapping and substantial reductions in detector readout frequency. His work demonstrates the potential for scalable deployment in next-generation detectors.
During the fellowship, Patrick aims to validate go-to-market strategies with established manufacturers to show commercial interest, prepare the software for custom integration into existing frameworks and benchmark performance against traditional methods.
Affiliation: Prof. Johan Chang
Start date: 1.09.25