题目：

Hybrid Pixel Detector development at PSI & Enhanced spatial resolution via deep learning for electron microscopy

摘要：
After emerging in High-Energy Physics, the Hybrid Pixel Detector (HPD) has found extensive usage in photon science and is gaining more popularity in electron microscopy due to its excellent counting capability, radiation harness, and good spatial resolution. To extend the detection capability, various technologies have been developed for HPD. In this presentation, the developments in HPD in the detector group of the PSI Photon Science Division will be briefly reviewed. In addition, an ongoing project with deep learning involved will be introduced. To fully realize the detection potential for electron microscopy of MÖNCH, a 25 μm HPD under development with 6 kHz readout speed, deep learning is used to reconstruct the electron impact points. Details of the project together with preliminary results will be reported.

报告人简介：
Xiangyu earned his Ph.D. in experimental particle physics in June 2022 from the University of Science and Technology of China. His research and development work focused on the thin-gap RPC for the ATLAS Phase-II upgrade at CERN. After completing his degree, he joined the Photon Science Division detector group at Paul Scherrer Institut as a postdoctoral researcher. Currently, he is working on enhancing the spatial resolution of MÖNCH for electron microscopy using deep learning techniques.