Davide Di Croce
BiographyMy research interests focus on the application of Machine Learning (ML) in the fields of Accelerator and Particle Physics. I am currently engaged in implementing Deep Learning algorithms for the FCC design/project.
Prior to this role, I served as a software and computing R&D postdoctoral researcher at US-CMS, affiliated with The University of Alabama, during 2020-2021. I have also been an active member of the CMS collaboration from 2013 until 2021. During my time with CMS, I have undertaken various tasks and contributed to several research areas, including:
- CMS shift leader
- End-to-End Deep Learning for particle and event reconstruction.
- Search of Higgs boson decaying to light pseudoscalars.
- Beam test (operation and data analysis) of 2S module for CMS Phase-2 Tracker Upgrade
- DAQ for CMS 2S front-end hybrid prototype: software integration of CIC data concentrator and commissioning
- MC simulation: FastSim code maintenance and tuning.
- Trigger contact: maintenance and monitoring of the CMS triggers for HWW analyses.
- Tracking performance: software development and study of the performance of each layer of the CMS tracker.
- Higgs to WW measurements in same-flavor leptons channel.
- Study of anomalous coupling 𝛾𝛾𝑍𝑍 with the CMS PPS detector.