Thomas is an applied physicist in the CMS group of CERN, where he is applying machine learning (ML) solutions to ultra low-latency (microsecond) data-processing using FPGAs. Thomas has worked on the CMS experiment since 2013, specialising in data acquisition, fast particle selection, and event reconstruction in FPGAs. He joins the CTO team of CERN openlab to advise on ML/AI and real-time data processing.
In 2018, Thomas graduated with his PhD in particle physics from Imperial College London, UK, where he developed a novel FPGA-based online particle track finder, earning him the CMS Thesis Award for that year. Prior to that, he obtained his Masters and Bachelors degree in physics with theoretical physics from the same institute.