Telephone: (630) 840-5686 E-mail: firstname.lastname@example.org Office Location: WH11E
I first joined the CMS collaboration in 2009 and I also contribute to DUNE; in the past, I worked on Daya Bay, ATLAS, and CLIC. In CMS, I have previously served as convener for the offline software for the HCAL Phase 1 upgrades, coordinator for the offline software for all CMS Phase 2 detector upgrades, and deputy release manager for the CMS software. I am currently the convener of the Machine Learning for Simulation (ML4Sim) group in CMS and co-convener of the Detector Simulation group for the HEP Software Foundation. The SONIC project, for which I am the lead developer, uses coprocessors, such as GPUs and FPGAs, as a service to accelerate neural network inference. I am also investigating the use of graph neural networks for calorimeter clustering and other applications.
At the start of Run 2 of the LHC, I focused on searching for strongly-produced supersymmetry in events with jets and missing energy. My physics interests now focus on dark matter; specifically, I am searching for evidence of strongly-coupled hidden sectors. These models can produce semi-visible or emerging jets that contain invisible and/or displaced particles, as well as soft unclustered energy patterns (SUEPs). Such signatures have generally been ignored by existing collider searches, providing the potential to discover the nature of dark matter at the LHC. I am exploring AI as a powerful tool to extract these signals from large, noisy backgrounds.