I am a particle physicist and I search for experimental evidences towards deeper understanding of space and time. Our group is studying the highest energy proton-proton collision data collected by the Compact Muon Solenoid experiment(CMS) at the CERN Large Hadron Collider. We hunt for hints of new physics phenomena, beyond the Standard Model of fundamental particles, with ultra-rare processes such as those containing multiple heavy gauge bosons or violating the lepton universality.
To harness the big data at unprecedented rate and volume at the LHC and its future upgrade, our group is developing real-time artificial intelligence in embedded systems or with heteregenous compute with collaborators in the fast machine leanring lab and the NSF A3D3 institute. The Purdue CMS group is also building the semiconductor tracker for the next CMS upgrade, that will collect data at an unprecedented rate in a harsh radiation enviroment. Previously, I worked on searches for supersymmetry particles and the CMS pixel detector, see my CV and google scholar profile for more.
I am a manager of the US.CMS software and computing operations program and a co-convener of the CMS machine learning production group. I am also leading the efforts of enabling machine learning based methods in CMS offline data processing and the utilization of heteregeneous computing platforms.
We are actively recruiting: a silicon lab engineer (apply here), a postdoctoral researcher for CMS data analysis and instrumentation development (apply here), graduate students (apply here), and undergraduate students (email me).
Our work is supported by the Department of Energy (DOE), Office of Science, Office of High Energy Physics Research Program under award number DE-SC0007884, and the National Science Foundation (NSF) under award numbers 2117997 (A3D3)