LHC Physics Center

What I will be working on:

My research focus on physics analysis with events containing three heavy bosons (VVV) searches and their interpretation in the content of an Effective Field Theory (EFT) using the full Run 2 dataset. In addition to physics analysis I am working on the integration of a new method to mitigate the pile up effects using Graph Neural Networks to CMS software. As an LPC distinguished researcher I plan to push the current efforts and consider new analysis interpretations for Run3. LPC has a known ML community and during my DR period I would like to consider more applications on GNNs and potentially join projects aiming for HL-LHC.

My role in CMS past and present:

Currently I am a post-doctoral researcher at Purdue university and a member of CMS collaboration from 2015. I have been pursuing a research program covering a wide range of research in high energy physics including the search for beyond the standard model physics (BSM) interpreted in Effective Filed Theory (EFT) framework and Machine learning applications in CMS. In addition, I am appointed with a L3 convenorship in Data Management (DM) group. My role as DM convener is to ensure a smooth operation by developing and optimizing tools and developing and testing future data management strategies. I obtained my PhD by completing two physics analysis using 2016 CMS data focusing on searches for supersymmetry in events with photons and missing transverse momentum and searches for a standard model Higgs boson in association with a top quark pair (t ̄tH) in the all-hadronic final state using boosted signatures. In addition to physics analysis I worked on commissioning and validation of the state-of-art b-tagging discriminators for the full Run 2 data.