LPC Graduate Scholar


Raghav Kansal



What I will be working on:

I plan a search for a Z’ vector boson that couples to both beauty (b) and strange (s) quarks, and explains the recent exciting LHCb flavor anomalies and ∼90 GeV excesses observed in CMS Run 2 data. The prevalent production mechanisms for such a Z’ all produce an associated b-jet, providing an additional handle to the traditional CMS di-jet and boosted jet searches. In addition to this, I’ll continue my work in novel machine learning methods for fast CMS simulations for the HL-LHC, and jet tagging for Run 3 using self-supervised learning.

My role in CMS past and present:

I joined CMS as a CERN summer student in 2019 working on machine learning for detector simulations. I continued this during my PhD and recently as a 2021-22 LPC AI fellow, developing graph/attention-based generative models and validation techniques for CMS fast simulation. I also worked on ML for anomaly detection, reconstruction, and a boosted jet tagger in the WW final state, applying the latter to a boosted di-Higgs measurement and resonance search in all-hadronic final states.