As a Fermilab 2018 LHC Physics Center Distinguished Researcher, I am spending time at Fermi National Laboratory in Batavia, Illinois, working on development of latest machine learning techniques for the rare Higgs boson decays into di-muons and the Higgs boson decays into bottom quarks.

This work builds upon our latest results in rare Higgs decays into di-muons and End-To-End Deep Learning for Event Classification in combining the latest machine learning algorithms directly with low-level detector data.

Additionally, I am working on the High Luminosity Large Hadron Collier (HL-LHC) Phase II upgrade to the CMS trigger with advanced machine learning applications for real-time event selection.

I have been chosen to be one of Fermilab 2019 LHC Physics Center Distinguished Researchers, to further expand the machine learning applications at the LPC, including end-to-end learning, Higgs to fermions and detector upgrades. I am looking forward to another successful stay at the LPC.



I will also be helping organize the local machine learning efforts both in CMS and other cosmic and intensity frontier experiments and collaborating with Fermilab’s Computing Division on machine learning research and development projects.

During 2018 I will serve on the LHC Physics Center (LPC)’s Events Committee and help organize and teach a new CMS machine learning training course.



In November 2018, I co-chaired the Machine  Learning for Jet Physics (ML4Jets2018) International Workshop at Fermilab, attracting 130 participants from around the world, including theorists, phenomenologists, experimentalists and data scientists, who gathered to discuss the latest progress in this area. There is a Fermilab News article about ML4Jets2018:



On November 16, 2018, I gave a Fermilab Wine and Cheese seminar on the topic of “Deep Learning for the Future of Particle Physics”. In January 2019, I am organizing the Machine Learning Exercises at the CMS Machine Learning Data Analysis School at the LPC.