I am a Ph.D. candidate at RWTH Aachen in the field of High Energy Physics, where my focus is data analysis from the CMS experiment.

Currently, my primary projects involve:

Correction of Simulation Mismodeling: The CMS detector is a complex machine, and simulations of physical processes cannot account for everything that occurs within the detector. I am dedicated to correcting simulation inaccuracies to enhance the alignment with the observed data. To achieve this, we are employing conditional auto-regressive neural spline flows.

Early Run3 Higgs to gamma gamma Effort: I actively contribute to the development of the analysis framework HiggsDNA, a novel framework that fully utilizes columnar analysis for the Early Run3 Higgs to gamma gamma effort. (https://gitlab.cern.ch/HiggsDNA-project/HiggsDNA)

I have also recently joined the AutoDQM (Automatic Data Quality Management) team. AutoDQM functions as a tool designed for analyzing the performance of detectors within the CMS experiment. It employs anomaly detection algorithms, such as the beta-binomial statistical test, principal component analysis, and autoencoders, to identify anomalies in the detectors. The detected anomalies are flagged, enabling prompt resolution of issues and appropriate identification of data collected during detector malfunctions.

I am also a tutor in the RWTH Deep learning course, and one of the organizers in the computing boot camp for junior reseraches in the institution.