Maryam Bayat Makou

DESY
Notkestraße 85 (Building 1b)
22607 Hamburg
Room: O1.243

 

 

Supervisors: Prof. Elisabetta Gallo (DESY/UHH), Dr. Roberval Walsh (DESY), Dr. Rainer Mankel (DESY), Prof. Peer Stelldinger (HAW)

After Maryam obtained her Bachelor’s degree in Physics at the Alzahra University of Tehran, she decided to continue her studies in Physics at the Universität Hamburg. She obtained her Master’s degree in 2021 and with a focus on particle and astroparticle physics. During her Master studies and especially during her Master thesis project within the DESY-CMS group she developed a strong interest in Data Science and Machine Learning. Her master thesis project was focused on the optimization of Machine Learning techniques that are used in the Higgs boson analysis and its decay into two tau leptons with the CMS 2018 data that are collected during the last year of Run 2 at the Large Hadron Collider (LHC).
For her PhD thesis, she will continue working on Higgs analysis within DESY_CMS group and she will search for the Standard Model Higgs boson in the bbH production with the state of the art Deep Learning.
The production of b quarks (bb pair) with a Higgs boson is considered as the key process for directly probing the Yukawa Interaction between the Higgs boson and bottom quarks. Although this process in Standard Model suffers from very large backgrounds from other Higgs production channels. Hence the aim of her PhD thesis would be to solve the aforementioned problem with the use of Deep Neural Networks with the CMS full Run2 data.