Dr. Ram Chand’s Research Group

High-Energy Physics & Machine Learning (CERN Collaboration)

In collaboration with CERN, this research group applies state-of-the-art deep learning architectures to fundamental problems in particle physics, with a primary focus on jet classification in proton-proton collision events recorded at the Large Hadron Collider. Jets—collimated sprays of hadrons originating from quarks and gluons—carry essential information about the underlying hard scattering processes, and their accurate classification is critical for precision measurements and searches for new physics beyond the Standard Model.

We leverage CERN’s open data initiative to train and benchmark convolutional neural networks, graph neural networks, and transformer-based models on jet tagging tasks, including discrimination between quark-initiated and gluon-initiated jets, identification of boosted heavy particles, and anomaly detection for potential new physics signatures. Our work contributes to the growing intersection of artificial intelligence and fundamental physics, developing interpretable and robust ML pipelines suitable for deployment in high-throughput experimental environments. This collaboration provides our students with exposure to international research standards and cutting-edge computational methodologies in particle physics.

Principal Investigator:

• Dr. Ram Chand, Chairperson, The Begum Nusrat Bhutto Women University, Sukkur

Research Team:
• Miss Bibi Naifa, Miss Mah Laca, Miss Kanwal