Applied machine learning to particle physics big data analysis, gaining deep expertise in graph transformer models and neural networks.
Publications & Presentations: Published 5+ papers on AI applications in high-energy physics; invited to speak at international conferences on AI in scientific research.
Applied machine learning to particle physics data, gaining deep expertise in predictive models and neural networks.
• Author of AI-driven project “TauJetGraphs”: Developed a state-of-the-art platform for Tau decay identification using Graph Neural Networks, reducing computational time by 30% and improving accuracy in particle classification and Background rejection by 2 and up to 10 times com...
England, United KingdomAs part of my Doctorate studies, a data science internship was a requirement. I followed through one in collaboration with the engineering department at Lancaster University and NNL (National Nuclear Laboratory). The focus of my training was on applying advanced machine learning algorithms in the field of robotics. I have gained skills in using Computer Vision techniques in overly complicated...