Thank you for visiting my webpage. I am a 2nd-year PhD student in the Deep Underground Neutrino Experiment (DUNE) group at University of Warwick. My area of interest is in the improvement and optimisation of automated pattern recognition software using machine/deep learning to reconstruct neutrino interactions. I work in the Elementary Particle Physics (EPP) group under the guidance and supervision of Prof. John Marshall.
Currently, I am working to improve pattern recognition at Deep Underground Neutrino Experiment (DUNE), which is a multi-national, multi-billion dollar experiment situated in the United States of America. DUNE utilises Liquid Argon Time Projection Chambers (LArTPC), rather than scintillator or water detector, to study the charged particles produced from neutrino interactions in ever greater detail, with one of the main advantages being its ability to produce high granularity images of the events. To study and reconstruct these images, DUNE employs the use of Pandora, a pattern recognition software that uses multi-algorithm approach.
One of the challenges in terms of pattern recognition is the discrimination of "track-like" and "shower-like" structures that arise from a neutrino interaction. One of the main goals of this PhD project is to help improve already existing algorithms that uses cut-based approach to differentiate between a track-like and shower-like structures and then move on to machine/deep learning approach to make further improvements. I will then look at real proto-Dune data and focus to improve kaon seperation and finally conclude the project by calculating proton decay sensitivity at the far detector.
If you are interested in learning more about DUNE, then please click here.
Year 1 Physics Tutorial Classes (Classical Mech, E&M, Thermal Phys, etc.)
Year 1 Physics Examples for Maths Students
- University of Surrey (2017-2018) - MSc Physics
- University of Leeds (2013-2016) - BSc Theoretical Physics
Department of Physics
University of Warwick
West Midlands, UK