Hi, I'm
Madhva Fakare
MSc Physics student building machine learning pipelines for electron-pion separation using the Transition Radiation Detector at CERN.
TRD Electron-Pion Separation
Developing an analysis pipeline for particle identification using the ALICE Transition Radiation Detector. Working with O2Physics, ROOT framework, and real Run 3 experimental data on CERN lxplus servers.
Who I Am
I'm a Master's student in Physics at the University of Münster, originally from India. My thesis sits at the intersection of experimental particle physics and machine learning — I'm building a pipeline to separate electrons from pions using the Transition Radiation Detector inside the ALICE experiment at CERN.
What draws me to this problem is the scale of it: heavy-ion collisions at the LHC recreate conditions from microseconds after the Big Bang, and the TRD is one of the key detectors helping us understand what comes out. Getting the particle identification right matters for the physics.
Day-to-day, I work with real Run 3 data on CERN's lxplus servers, writing analysis code in the O2Physics framework, building ROOT macros, and training Boosted Decision Trees to distinguish particle signatures from raw detector signals.
University of Münster, Germany
Run 3 data · Pb+Pb collisions
TRD · Boosted Decision Trees
Python · Git · lxplus / CVMFS