VB

Vikas Shridhar Bothe

Max Planck Institute for Nuclear Physics, Heidelberg University, Center for Excellence in Basic Sciences

Research areas: Physics and Astronomy · Nuclear and High Energy Physics · Neutrino Physics Research · Radioactive Decay and Measurement Techniques · Particle Detector Development and Performance

ORCID iD 0000-0002-1690-6929
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About

I am a particle physicist with a strong background in computational physics and machine learning. My research interests include developing machine learning algorithms for pulse shape discrimination techniques, analyzing large datasets, and feature extraction. I possess extensive coding skills in C++, Python, and Fortran, and am proficient with SQL and CERN-ROOT.

I hold a PhD in Physics and have several peer-reviewed publications. Currently, I am seeking opportunities in machine learning and data science to further my expertise. My academic journey began with a 5-year integrated Master’s in Physics from the University of Mumbai, where I developed a solid foundation in physics. My master’s thesis focused on experimental nuclear physics, particularly the analysis of high-energy nuclear reaction experiments using gamma-ray spectroscopy. This work provided experimental insights into the nuclear structure of heavy thallium isotopes and their isomeric states.

In 2018, I joined the Max-Planck-Institute for Nuclear Physics in Heidelberg as a doctoral candidate. As a member of the GERDA/LEGEND collaboration, which is dedicated to the search for neutrinoless double beta decay, I have been deeply involved in data analysis and model building to enhance the sensitivity of this rare decay experiment. My contributions include developing multivariate analysis techniques based on pulse shape analysis to suppress background and creating various machine learning models for efficient data classification. I am adept at building Monte Carlo simulations to model observed data and conduct sanity checks.

With a comprehensive understanding of the challenges associated with large datasets and machine learning model development, I excel in programming and data visualization, ensuring clear and effective presentation of scientific results.

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Publications (7)