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Author: Hariprashad-Ravikumar

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 I am also collaborating with <a href="https://cnls.lanl.gov/~rajan/" target="_blank">Dr. Rajan Gupta</a> and <a href="https://sites.santafe.edu/~tanmoy/cv.html" target="_blank">Dr. Tanmoy Bhattacharya</a> from <strong>Los Alamos National Laboratory</strong> on calculating the hadronic matrix elements needed to connect nucleon Electric Dipole Moments (EDMs) to BSM physics. In this role, I develop and optimize parallelized C++ CUDA kernels to accelerate multi-terabyte calculations, achieving significant runtime reductions on GPU-accelerated HPC clusters like the NERSC Perlmutter. I increased model reliability through rigorous statistical validation on over 50,000 correlated data points, applying methods like AIC-based selection and chi-squared minimization with full covariance matrices. I design and deploy custom SLURM workflows to manage and execute over <strong>75,000 CPU/GPU compute hours</strong>, enabling robust, automated parallel analysis for these large-scale simulations.
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 In addition, I am collaborating with <a href="https://physics.sciences.ncsu.edu/people/crji/" target="_blank">Dr. Chueng-Ryong Ji</a> (<strong>North Carolina State University</strong>) on a project interpolating the manifestly covariant conformal group (SO(4,2)) between different forms of relativistic dynamics. For this work, I implement and manage Mathematica symbolic computation workflows on HPC clusters (NERSC Perlmutter) to analyze complex algebraic structures and symmetry constraints inherent in the problem.
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 My background provides me with a unique blend of deep physics intuition and hands-on expertise in C++/CUDA, parallel computing, and machine learning. I am driven to apply these skills to solve complex, data-intensive challenges and contribute to cutting-edge scientific and technical advancements.
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