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Author: Hariprashad-Ravikumar

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     <p class="a">
-I’m a theoretical particle physics PhD candidate at New Mexico State University, USA, studying the intrinsic motion of quarks and gluons within nucleons and exploring Beyond Standard Model (BSM) physics through GPU-accelerated high-performance computing (HPC) and machine learning techniques.
+I am a PhD Candidate at New Mexico State University specializing in High-Performance Computing (HPC) and Deep Learning, with deep expertise in GPU-accelerated computing using C++/CUDA and Python. My work involves developing and optimizing software for large-scale data analysis and scientific simulation on supercomputing clusters.
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-      <p class = "a"> My PhD research under <a href="https://phys.nmsu.edu/facultydirectory/engelhardt_michael.html" target="_blank">Dr. Michael Engelhardt</a> (NMSU) focuses on lattice quantum chromodynamics (QCD), which is based on Markov chain Monte Carlo simulations of discretized space-time fields. In particular, I work on calculating Transverse Momentum Dependent Parton Distribution Functions (TMDs) such as generalized Sivers shift, which represents the average transverse momentum of unpolarized quarks orthogonal to the transverse spin of the proton. I analyze the dependence of Sivers TMDs on the longitudinal momentum fraction of the quark by placing the Wilson gauge link in various off-axis directions on the lattice simulations. The analysis also utilizes <em>PySR</em> symbolic regression, a machine learning (ML) technique, to extract analytical functions from the lattice data.</p>
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+My doctoral research focuses on applying advanced computational techniques to solve complex problems in particle physics. Key technical achievements include:
+<ul>
+<li><b>Performance Engineering & Acceleration:</b> I developed GPU-accelerated CUDA C++ pipelines that reduced data processing time by <strong>10x</strong> for multi-terabyte Fourier transforms on HPC clusters. As part of my collaboration with <strong>Los Alamos National Laboratory</strong>, I design and optimize parallelized C++ CUDA kernels that significantly accelerate multi-terabyte Monte Carlo simulations on clusters like the NERSC Perlmutter.</li>
+<li><b>End-to-End Machine Learning Pipelines:</b> I built a complete ML pipeline to process over 30,000 multi-dimensional observables from simulations. Using symbolic regression (PySR) with custom, physics-constrained loss functions, this pipeline achieved a model fit accuracy of over <strong>93%</strong>.</li>
+<li><b>Large-Scale System Orchestration:</b> I have designed and deployed custom SLURM workflows to manage and execute over <strong>75,000 CPU/GPU compute hours</strong>, enabling robust, automated parallel analysis for large-scale jobs.</li>
+<li><b>Robust Software Development & Validation:</b> I created production-grade Python and Mathematica packages to ensure numerical stability and reproducibility in multi-stage data analysis workflows. To increase model reliability, I apply rigorous validation methods, including AIC-based selection, chi-squared minimization, and bootstrap/jackknife resampling across tens of thousands of correlated data points.</li>
+</ul>
+</p>
 
-      <p class = "a">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> (T2) on a research project focused on lattice quantum chromodynamics (QCD) calculations of the hadronic matrix elements needed to connect nucleon Electric Dipole Moments (EDMs) to Standard Model (SM) and Beyond Standard Model (BSM) physics. This project is supported by a Travel Grant from the New Mexico Consortium at Los Alamos. </p>
 
-    <p class = "a">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 research project that involves interpolating the manifestly covariant conformal group \(SO(4,2)\) between the instant form and the light-front form of relativistic dynamics. One of the main goals of this work is to study the conformal invariance of high-energy scattering processes in the aforementioned interpolating form dynamics. For a recent presentation on this topic, visit Dr. Ji’s <a href="https://crjiresearchgroup.wordpress.ncsu.edu/group-meetings/hariprashad-ravikumar/" target="_blank">NC State research group page</a>.</p>
 
-    <p class="a">
-As a driven and enthusiastic physicist with expertise in C++, Python, CUDA, high-performance computing (HPC), symbolic regression, Monte Carlo simulations, and large-scale data analysis, I am fully committed to making significant contributions to scientific research and advancing our understanding of particle physics.
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+<p class="a">
+In addition to my core research, I actively pursue independent projects to broaden my technical skill set. I built a <a href="[Your Live App Link]" target="_blank">cloud-hosted ML forecasting platform</a> using AWS/Azure, Flask, and React, featuring automated data pipelines and a GPT API integration for generating natural-language summaries. I have also implemented neural networks from scratch in NumPy to solidify my understanding of fundamental ML principles.
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+<p class="a">
+With a strong foundation in C++, Python, CUDA, and parallel computing, complemented by hands-on experience in MLOps, cloud technologies, and rigorous data analysis, I am passionate about building efficient, scalable, and impactful software solutions for data-intensive challenges.
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