Update index.html

Author: Hariprashad-Ravikumar

index.html

@@ -125,14 +125,14 @@ <h1>Hariprashad Ravikumar</h1>
 
     <p class = "a">I am a theoretical particle physics PhD candidate at New Mexico State University, USA. I am currently engaged in research aimed at understanding the intrinsic motion of quarks and gluons inside the nucleons.</p>
 
-      <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 (<em>ML</em>) technique, to extract analytical functions from the lattice data.</p>
+      <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>
 
       <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 Los Alamos National Laboratory (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 parallel, I am collaborating with <a href="https://physics.sciences.ncsu.edu/people/crji/" target="_blank">Dr. Chueng-Ryong Ji</a> (North Carolina State University) 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. </p>
 
     <p class="a">
-As a driven and enthusiastic physicist with expertise in 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.
+As a driven and enthusiastic physicist with expertise in C++, Python, 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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