Hi!
I am Rajesh Kumar
a Nuclear Astrophysicist (Theoretical and Computational)
Currently working as an Assistant Professor at M.R.P.D. Government College, Talwara, Punjab, India
New research paper on the effect of hexaquarks on neutron star equation of state
Currently working as an Assistant Professor at M.R.P.D. Government College, Talwara, Punjab, India
I am a dedicated researcher and educator with over eight years of experience in theoretical and computational nuclear astrophysics. Currently, I serve as an Assistant Professor at MRPD Government Arts and Science College, Talwara, Punjab, India. Prior to this, I was a postdoctoral research associate at Kent State University, Ohio, USA, where I explored the physics of compact stars and the behavior of hadrons in hot and dense environments. I earned my Ph.D. from Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, with a focus on the properties of hadrons under extreme conditions, including strong magnetic fields. My academic profile is supported by a robust record of peer-reviewed publications, active participation in international conferences, and involvement in global research collaborations. I am an active contributor to the MUSES collaboration development team, where I work on the CMF module, QLIMR, CMF+QLIMR, and CMF+lepton module projects hosted on GitHub. In collaboration with NP3M, I am also engaged in incorporating meson contributions to the equation of state for high-temperature and compact star matter. In addition to research, I have extensive teaching experience at both undergraduate and postgraduate levels. I have taught courses in astrophysics, quantum field theory, classical mechanics, and introductory physics, with a strong emphasis on conceptual clarity and student engagement. My teaching approach integrates computational tools and research-based learning strategies to create an inclusive, stimulating, and student-centered classroom environment.
Research Interests: Hot and Dense Nuclear Matter, Compact Stars, QCD Phase Transitions, Machine Learning, Statistical Analysis