Gopi Krishna

Developing a GPU-accelerated 3D PIC simulation framework in CUDA for high-current electron beam injectors, implementing self-consistent Poisson solvers and electromagnetic particle trackers to analyze beam emittance and transport while achieving major speed-ups over CPU solvers.

Led a parameterized dark energy modeling project using Pantheon+, OHD, BAO and CMB datasets and Bayesian MCMC methods (CLASS, Cobaya, MontePython), producing a model that outperformed ΛCDM across redshifts and resulting in a peer-reviewed publication.

Analyzed ASIC performance for the DUNE detector using CERN ROOT, Python, and C++, assessing noise at room temperature and 77K and identifying failure modes related to connections and manufacturing defects.

Activities and societies: Research on GPU-accelerated particle-in-cell simulations; presentation at ISBA25.

Ph.D. student in the Department of Physics conducting GPU-accelerated 3D PIC simulations for high-current electron beam injectors; research focuses on space-charge effects, solver development, and beam transport analysis.

Grade: 9.1/10

Activities and societies: PG project on dark energy modeling; used CLASS, Cobaya, Montepython; cosmological data analysis.

Completed a Master of Science with a research-focused project on dark energy modeling using cosmological datasets and Bayesian MCMC analysis.

Grade: 7.8/10

Activities and societies: Undergraduate coursework and projects including analysis for DUNE detector ASICs.

Completed a Bachelor of Science in Physics with coursework and projects in cosmology, particle physics, and experimental methods.

Grade: 94.8%

Completed CBSE Class XII with focus on science subjects and strong academic performance.

Grade: 10/10

Completed CBSE Class X with full marks.