PhD Student in Machine Learning | IIIT Delhi
I am a PhD Research Scholar at IIIT Delhi focusing on the theoretical foundations of Machine Learning.
I completed my 5-Year Integrated M.Sc. in Mathematical Sciences from Maharshi Dayanand University with an 80.4% score.
UGC-CSIR NET JRF Qualified with All India Rank 64.
Theoretical Foundations of Continual Learning via Drift-Plus-Penalty
Authors: Govinda Arya, Nazreen Shah, Ranjitha Prasad, Bharath B. N.
Status: Submitted to TMLR (Under Review)
Continual Learning via Constrained Stochastic Optimization
Authors: Govinda Arya et al.
Venue: CODS-2025 (Young Researchers Symposium)
3-D Image Generation (2024–Present)
Developed a 3D image generation framework using coordinate-based neural
representations (x, y, z, t) in PyTorch.
Constrained Optimization for Continual Learning (2024)
Proposed a drift-plus-penalty objective for stability-plasticity tradeoff.
Python, MATLAB, PyTorch, TensorFlow, LaTeX
Mathematics:Linear Algebra, Real Analysis, Probability, Statistics, Calculus