Nitin Nagesh Kulkarni, Ph.D.

I am a Machine Learning Engineer II at Milwaukee Tool, specializing in the intersection of science and machine learning.My research interests lie at the convergence of:1. LLM Fine-Tuning and agents orchestration for domain specific generation,2. PINNs and Operator learning for solving complex engineering problems with sparse data constraints,3. Scientific Machine Learning applications in mechanical systems, particularly for multi-physics problems and damage detection.Prior to my current role, I was a PhD student at UMass Lowell, where I developed physics-informed variational autoencoders (PI-VAE) for full-field reconstruction and worked extensively on SHM using computer vision and ML techniques.