I am a Ph.D. student in Computational Science and Engineering at MIT, co-advised by Prof. Alan Edelman and Dr. Chris Rackauckas at the Julia Lab, MIT CSAIL. My research lies at the intersection of artificial intelligence, probabilistic modeling, and scientific computing. I build scalable, performance-engineered, and physics-consistent AI systems for scientific discovery, spanning LLM post-training, generative modeling, and high-performance computing.

Through my research internships, I have worked closely with Danielle Robinson, Bernie Wang, and Michael W. Mahoney at AWS AI Labs on probabilistic learning with hard constraints. At NVIDIA, I collaborated with Akshay Subramaniam and Noah Brenowitz on kilometer-scale climate emulation and, more recently, worked with DevTech on high-performance RL post-training infrastructure for mixture-of-experts language models.

Before MIT, I completed a double major in Electrical Engineering and Chemical Engineering, with a minor in Computer Science and Engineering, at IIT Kanpur, India.