Hello World
I am a graduate student in the Department of Electrical and Computer Engineering at Carnegie Mellon University, pursuing a Masters in AI Engineering. I completed my undergraduate education from the Indian Institute of Technology Hyderabad (IITH) in Electrical Engineering, along with a second major in Computer Science and Engineering. I love exploring the theoretical aspects of Machine Learning (there was a time, long, long ago, where this wouldn’t sound as vague as it does now. Alas!) and attempting to bridge the gap between theory and practice, developing models and algorithms with mathematical guarantees. Diverging from the nerdy stuff, I thoroughly enjoy playing and watching football (soccer, for those who prefer it that way), basketball, and table tennis (or ping-pong; if I had a nickel for every time this happened, I’d have two nickels- which isn’t a lot, but it’s weird that it happened twice- Dr. Doofenshmirtz, probably).
Work Experience
I’m interning at Apical Intelligence (formerly Numenta) for Summer 2026, specializing in the pre-training of sparse Large Language Models.
Previously, I completed an internship at NVIDIA in the summer of 2024, where I worked on non-convex computational geometry problems and graph-partitioning heuristics for chip design.
Research Experience
I’ve been a part of the OPAL Lab at CMU since June 2025, working under the guidance of Dr. Gauri Joshi. My research includes 1) Diffusion Language Models, 2) Improving the performance of LLM judges, and 3) enhancing LLM Inference in terms of both speed and output quality using CRITICS and Infilling.
At IITH, I was a Research Assistant to Dr. Aditya Siripuram. Spanning about 30 months, I worked on non-convex robust PCA, Matrix Factorization, Orthogonal Dictionary Learning, Householder Matrices- their richness in the orthogonal group, utility in signal processing, as well as in normalizing flows, and matrix rigidity. Supported by the Qualcomm 6G University India Research Program, I spent 10 months working on Algebraic Error Correcting Codes. This work was conducted under the guidance of Dr. Lakshmi Prasad Natarajan and in direct collaboration with researchers at Qualcomm. Further details regarding this project can be found in the publications and projects sections.
Teaching
IITH: I was a Teaching Assistant for the courses: Matrix Theory, Semiconductor Device Fundamentals, Vector Calculus, Probability Theory, Convex Optimization, and Differential Equations & Transform Techniques during my time at IITH.
CMU: I am currently serving as a Teaching Assistant for the course: Introduction to Machine Learning for Engineers.
A big thanks to all the professors who allowed me to take up these roles, and especially, the hundreds of amazing students I’ve interacted with along the way!
To the reader
I made this page while killing time I didn’t have. I apologize in advance for any misdemeanours.
circa May 2026