Undergraduate Student & Budding Researcher.

Thapar Institute of Engineering & Technology, India.

My interests span three areas I find persistently compelling, and increasingly, the territory where they meet:

Systems Design  |  How architectural decisions propagate through large-scale infrastructure. I am particularly interested in fault models, emergent failure modes, and the principled tradeoffs that separate systems that degrade gracefully from those that do not.

MLOps  |  The theory-to-production gap in machine learning remains poorly understood and routinely underestimated. I am drawn to the operational and engineering problems that arise when statistical models are embedded in live systems — reliability, reproducibility, drift, and the organisational conditions that determine whether any of this is possible at all.

Computer Vision  |  Representation learning for visual data, with a growing interest in how robustness and generalisability are achieved (or claimed to be achieved) in practice, and what the gap between benchmark performance and real-world deployment reveals about the state of the field.

A machine learning pipeline for the classification of neurological conditions from raw EEG recordings. The project addresses the full signal-to-decision chain: preprocessing and artifact removal, feature extraction from time-frequency representations, and evaluation of classification architectures against clinically meaningful baselines. The central question is whether discriminative structure in neural oscillations can be reliably surfaced by learned models, and under what conditions such a system could be trusted.

Python   Signal Processing   Deep Learning   Biomedical AI

AEGIS-NET is an AI-powered system that analyzes aerial imagery from UAVs to identify safe landing zones in real-time. This project uses the WildUAV dataset, a large-scale benchmark for monocular depth estimation in unstructured outdoor environments captured from UAV perspectives.

Drone Tech   Defense Systems   Applied ML

Wydey is a progressive web application designed to map mathematical functions to geometric visualizations and audio samples. By translating abstract equations into visual formats and pairing them with instrument sounds (like Piano, Violin, Synth, and Flute), Wydey makes exploring mathematics a multisensory experience.

Applied Mathematics   Vite   Java Script & CSS

• Deepening my understanding of MLOps tooling — experiment tracking, model registries, deployment patterns
• Reading across the systems and distributed computing literature
• Open to research collaboration, particularly on projects involving signal processing, computer vision, or ML system design

If you are working on something at the intersection of these areas and are looking for a collaborator, I am glad to hear about it.