Growth
The Journey
Not a resume. A map of how curiosity moved across domains — and what each chapter left behind.
BTech & First Contact with ML
Project: Stock Market Prediction using KNN
Four years of engineering fundamentals — algorithms, data structures, systems programming in C++. Discovered machine learning midway through and became obsessed. Started applying ML concepts to real datasets, grinding LeetCode, and building the first real project: a stock market prediction model using K-Nearest Neighbours.
Software Engineer @ TCS
Tata Consultancy Services
First real exposure to production systems and enterprise software. Working at scale changed how I think about code — reliability, observability, and maintainability stopped being theoretical. The gap between university projects and production systems was larger than expected, and learning to close that gap was the most valuable thing this year taught me.
Master's Degree — AI/ML Focus
MSc — Advanced AI/ML Projects
Went deeper on the theory side — advanced ML, deep learning architectures, NLP, computer vision. Built VisionDigits (MNIST CNN), CineMatch (recommendation systems), Falcon Landing Intelligence (predictive modelling on SpaceX data), and GraphMind (GNN exploration). This year was about depth: going from knowing ML techniques to understanding why they work.
Exploring Data Engineering
The infrastructure layer of AI
Realised that production AI lives downstream of good data infrastructure. Started exploring the data engineering layer — pipelines, orchestration, transformation, and warehousing. Understanding how data moves and transforms before it ever reaches a model changed the way I think about end-to-end ML systems.
Java Full-Stack Development
Currently active
The current chapter: building complete products from the ground up. Java on the backend, React and Next.js on the frontend. Learning to own the entire stack — not just write features, but architect, deploy, and maintain systems. InboxSignal was the first real full-stack build. There's more incoming.
What's Next
The next chapter is still being written. The pattern is clear — follow the most interesting problem available, stay long enough to understand it deeply, then carry that understanding forward. Chapter 06 is incoming.