Passionate about building intelligent systems that solve real-world problems. Exploring the intersection of data science, machine learning, and software engineering.
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I am an Artificial Intelligence & Data Science Engineering student who is deeply passionate about learning how to build data-driven solutions and robust backend architectures. I spend a lot of my time diving into Python backend development, figuring out how to build scalable REST APIs with FastAPI, wrap my head around asynchronous programming, and connect databases using PostgreSQL and SQLAlchemy. I'm also actively learning how to implement secure JWT/OAuth2 authentication, manage background tasks with Redis, and deploy everything smoothly using Docker.
Beyond backend basics, I am incredibly fascinated by cutting-edge AI. I've been experimenting a lot with deploying local LLMs, setting up Retrieval-Augmented Generation (RAG) pipelines, and using AI tools to help me code faster and learn better. I really enjoy taking complex, high-level concepts from my classes and turning them into real, working applications that I can actually interact with.
REVA University, Bengaluru, Karnataka, India
2025-2029
End-to-End Educational Data Mining
Built a full data science pipeline to analyze thousands of student performance records. I focused on extracting meaningful features to uncover hidden academic trends, and I trained predictive models to try and identify at-risk students early on. This project was a great hands-on way for me to bridge raw statistical theory from my coursework with real-world educational insights.
Python, Pandas, NumPy, Matplotlib, SQL
Multi-Model AI Inference & Coding Agent
Set up a local, multi-model AI inference server by running Ollama inside Docker containers on Linux, which allowed me to expose secure API endpoints across my home network. I had a lot of fun figuring out how to route requests between Mixture of Experts (MoE) and dense models, and I spent time tweaking hardware optimizations to push inference speeds up to 30 tokens/sec for 36B models and 180+ tokens/sec for 7B models. I also integrated an autonomous local coding agent using these models and OpenClaw to help me code and learn faster!
Ollama, Docker, Linux, MoE & Dense Models, OpenClaw, API Networking
Decentralized Task Resolution Platform
Built and deployed a full-stack web application that integrates blockchain concepts for decentralized micro-tasking. I developed the backend using Python and FastAPI, connected it to Supabase to handle real-time data syncing, and learned how to deploy the frontend smoothly via Vercel. It was an awesome experience learning how to bridge smart contracts with dynamic UI rendering.
FastAPI, Python, JavaScript, Blockchain, Supabase, Render, Vercel
Real-Time Machine Learning Inference Engine
Created a REST API designed to serve pre-trained machine learning models for real-time predictions. I tackled the challenge of handling data preprocessing and feature engineering on the fly, which really helped me understand how to take static ML models out of Jupyter notebooks and integrate them into live, working software environments.
FastAPI, Python, Scikit-Learn, Pandas, REST APIs
Low-Level CLI Engine & Rendering Pipeline
Coded a completely custom, command-line based 2D graphics engine from scratch. Instead of relying on pre-built GUI libraries, I challenged myself to implement mathematical rendering algorithms directly in the terminal. It was a really fun way to learn core logic by mapping out geometric shapes into ASCII arrays that update in real time.
C, Terminal Graphics, Core Logic Algorithms, CLI Tooling