Second-year Computer Science & Engineering Student at Manipal Institute of Technology (MIT), Bengaluru | Specialising in Data Science, Backend Development & Data Engineering
Backend • Data Pipelines • Cloud • AI/ML for Real-World Applications
Passionate about building scalable systems, turning raw data into insights, and making complex concepts fun.
I'm a second-year CSE student at Manipal Institute of Technology (MIT) with hands-on experience in backend development, data engineering, and cloud technologies. I specialise in designing robust APIs, building efficient data pipelines, and creating database-driven applications that scale. Proficient in Java, Python, SQL, and modern frameworks, I thrive in collaborative environments delivering high-impact solutions.
- Currently focused on: Backend systems (Spring Boot, Flask), Data Engineering, Cloud (AWS), and AI/ML applications.
- Currently learning: Spring Boot + Spring Security, advanced data pipelines, and production-grade AI integrations.
- Fun Fact, I'm a huge Formula 1, and motorsport fan! It's pretty fun to mess around with race telemetry data, and build stuff with it.
Finance Tracker Backend – Production-Style Backend System
Scalable REST API for managing personal finance data including users, accounts, transactions, budgets, and multi-currency support, designed with real-world backend architecture principles.
Key Features:
- Full CRUD APIs across multiple financial entities
- Relational PostgreSQL schema with constraints, indexing, and optimized design
- CSV-based bulk transaction import with duplicate detection and batch tracking
- External currency conversion integration (supports 150+ currencies)
- Robust validation, structured error handling, and data consistency mechanisms
Tech Stack:
Java 21 • Spring Boot • PostgreSQL • Maven • ExchangeRate-API
El Plan STEM – Hackathon Project (AI × Motorsport Education)
AI-powered web application that teaches STEM concepts using Formula 1 data, combining data engineering, frontend development, and LLM-based features under hackathon constraints.
Key Features:
- Designed and deployed MongoDB Atlas database with optimized schema for real-time queries
- Built core frontend with responsive UI using HTML, CSS, and JavaScript
- Developed data ingestion and processing pipelines for large-scale F1 datasets
- Contributed to RAG-based LLM integration for context-aware query responses
- Enabled interactive, data-driven learning experiences using motorsport analytics
Tech Stack:
MongoDB • MongoDB Atlas • HTML/CSS/JS • Python • LLM APIs
- B.Tech in Computer Science & Engineering (Specialisation in Data Science)
Manipal Institute of Technology (MIT), Bengaluru
2024 – 2028
Let's connect and build something awesome together!
Whether it's backend systems, data pipelines, AI-powered tools, or just talking about the latest F1 regulations and technology, I'm always up for a chat.