Who I Am

About Me

A builder at heart — engineering systems that are intelligent, scalable, and production-ready.

I am a B.Tech student in Artificial Intelligence and Machine Learning, building expertise at the intersection of intelligent systems, scalable backend architectures, and data engineering. My work spans ML pipelines, full-stack applications, and production-quality Python engineering.

I don't just learn concepts — I build with them. Every project in my portfolio demonstrates a deliberate engineering decision: choosing the right algorithm for an imbalanced dataset, architecting a modular analytics platform, or implementing SOLID design patterns to write code that can grow. I approach every problem with a product thinking mindset — asking not just "does it work?" but "does it scale and deliver real value?"

My core focus areas are Machine Learning & AI engineering (classification, regression, fraud detection, time-series forecasting), backend development (REST APIs, authentication, data pipelines), and software craftsmanship (OOP, SOLID principles, clean architecture, design patterns). I am actively expanding into Generative AI, LLMs, and cloud-native development.

I am currently seeking internship opportunities where I can contribute to production systems, collaborate with strong engineering teams, and continue growing as a software engineer.

6+ Projects Built
15+ GitHub Repos
8+ ML Models
3+ Languages

Engineering Journey

2025 — Present
AI & Machine Learning Engineering
Built end-to-end ML pipelines — fraud detection, medical diagnosis, revenue forecasting, student performance prediction. Hands-on with Scikit-learn, NumPy, Pandas, Matplotlib.
2025
Full-Stack & Backend Engineering
Developed the AgriCrop AI platform — a full-stack Python web application integrating AI for smart agricultural intelligence. Learned REST API design, authentication, and data-secure architectures.
2025
Software Engineering Foundations
Implemented enterprise-grade Python systems: OOP, SOLID principles, Singleton / Repository / Strategy design patterns, type hints, custom exceptions, and comprehensive logging. Built a production-quality Expense Tracker and Java concurrent task scheduler.
2025
Data Engineering & Analytics
Delivered the Smart Logistics Supply Chain Analytics project using Python, SQL, and Power BI. Built a modular Revenue Intelligence Platform with ARIMA time-series forecasting and RFM customer segmentation.
2024 — 2028
B.Tech in Artificial Intelligence & Machine Learning
Aditya University. Coursework covers core Computer Science and AI: Algorithms, Data Structures, Operating Systems, DBMS, Computer Networks, Linear Algebra, Probability & Statistics, and ML paradigms.

How I Work

Problem-First Thinking

I start every project by deeply understanding the problem before writing a single line of code. The right algorithm matters — so does knowing why it's right.

Clean Architecture

I write code that is modular, testable, and maintainable. SOLID principles, design patterns, and meaningful abstractions are non-negotiable in my workflow.

Production Mindset

Every project is built to run in production — with error handling, logging, type safety, and scalability considerations baked in from the start.