🎓 Computer Science Graduate | Backend Engineer | 🧠 Problem Solver
I'm passionate about building production-ready backend systems, data-driven ML solutions, and solving complex problems in Java, Spring Boot, full-stack development, and machine learning. I actively compete on Codeforces and continuously upskill through hands-on projects and certifications.
A production-ready E-Commerce backend built with Java and Spring Boot, featuring scalable REST APIs and role-based JWT authentication.
Tools & Tech: Java, Spring Boot, PostgreSQL, Redis, Docker, JWT, GitHub
Highlights:
- Designed scalable REST APIs handling full CRUD operations with role-based JWT authentication.
- Integrated Redis caching, reducing database read load by ~40%.
- Optimized SQL queries using indexing, improving API response time by 30%.
- Containerized application using Docker for consistent deployment across environments.
- Implemented global exception handling for production-ready API behavior.
A complete book store system built with a React frontend and Django backend (Django REST Framework). Implemented end-to-end features for browsing, searching, user authentication (JWT), cart & checkout flows, and an admin interface for managing inventory.
Tools & Tech: React, Django, Django REST Framework, PostgreSQL, JWT, Axios, Docker, GitHub
Highlights:
- Designed RESTful APIs and React components for product listing, filtering (by author, genre, price), and detailed book pages.
- Implemented secure authentication with JWT, role-based access for admin users, and protected routes on the frontend.
- Cart persistence, order creation, and basic checkout flow (mock payment integration).
- Clear project structure, README with setup & run instructions, and environment configuration for local development.
Predicts the best fertilizer based on crop, weather, and soil data using boosting algorithms and interactive EDA.
Tools: Python, XGBoost, Pandas, Scikit-learn, Kaggle
Highlights:
- Applied interactive EDA and feature engineering for data-driven insights.
- Used XGBoost boosting algorithm for high-accuracy predictions.
- Evaluated using MAP@3 metric — part of Top 10% global Kaggle ranking.
Forecasts future crop prices using historical and environmental data.
Tools: Python, Scikit-learn, Pandas, Machine Learning
Highlights:
- Designed ML pipeline using historical data, weather patterns, and market trends.
- Applied feature engineering and ensemble models to achieve 90%+ prediction accuracy.
- Optimized pipeline for large datasets while maintaining high accuracy.
Designed a secure and efficient banking network with VLANs, VPNs, ACLs, and DNS.
Tools: Cisco Packet Tracer, TCP/IP, OSPF, VLANs, VPN, ACLs
Highlights:
- Configured VLANs, VPNs, and ACLs for branch-level security and communication.
- Set up OSPF routing and DNS for secure ATM and inter-branch connectivity.
- Programming: C++, Java, Python, JavaScript, SQL, DSA, OOP
- Web & Full-Stack Development: HTML, CSS, JavaScript, React, Django, Spring Boot
- Tools & Platforms: Git, Docker, Azure Integration Services, Cisco Packet Tracer, Linux, Bash
- ML & Data Science: Pandas, Scikit-learn, XGBoost, EDA, Feature Engineering
- Databases: PostgreSQL, Redis — indexing, normalization, data modeling
- Soft Skills: Problem Solving, Critical Thinking, Attention to Detail, Team Collaboration
- 🥇 Kaggle — Top 10% Global Rank across ML competitions
- ⭐ GFG Two-Star Coder — 1500+ rating on GeeksforGeeks
- 💡 500+ DSA problems solved across LeetCode, GFG, and CodeChef
- 🏋️ Codeforces rating: 740 — actively competing
- 🐍 Python (Advanced) – HackerRank (Certificate)
- 🔐 Cybersecurity Foundation – IBM SkillsBuild
- 🛡️ Red Team & Blue Team Fundamentals – TryHackMe
- 🏋️ Codeforces Rating: 740 (active)
- ⭐ Two-Star Coder on GeeksforGeeks (1500+ rating)
- 💡 Profiles:
- 📧 Email: udaykanchanpally408@gmail.com
- 🐙 GitHub
- 🧠 Kaggle