π B.Tech in Electronics & Communication Engineering, VIT Bhopal (Graduating 2027)
π» Focused on IoT, Machine Learning, and Full Stack development
π± Currently sharpening: Data Structures & Algorithms, System Design, Backend Engineering
Detects fraudulent financial transactions using Machine Learning, achieving 92% detection accuracy on historical transaction data.
Tech Stack: Python Β· Flask Β· Machine Learning Β· MySQL
Key Features
- ML-based transaction risk prediction (92% accuracy)
- OTP verification and analytics dashboard
- Secure Flask backend with MySQL integration
π Repository: PayShield
Full-stack web application that flags suspicious expense claims using rule-based and AI-driven validation, with role-based access for Admin and Users.
Tech Stack: React Β· FastAPI Β· Python Β· MySQL
π Repository: ExpenseGuard
Intelligent drone system combining computer vision and embedded hardware for real-time manual control, live video streaming, and autonomous navigation β achieving 95% waypoint accuracy. Built for applications like surveillance and medical delivery.
Tech Stack: Python Β· OpenCV Β· Raspberry Pi Β· Computer Vision
π Repository: ABHRABHEDI
Ongoing collection of LeetCode solutions in Python, C++, and Java, categorized by topic to track consistent algorithmic practice.
π Repository: DSA-Problems