Hardworking and passionate job seeker with strong organizational skills eager to secure entry-level Developer position. Ready to help team achieve company goals.
Project-1
Title - City Navigator:
A Comprehensive Web Platform for Seamless Travel.
Technology used: HTML, CSS, JavaScript, Java, MY SQL, JSP, JDBC
Summary:
Developed a website to enhance the travel experience for tourists and provide valuable information about local businesses and attractions. I have used Bootstrap 4, JavaScript, MY SQL, and Java for developing this project. Implemented a monetization strategy by charging users for premium services. Incorporated three user-friendly modules catering to students, tourists, and business professionals, offering a wealth of city- related information. Ensured the system's adaptability for users seeking city insights, historical context, and real-time navigation. Successfully combined technology and local knowledge to create an innovative tool for optimizing the visitor experience and supporting local businesses.
Project-2
Title: Student Management System
Technology used: Java, JDBC, Spring Boot.
Summary:
Developed a Student Management System designed to revolutionize academic administration. Engineered a comprehensive platform that centralizes student information, streamlines enrollment processes, and tracks academic performance in real-time. Successfully integrated communication tools, automated attendance monitoring, and facilitated efficient course management.
Project-3
Title: Securing Electric Vehicles: An Intelligent Anomaly Detection System for Enhanced Cybersecurity in CAN Bus Communication
Technology used: Python.
Summary:
Team leader Led the development of a cybersecurity project for electric vehicles, focusing on detecting intrusions and anomalies in communication between sensors and Electronic Control Units (ECUs) utilizing the Controller Area Network (CAN) protocol. Implemented machine learning algorithms to analyze packet frequencies and prioritize requests, aiming to identify potential attacks. Successfully trained models to predict attacks based on abnormal request patterns, assigning class labels to distinguish between normal and malicious packets. Mitigated the risk of hackers disrupting ECU operations, thereby ensuring the reliability and safety of vehicle sensor communications.