Dhanush Shetty

Bengaluru

Summary

Detail-oriented developer skilled in database management, API integration, and debugging. Proven ability to collaborate effectively and adapt to dynamic environments.

Education

SSLC -

V.K.R Acharya Memorial High School

Kundapura , Udupi District

07-2021

Pre-University Course - Science

RN Shetty PU College

Kundapura , Udupi District

03-2023

Bachelor of Engineering - Information Science

Atria Institute of Technology

Bengaluru , Hebbala

07-2027

Skills

Programming Languages: Java, Python (Basic)
Core Concepts: Object-Oriented Programming, Basic Data Structures, Exception Handling
Application Development: Console-based Application Development, Basic Full-Stack Exposure
Backend & Frameworks: Java Database Connectivity (JDBC), Spring Framework (Basic)
Databases: Basic Database Concepts, File-based Data Storage

APIs & Integration: Basic API Usage and Integration
Dev Tools & Platforms: Git, GitHub, Gradle, Maven,Command Line Interface (CLI)
Containerization: Docker (Basic Exposure)
Debugging & Development: Basic Code Debugging, Modular Code Structure

Projects

Bank Account Management System (Java)

Developed a Java-based console application to simulate core banking operations such as account creation, deposits, withdrawals, and balance inquiries. Implemented object-oriented programming concepts, including encapsulation, constructors, and exception handling, with modular class design for maintainability and future scalability

SyncSphere – Distributed Synchronization Engine

Created a full-featured peer-to-peer file synchronization application demonstrating expertise in distributed systems architecture. Key achievements: implemented automated file scanning and metadata tracking, built peer discovery and message handling for network communication, engineered conflict resolution logic, and developed a monitoring UI. Tech stack: Java, Gradle, multithreading, file I/O, and network programming.

AI-Powered Timetable Generator

Developed an AI-based timetable generation system that creates conflict-free academic schedules by considering student enrollments, elective choices, credit structure, and faculty availability The system generates optimized timetables in exportable formats, reducing manual scheduling effort.

AI BASED EMAIL VALIDITY AND PHISHING DETECTOR

Built a full-stack cybersecurity application that classifies emails and URLs as legitimate or phishing using heuristic feature extraction and a Random Forest ML model. Implemented a Python Flask backend with a responsive HTML/CSS/JavaScript frontend, providing real-time results with confidence scores and under 200ms latency