I'm a Computer Science undergraduate at KIIT University (Class of 2026) with a passion for building innovative solutions that solve real-world problems. Currently focused on machine learning, full-stack development, and privacy-focused applications.

• CognitoPics: A privacy-focused photo management application using face recognition and encryption
• Cloud Architecture: Learning AWS and serverless technologies
• Cybersecurity: Exploring security fundamentals and best practices

• AWS Cloud Architecture & Services
• Red Hat Linux Administration
• Cybersecurity Fundamentals
• Advanced Machine Learning Techniques

I'm actively seeking internship opportunities in software development, machine learning, and cloud computing. I enjoy collaborating on projects that make a meaningful impact.

Technologies: Python, Streamlit, OpenCV, Face Recognition, Cryptography

• Developed a smart photo management system that automatically detects and encrypts photos containing selected faces
• Implemented secure encryption algorithms for privacy protection of personal images
• Created an intuitive interface inspired by Google Photos with enhanced privacy features
• Status: Active development with planned features for batch face detection

Technologies: AWS Lambda, Node.js, DynamoDB, Serverless Framework

• Built a fully serverless expense tracking application with real-time categorization
• Implemented cost-effective architecture using AWS services for scalability
• Created data visualization features for spending pattern analysis
• Achieved 99.9% uptime with minimal operational costs

Technologies: Python, Scikit-Learn, Machine Learning, Data Analysis

• Developed machine learning models for heart disease prediction using clinical datasets
• Implemented multiple algorithms (Logistic Regression, KNN, Random Forest) with accuracy comparison
• Applied feature engineering and cross-validation techniques to improve model performance
• Achieved 85%+ accuracy in disease prediction

Technologies: Node.js, Java, MySQL, Web Development

• Designed and developed a robust event scheduling platform for college campus
• Built system capable of handling 1,000+ concurrent users with optimized database queries
• Created intuitive interface for students to track events from various societies and clubs
• Implemented real-time notifications and calendar integration