Extracurricular

Hacksecure 2026

As part of HackSecure’26 at NIT Hamirpur, I worked on developing an SMS fraud detection application exploring energy-efficient neuromorphic AI for cybersecurity. Our comparative experiments showed that the Spiking Neural Network (SNN) model required approximately 444× fewer computational operations and achieved an estimated 14,000× lower energy consumption than conventional Artificial Neural Networks (ANNs), while maintaining practical detection capability. This project strengthened my interest in building low-power intelligent security systems at the intersection of computational neuroscience, neuromorphic computing, and trustworthy AI.

AI Synergy Hackathon

At the AI Synergy Hackathon, I contributed to Air-Sense, an AI-powered environmental monitoring solution designed for real-time air quality analysis and health-aware decision support. The project focused on transforming environmental sensor data into actionable insights through intelligent analytics and user-friendly visualization. Working on this application strengthened my practical experience in applied machine learning, intelligent sensing, and building AI systems for real-world societal challenges.