Undergraduate research projects and early explorations in AI & healthcare
Developed a CNN-based system for early detection of Parkinson's Disease by analyzing patient drawings (spirals and waves). Achieved 94% accuracy on test dataset using transfer learning with VGG16 architecture.
Publication: Vatsaraj, I., et al. "Deep Learning for Parkinson's Disease Detection from Hand Drawings." International Journal of Engineering Research & Technology (IJERT), 2021.
Designed and implemented algorithmic optimization strategies for hospital patient flow management. Reduced average wait times by 23% and improved bed utilization efficiency using queuing theory models.
Publication: Vatsaraj, I., et al. "Algorithmic Optimization of Hospital Patient Flow Using Queuing Models." International Journal of Engineering Research & Technology (IJERT), 2021.
Built a real-time driver drowsiness detection system using computer vision and facial landmark detection. The system monitors eye aspect ratio and yawning patterns to alert drowsy drivers, potentially preventing accidents.
Conference: Vatsaraj, I., et al. "VIGILANT: Real-time Driver Drowsiness Detection using Computer Vision." IEEE INDICON 2021, Guwahati, India.