Abhishek Rathod N

I've built AI systems for medical imaging, NLP, and human-computer interaction, including an Attention U-Net that reached 98.6% validation accuracy for carotid artery segmentation across 1,100 ultrasound images.

My clickbait-detection classifier combined BiGRU, custom attention, focal loss, spaCy, and GloVe embeddings to achieve 95% accuracy and a 0.95 macro F1-score. I also built a real-time gesture-control system with MediaPipe, OpenCV, and PyAutoGUI, delivering 92% recognition accuracy at 50ms latency.

At Srijiva HealthCare, I developed responsive React.js interfaces, integrated RESTful APIs, and created reusable UI components. I improved frontend performance through code splitting, lazy loading, efficient state management, debugging, and deployment support.

I've published crop-yield prediction research using a Bagging Regressor model with R = 0.9859, and I was selected for Amazon ML Summer School. I'm pursuing a B.Tech in Artificial Intelligence and Data Science while continuing to bridge intelligent models with scalable frontend delivery.