Atul Anilkumar

Developed an artificial intelligence framework for automated detection and risk prediction of Non-Alcoholic Fatty Liver Disease using clinical and biochemical parameters. Employs XGBoost for early disease classification and is designed to be extendable to imaging modalities (CT, Ultrasound, MRI) using Vision Transformers and Mamba models.

Introduced an image filtering technology using convolutional neural networks to leverage structural features from guidance and target images. The system creates learned kernels for edge detection and feature extraction from images, surpassing traditional filtering approaches.

Java-based system to manage student attendance with features including attendance marking, data visualization, leave management, and grievance management. Built with a relational database backend for institutional deployment.

Full-featured e-commerce web application for online grocery shopping. Includes product catalogue management, cart functionality, e-payment integration, and an admin order management dashboard.