I'm passionate about applying machine learning to medical imaging and healthcare challenges. My work focuses on developing intelligent systems for medical image analysis, particularly in abnormality and tumor detection.
My research explores text-guided object detection architectures for identifying abnormalities in chest X-rays, combining computer vision with natural language processing to enhance diagnostic capabilities. I'm driven by the potential of AI to assist healthcare professionals and improve patient outcomes.
Research investigating region-region similarity based text-guided object detection architecture for abnormality detection in chest X-ray imaging. This work explores a novel approach to combining textual descriptions with visual features to improve chest disease diagnostic accuracy.
Developed during the Beaver Works Summer Institute as a team project. Created a deep learning zero-shot object detection model for detecting and classifying brain tumor types including Meningioma and Glioma from medical imaging data.
Computer vision application that detects whether individuals are wearing face masks. Demonstrates practical application of machine learning for public health and safety monitoring.
Agricultural AI system for identifying diseases in tomato plants through leaf image analysis. Showcases machine learning's versatility in addressing real-world problems across different domains.
Feel free to reach out for collaborations or discussions about machine learning and medical imaging.