My research interests span a captivating spectrum at the convergence of cutting-edge technologies and critical healthcare applications

• Medical Image Analysis and Processing: In this dynamic field, we explore the intricate details of medical images—be it X-rays, MRI scans, or histopathological slides. By developing robust algorithms, we unravel patterns, segment organs, and detect anomalies. Whether it’s identifying tumors, quantifying disease progression, or enhancing image quality, our work directly impacts clinical diagnosis and patient care.
• Machine Learning: As a researcher, we harness the power of machine learning to unlock hidden insights within medical data. From convolutional neural networks (CNNs) to recurrent models, and state of art models. we delve into supervised and unsupervised learning. These algorithms aid in image classification, feature extraction, and predictive modeling. Our goal? To augment diagnostic accuracy and automate repetitive tasks for healthcare professionals.
• Computational Neuroscience in fMRI: The human brain remains an enigma, and functional magnetic resonance imaging (fMRI) provides a window into its activity. Here, we analyze brain connectivity, map neural networks, and decode cognitive processes. By integrating machine learning techniques, we uncover biomarkers for neurological disorders, paving the way for early detection and personalized treatment strategies.
• Computer Vision and Image Processing: Pixels hold secrets, and computer vision techniques allow we to extract meaning from visual data. Whether it’s detecting retinal abnormalities, segmenting lesions, or tracking cell migration, our work bridges the gap between pixels and clinical insights. Image enhancement, 3D reconstruction, and feature extraction—all contribute to advancing healthcare through visual understanding.

In this captivating journey, we decode pixels, train models, and collaborate with clinicians, ultimately shaping the future of healthcare.

Active areas are as follows: