معرفی
Dr. Farah Deeba is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of North Carolina at Charlotte. Her research focuses on Medical Imaging, Placenta Tissue Imaging and Characterization, Quantitative Ultrasound Signal Processing, and Machine Learning. She is affiliated with the university's Electrical & Computer Engineering department and can be contacted at fdeeba@charlotte.edu.
Dr. Deeba holds a Ph.D. from The University of British Columbia (2022), an M.Sc. from the University of Saskatchewan (2016), and a B.Sc. from Bangladesh University of Engineering and Technology (2013). Her work emphasizes innovative applications of ultrasound technology in placenta tissue analysis, aiming to improve diagnostic precision for placenta-mediated diseases.
Her research integrates quantitative ultrasound techniques with machine learning to enhance medical imaging accuracy, particularly in obstetric contexts. Recent studies include phantom-based calibration, automatic placenta segmentation, and multi-modal imaging approaches for placental biomarker detection. Her publications often address challenges in signal processing and regularization methods for ultrasound data analysis.
While no formal awards or grants are explicitly listed, her contributions span academic and clinical domains, with a focus on advancing non-invasive diagnostic tools. Her work aligns with broader efforts in biomedical engineering and medical imaging innovation.
