Valentina Pedoia, PhD, is an Assistant Professor in the Radiology and Biomedical Imaging Department. She is an Imaging scientist with a primary interest in developing algorithms for advanced computer vision and machine learning to improve the usage of non-invasive imaging as diagnostic and prognostic tool. She obtained her doctoral degree in Computer Science working on features extraction from functional and structural brain MRI in subjects with glial tumors. After graduation, in 2013, she joined the Musculoskeletal and Imaging Research Group at UCSF as post-doctoral fellow to study degenerative joint diseases with compositional MRI techniques.
Dr Pedoia joined UCSF as Faculty In 2018. She is part of the Center of Intelligent Imaging where she serves as Co-director of the Educational Pillar. Her current research is focused in exploring the role of machine learning to extract imaging biomarkers of several musculoskeletal conditions including knee and hip Osteoarthritis, shoulder Instability and lower back pain. She develops analytics to model the complex interactions between morphological, biochemical and biomechanics aspects of the joints as a whole. Her goal is to develop efficient and effective data-driven models that able to extract imaging features and use them to identify risk factors, stratify patients and predict outcomes.
She has great interest in the clinical translation of novel technology, as such she is invested in making the image acquisition and processing faster, safer, and smoother for patients and clinicians.