Duygu Tosun is a professor of radiology and biomedical imaging at the University of California San Francisco and is the founding director of Medical Imaging Informatics and Artificial Intelligence at the San Francisco Veterans Affairs Medical Center. Her research focuses on neuroimaging, neurodegenerative diseases, and psychiatric disorders. The goal of her research is to develop multi-modal biomarkers using advanced imaging technology that can detect the progression of neurodegenerative pathologies before they cause irreversible damage to the brain. One of the key objectives of Dr. Tosun’s research is to develop validated biomarkers of neurodegeneration. These markers could be used for early diagnosis, initiating prevention strategies for those at risk, monitoring the efficacy and regional specificity of therapies, and clinical trial enrichment. She has over 20 years of experience in developing algorithmic approaches for the analysis of multi-disciplinary and multi-modality data, including neuroimages, fluid biomarkers, genetics, proteomics, and cognitive measures, all within a unified framework. Her work is characterized by inter-disciplinarity as she has applied her computational expertise in an engineering framework to facilitate both clinical neuroscience research studies and clinical trials on Alzheimer’s disease and related dementias. Her research has been peer-funded by various sources, including the National Institute of Aging, Department of Defense, Michael J. Fox Foundation, Alzheimer's Association, and several industry partners and pharmaceutical collaborations. She has held various roles in collaborative projects, including serving as a co-investigator of ADNI, leading the ADNI MRI Core’s efforts on processing of structural and ASL MRIs, and serving as the PI of the ADNI4 Project on the role of imaging and fluid biomarkers in Alzheimer’s disease clinical trials. Additionally, she is a co-investigator/site-PI/core-lead in various multicenter collaborative projects such as NIA R01AG058676: Alzheimer's Dementia Onset and Progression in International Cohorts; NIA U01AG068057-01: Ultrascale Machine Learning to Empower Discovery in Alzheimer’s Disease Biobanks; NIA U24AG057437 Alzheimer's Clinical Trials Consortium – ACTC; U24 AG074855: Alzheimer's Disease Sequencing Project Phenotype Harmonization Consortium. She brings extensive experience in the development and validation of biomarkers for Alzheimer’s disease clinical trials and has previously led multiple projects on biomarker development in neurodegenerative conditions.