Kate Rankin, PhD, is a professor in the UCSF Department of Neurology and a neuropsychologist at the Edward and Pearl Fein Memory and Aging Center, part of the UCSF Weill Institute for Neurosciences. She specializes in understanding the neuropsychological, neuroanatomic, and genetic foundations of human socioemotional behavior in both healthy aging and neurodegenerative diseases.
Dr. Rankin earned her bachelor’s degree in psychology from Yale University before completing her doctoral training in clinical psychology and a master’s degree in theology at the Fuller School of Psychology in Pasadena, California. She then completed a clinical internship at the Veterans Affairs Northern California Health Care System’s Martinez Outpatient Clinic and UC Davis Medical Center, followed by a two-year postdoctoral fellowship in neuropsychology at UCSF.
At UCSF, Dr. Rankin has developed innovative tools to assess socioemotional functioning in patients with cognitive impairments. Her battery of tests, which measures empathy, theory of mind, personality, and social signal comprehension, has been adopted nationally by the National Institute on Aging’s Alzheimer’s Disease Research Centers to improve diagnostic accuracy for conditions such as behavioral variant frontotemporal dementia, semantic variant progressive aphasia, progressive supranuclear palsy, and corticobasal syndrome.
Dr. Rankin’s research uses advanced structural and functional imaging techniques to investigate the neurological changes that influence personality and social behavior, as well as the neural mechanisms underlying social cognition. She is dedicated to developing earlier and more precise diagnostic tools for neurodegenerative diseases.
In addition to her research, Dr. Rankin leads data and bioinformatics cores for numerous center grants and research consortia, facilitating collaboration across disciplines and institutions. She also plays a key role in UCSF’s Precision Medicine Knowledge Network Initiative and serves on several committees focused on advancing digital health and optimizing computational resources for research and clinical care.