Stanford University
Showing 21,421-21,430 of 36,173 Results
-
Hylton Molzof, PhD, MPH
Clinical Assistant Professor, Psychiatry and Behavioral Sciences - Sleep Medicine
BioDr. Molzof is a Clinical Assistant Professor and Licensed Psychologist in the Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine. She specializes in the assessment and treatment of sleep disorders via behavioral sleep medicine interventions, including Cognitive Behavioral Therapy for Insomnia (CBT-I) and positive airway pressure (PAP) desensitization. She also utilizes evidence-based techniques to help patients better manage circadian rhythm disorders, such as delayed sleep-wake phase disorder and shift work sleep disorder. Inspired by her background in public health, she has a strong interest in quality improvement and program development projects aimed at enhancing the quality and accessibility of sleep and circadian medicine for the diverse patient population served by Stanford Sleep Medicine Center.
-
Arash Momeni, MD, FACS
Associate Professor of Surgery (Plastic and Reconstructive Surgery)
Current Research and Scholarly InterestsDr. Momeni's research focuses on clinical outcomes after microsurgical reconstruction, with a particular emphasis on VTE prevention.
-
Shadi Momtahen
Postdoctoral Scholar, Anesthesiology, Perioperative and Pain Medicine
BioShadi Momtahen holds a BSc and MSc in Computer Science and Engineering, and a Ph.D. in Mechatronic Systems Engineering from Simon Fraser University, where she collaborated with the BC Cancer Agency on deep learning applications for cancer detection and treatment. She previously served as a Postdoctoral Research Fellow in the Department of Medicine at the University of British Columbia, working with the International Collaboration on Repair Discoveries (ICORD) to develop machine learning models for biosensor-based health monitoring.
Currently, Shadi is a Postdoctoral Scholar at the Aghaeepour Lab at Stanford Medicine. Her research focuses on applying deep learning to large-scale medical datasets—including wearable vital signs—to identify clinically relevant patterns and enable predictive, personalized healthcare.
