School of Medicine
Showing 711-720 of 939 Results
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Mahati Mokkarala
Assistant Professor of Radiology (Body Imaging)
Current Research and Scholarly InterestsMy research focus as a new attending will be on evaluating and implementing new technology in the radiology workplace including how technology can benefit private practice and academic radiologists.
This research focus is based on my current and previous research projects and interests. As an abdominal imaging fellow at the University of Pennsylvania, I worked on projects understanding how to apply spectral CT data in a clinical and research setting. Current projects include determining if spectral CT data can quantify normal organ characteristics. Understanding the age-old question of ‘what is normal’ is essential for determining if spectral CT data can help radiologists identify and characterize pathology.
Other previous research projects with interventional and diagnostic radiology colleagues at MIR include improving and evaluating the efficacy of multiple embolization agents. Additional diagnostic radiology projects as a resident included optimizing artificial intelligence programs that streamline radiology critical action items and better characterize glioblastoma imaging patterns. All projects had a common theme, focusing on implementing technology that could benefit both clinical and radiology practice and making sure that these tools would be useful for radiologists and other specialists. Radiology is unique because of how essential imaging interpretation is for modern medicine. An academic radiologist should be the leader in both developing and successfully integrating technology in the clinical world. -
Matteo Amitaba Mole'
Assistant Professor of Obstetrics and Gynecology (Reproductive, Perinatal & Stem Cell Biology Research)
Current Research and Scholarly InterestsWe study how the human embryo implants inside the maternal uterine tissue to establish a healthy pregnancy and the underlying maternal-embryo communication.
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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.
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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.
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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.
