Stanford University
Showing 61-70 of 92 Results
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William H. Robinson, MD PhD
James W. Raitt, M.D. Professor
Current Research and Scholarly InterestsOur lab investigates the molecular mechanisms of and develops therapies to treat autoimmune and rheumatic diseases, with a focus on rheumatoid arthritis, systemic lupus erythematosus, multiple sclerosis, and osteoarthritis.
The overriding objectives of our laboratory are:
1. To elucidate the mechanisms underlying autoimmune and rheumatic diseases.
2. To investigate the role of innate immune inflammation in osteoarthritis.
3. To develop novel diagnostics and therapeutics -
Neda Sattarnezhad Oskouei, MD, MS
Instructor, Medicine - Immunology & Rheumatology
BioDr. Neda Sattarnezhad Oskouei is a board-certified neurologist and neuroimmunologist specializing in Multiple Sclerosis (MS) and neuroimmunological disorders, including Neuromyelitis Optica (NMO), MOG Antibody Disease (MOGAD), optic neuritis, transverse myelitis, autoimmune encephalitis, neuro-rheumatological conditions, and neuroinfectious diseases. Her research focuses on understanding the role of pathogens in triggering autoimmunity, with a particular emphasis on the role of Epstein-Barr Virus (EBV) in the development of MS.
Dr. Sattarnezhad earned her MD degree with honors from Tabriz University of Medical Sciences. She completed a research fellowship in Multiple Sclerosis at the Brigham MS Center, Harvard Medical School, before pursuing her residency in adult neurology at the University of Illinois at Chicago. She further specialized by completing a clinical fellowship in Multiple Sclerosis and Neuroimmunology at Stanford University as a Sylvia Lawry Fellow of the National MS Society, during which she also earned a master’s degree in Epidemiology and Clinical Research. She subsequently completed a fellowship in immunology and rheumatology at Stanford.
Her research and training have been supported by the National MS Society (NMSS), National Institutes of Health (NIH), and National Institute of Allergy and Infectious Diseases (NIAID). Dr. Sattarnezhad is a member of the American Academy of Neurology (AAN) and the Consortium of Multiple Sclerosis Centers (CMSC). -
Mojtaba Sedigh Fazli
Postdoctoral Scholar, Immunology and Rheumatology
BioDr. Mojtaba Fazli is a leading scientist specializing in AI/ML, computer vision, and biomedical research. He is currently a Postdoctoral Research fellow Scientist at Stanford University and a Senior Research Fellow at the Harvard Ophthalmology Artificial Intelligence Lab, Harvard University, where he previously completed a postdoctoral fellowship.
Dr. Fazli's research bridges cutting-edge artificial intelligence with groundbreaking applications in multi-scale biomedical imaging, disease modeling, and drug discovery. His expertise encompasses advanced areas of AI/ML, including computer vision for 2D/3D medical image analysis, bioinformatics, and object tracking in both 2D and 3D environments. He has played a key role in developing state-of-the-art algorithms to enhance diagnostic precision and therapeutic outcomes within the biotechnology and healthcare sectors.
With a strong foundation in both academia and industry, Dr. Fazli previously served as a Senior Open Innovation Scholar at the Novartis Institute for Biomedical Research. There, he applied his expertise in strategic planning, programming, and simulation to tackle complex biomedical challenges.
Dr. Fazli holds a Ph.D. in Computer Science, with a minor in Mathematics, from the United States, as well as a Doctorate in Business Administration from France. His academic journey also includes master’s degrees in Economics and Management, as well as Artificial Intelligence and Robotics. His interdisciplinary approach blends AI-driven innovation with practical, impactful solutions in healthcare.
At Stanford, Dr. Fazli leads research initiatives focused on integrating multimodal data in rheumatology, advancing ultrasound imaging research in Rheumatoid Arthritis, and developing AI methodologies for clinical applications. His current work also involves leveraging Generative AI and Large Language Models (LLMs) to drive innovation in medical data analysis and clinical decision support.
