Surgery
Showing 11-18 of 18 Results
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Perisa Ruhi-Williams, MD
Clinical Assistant Professor (Affiliated), Surgery - General Surgery
Staff, Surgery - General SurgeryBioDr. Perisa Ruhi-Williams is a board-certified General Surgeon practicing at the VA Palo Alto Health Care System. Her clinical practice is centered on utilizing robotic-assisted techniques for metabolic/bariatric surgery and hernia and abdominal wall reconstruction.
She graduated as an Echols Scholar with a Bachelor of Science in Biology from the University of Virginia. She earned her MD from the Virginia Tech Carilion School of Medicine and completed her General Surgery residency at the University of California, Irvine. While in residency, she served as the Chief Resident in Quality and Patient Safety at the VA Long Beach Medical Center. She subsequently completed an advanced fellowship in Minimally Invasive Surgery, Bariatrics, and Foregut Surgery at Stanford Health Care.
Dr. Ruhi-Williams is passionate about advancing surgical education and the wellness of surgical trainees. In addition to her clinical roles, she serves as the Site Director for the Surgery Core Clerkship at VA Palo Alto and Assistant Site Director for the General Surgery Residency Program at VA Palo Alto. -
Brian Ruhle, MD, MS
Clinical Assistant Professor, Surgery - General Surgery
BioDr. Brian Ruhle is a board-certified surgeon with dual-fellowship training in minimally invasive bariatric (weight loss) surgery and endocrine surgery. He is also a clinical assistant professor in the Department of Surgery, Division of General Surgery at Stanford University School of Medicine.
Dr. Ruhle specializes in bariatric surgery, foregut (upper digestive tract) surgery, adrenal surgery, and abdominal wall reconstruction. He uses leading-edge laparoscopic and robotic surgical techniques to help patients achieve sustainable weight loss and improve obesity-related health conditions. His expertise in advanced minimally invasive procedures offers patients significant benefits, including faster recoveries, reduced pain, and shorter hospital stays.
Dr. Ruhle’s research interests span a wide range of topics in metabolic and bariatric surgery. His studies have explored combination therapies for managing obesity, improvements in screening and treating endocrine disorders, and optimizing outcomes in thyroid and parathyroid surgeries. He has published his findings in many peer-reviewed journals, including Surgery, Journal of Gastrointestinal Surgery, and Journal of the American College of Surgeons.
Dr. Ruhle has presented at prominent national conferences, including the annual meetings of the American Association of Endocrine Surgeons and the American College of Surgeons Clinical Congress. His presentations have discussed using GLP-1 receptor agonists (weight loss medications that help regulate blood sugar and reduce appetite) before and after bariatric surgery. He has also addressed improving screening protocols for hyperaldosteronism (high blood pressure caused by excess production of the hormone aldosterone by the adrenal gland).
Dr. Ruhle is a member of the American Association of Endocrine Surgeons, the American Society for Metabolic and Bariatric Surgery, and the Society of American Gastrointestinal and Endoscopic Surgeons. -
Alejandra Ruiz
Postdoctoral Scholar, General Surgery
BioDr. Alejandra Ruiz is a physician-scientist working at the intersection of clinical medicine, health services research, and community-engaged intervention design. Based on her clinical experience in high-complexity settings, she works to optimize integrative care models that address both physical and mental health needs.
She is currently a postdoctoral researcher in the Departments of Emergency Medicine and General Surgery, where she examines structural barriers to care among underserved populations and develops pathways to improve access and care delivery. Her work is grounded in community-based participatory research, through which she designs, implements, and evaluates culturally responsive interventions. Dr. Ruiz is committed to advancing equitable, sustainable models of care that improve access, engagement, and patient outcomes. -
Charles William Ryan
Affiliate, Department Funds
Resident in SurgeryBioI was born and raised in Syracuse, New York. I first attended Onondaga Community College, where I developed a fascination with the development of complex biological systems, and then transferred to Syracuse University where I completed my B.S. in biochemistry. I next attended the University of Michigan MD/PhD program, where I used in-vitro models of human neurodevelopment to study to role of epigenetic marks in guiding neurogenesis. While at Michigan, I became interested in the prospect of harnessing in-vitro differentiation to cultivate functional tissues that can be transplanted to replace what is lost in degenerative conditions. Ophthalmology, with its microsurgical access to functionally critical cell layers, is well-positioned to capitalize on this emerging field of science to treat degenerative conditions. I am humbled and incredibly thankful to have the opportunity to pursue this aim as a SOAR resident at Stanford.
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Mattias Rydberg
Postdoctoral Scholar, Plastic and Reconstructive Surgery
BioMattias Rydberg, MD, PhD, is a hand surgeon and postdoctoral scholar in the Division of Plastic and Reconstructive Surgery at Stanford University School of Medicine. His research focuses on epidemiology, machine learning, and digital health technologies in hand surgery and musculoskeletal disease. Dr. Rydberg completed his medical and doctoral training at Lund University in Sweden, where his PhD work focused on diabetic hand disorders and large-scale register-based research.
At Stanford, he works in the laboratory of Dr. Paige Fox, studying peripheral nerve disorders, fibroproliferative diseases, and AI-based motion tracking technologies for upper extremity assessment. His current projects include national database studies on diabetes and entrapment neuropathies, frozen shoulder and Dupuytren’s disease, and the development of camera-based hand motion analysis tools using machine learning and computer vision.
