Stanford Surgery News

Greg Tiao, MD will join the Stanford Surgery team as a Professor in in the UML effective January 1, 2026. Tiao will be dual-appointed in the Divisions of Abdominal Transplantation and Pediatric Surgery.

Administrative Division Manager for General Surgery Ivette Arenas and Department Human Resources Administrator Anna Noriega are the inaugural recipients of the Stanford Surgery Staff Awards.

A Stanford Surgery delegation traveled to Montréal last week to advance a growing collaboration with the Centre Hospitalier de l’Université de Montréal (CHUM) and the Université de Montréal’s surgical and medical research programs. The visit focused on expanding joint clinical innovation, research exchange, and future opportunities for trainee engagement between the two institutions.

Dr. Stephan Busque shares insights from his 20-year journey in transplant tolerance, revealing groundbreaking research that will improve patient care, including the recent allogenic islet cell + bone marrow transplant for a Type 1 diabetes patient.

The American College of Surgeons (ACS) Scholarships Committee selected Dr. Cintia Kimura as a recipient of the 2026-2028 ACS Resident Research Scholarship.

Dr. Amanda Kirane has been promoted to Associate Professor in the Division of General Surgery, effective January 1, 2026.

Transplant Surgeon Dr. Tom Pham just returned from his most recent trip to Lusaka, Zambia, where he is working to create a kidney transplant program. This time, he was accompanied by fellow Stanford faculty members: Drs. Ken Tran from the Division of Vascular Surgery and Maha Mohamed from the Division of Nephrology in the Department of Medicine.

Dianelis Lopez is a Stanford Medical Student working in Dr. Sherri Krams' Lab and with the Center for Global Health.

Dr. Anand Athavale, Clinical Assistant Professor of Surgery in the Division of Vascular Surgery at Stanford, has been selected to receive the prestigious 2026 AVF-JOBST Clinical Research Grant Award from the American Venous Forum (AVF).

A machine learning-based model predicts how long it will take an organ donor to die after removing life support, aiding surgeons in deciding whether organs can be successfully transplanted.