School of Medicine


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  • Shivam Vedak

    Shivam Vedak

    Affiliate, Dean's Office Operations - Dean Other
    Fellow in Graduate Medical Education

    BioShivam Vedak, MD, MBA, is a clinical informatics fellow and internal medicine physician at Stanford Medicine. He holds a B.S. in Biology-Neuroscience from the Schreyer Honors College at The Pennsylvania State University, and an MD/MBA dual-degree from the University of Illinois at Chicago (UIC). He trained in the UIC Internal Medicine Residency program, during which he was selected as the American College of Physicians Outstanding Resident of the Year (2022) for his hospital-wide EHR optimization and education efforts. He also won several international hackathons as head of ImmunoLynk, a pandemic-era collaborative to improve COVID testing accuracy through use of machine learning and blockchain technology.

    Clinically, Dr. Vedak practices as a hospitalist physician at Stanford Health Care. He is passionate about education, digital health, and the practical implementation of novel technologies in the traditionally slow-moving health care industry. This includes improving the quality of medical education surrounding Clinical Informatics, artificial intelligence, and the business of medicine, to ensure that physicians have the appropriate knowledge to safely integrate emerging innovations into their clinical practice.

  • Ophir Vermesh

    Ophir Vermesh

    Affiliate, Dean's Office Operations - Dean Other
    Resident in Radiology

    Current Research and Scholarly InterestsMy interests lie at the interface of medicine and technology, engineering new wearable and implantable technologies for earlier cancer detection and continuous monitoring. I am particularly interested in moving promising diagnostic technologies past the proof-of-concept phase and into the clinic.

  • Davis Vigneault

    Davis Vigneault

    Affiliate, Dean's Office Operations - Dean Other
    Resident in Radiology

    BioDavis is a resident in diagnostic radiology at Stanford, having received his medical degree from Tufts University School of Medicine and his DPhil in Biomedical Engineering from the University of Oxford through the NIH-Oxford Scholars and medical scientist training programs. For his graduate degree, worked on novel algorithms for measuring regional cardiac function from cardiac CT and MR, publishing in Radiology, Medical Image Analysis, and the Journal of Cardiovascular Magnetic Resonance, among others. In addition to cardiovascular imaging and deep learning, Davis has a strong interest in open source science, having been a frequent contributor of software to ITK and other libraries in the ITK ecosystem.

  • Joshua Aaron Villarreal

    Joshua Aaron Villarreal

    Affiliate, Dean's Office Operations - Dean Other
    Fellow in Graduate Medical Education
    Resident in Graduate Medical Education

    BioDr. Villarreal is a current clinical informatics fellow at Stanford Medicine and first surgical resident to enter the program. He began general surgery training at Stanford in 2020. Dr. Villarreal is a Texas native and hometown is in McAllen TX. He completed medical school at Baylor College of Medicine in 2020 and undergraduate studies in Human Biology at the University of Texas.

    During residency, Dr. Villarreal has published numerous articles in a wide range of surgical fields including: pediatric surgery, liver transplantation, trauma critical care and surgical data science. He currently holds the role as president of the resident led surgical research group Surgeon’s Writing About Trauma (SWAT) and mentors medical students and undergrads in conducting surgical related clinical research. He is a member of the Artificial Intelligence in Surgery research group at Stanford focused on leveraging methods in machine learning in the care of transplant patients.

    His long-term goals are to apply clinical informatics frameworks to optimize surgical care workflows, enhance intraoperative decision making, and increase accessibility of outpatient surgical services to lower income patients.