School of Medicine
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Rene Caissie
Adjunct Professor, Primary Care and Population Health
BioRene Caissie is an entrepreneur, researcher, and former surgeon who holds the position of CEO and Co-Founder at Medeloop.ai, a company dedicated to revolutionizing clinical research and trials through innovative AI technology. He serves as an Adjunct Professor at the Stanford University School of Medicine, where he teaches entrepreneurship in Digital Health and A.I.. In addition, he lectures within the Stanford Master of Science in Clinical Informatics Management (MCIM) program, mentoring students through their practicum experiences. Furthermore, he provides instruction at the Translational Medicine Program (MTM) at UCSF, focusing on the translational challenges in medicine. He is also a member of the XPRIZE Brain Trust Team, where he lends his expertise to foster healthcare innovations. Additionally, Rene serves as a Venture Partner at the venture capitalist firm OVO Fund
Rene’s entrepreneurial and medical expertise has spurred the creation of several healthcare ventures, such as Medesync EMR, which was acquired by the $37 billion telecommunications giant, Telus. Amid the Covid-19 crisis, he played a crucial role in developing a powered Full Head Protective Hood with an air-purifying respirator and co-founding Dorma Filtration, which introduced Canada's first reusable N95 mask.
Beyond his professional pursuits, Rene is an avid mountain climber, sailboat trans-oceanic racer, SR22 Turbo aircraft pilot, and Ironman World Championship qualifier. His dedication to humanitarian work is evident through his NGO, Volte-Face, which has provided over $1 million in free medical care for life-changing surgeries to underprivileged patients. As a board member for Sprouts, a California-based non-profit, he supports disadvantaged youths through skills coaching and internships. -
Alison Callahan
Research Engineer, Med/BMIR
BioAlison Callahan is an Instructor in the Center for Biomedical Informatics and Clinical Data Scientist in the Stanford Health Care Data Science team led by Nigam Shah. Her current research uses informatics to expand and improve the data available about pregnancy and birth, and to develop and maintain and EHR-derived obstetric database. She is also the co-leader of the OHDSI Perinatal & Reproductive Health (PRHeG) working group. Her work in the SHC Data Science team focuses on developing and implementing methods to assess and identify high value applications of machine learning in healthcare settings.
Alison completed her PhD in the Department of Biology at Carleton University in Ottawa, Canada. Her doctoral research focused on developing HyQue, a framework for representing and evaluating scientific hypotheses, and applying this framework to discover genes related to aging. She was also a developer for Bio2RDF, an open-source project to build and provide the largest network of Linked Data for the life sciences. Her postdoctoral work at Stanford applied methodologies developed during her PhD to study spinal cord injury in model organisms and humans in a collaboration with scientists at the University of Miami.
