Bio
Alison 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.
