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Expert has a PhD in Computer and Information Science with a major in artificial intelligence and minors in the theory of computation and cognitive science. His artificial intelligence worked included knowledge sharing and problem solving strategies for knowledge-based systems ranging from work funded by the Department of Defense, NIH, and the Office of Naval Research. He has developed models of expert problem solving and diagnostic reasoning in highly uncertain domains, such as red blood cell antibody identification, naval tactical decision making, and biopsy interpretation. He has also been a consultant on the use and development of Bayesian networks for automated medical triage. He has experience developing and using ontologies and semantic web approaches to categorize medical errors and improve information retrieval in clinical and translational data warehouses.

He has extensive experience with LISP, the ACT-R rule-based system.

He has a minor in Cognitive Science and has spent the past 20 years using cognitive models and theories to understand expert decision making, human learning, and to design user interfaces that decrease errors and improve decision making and efficiency. His work ranges from computational models of human learning and problem solving, to the effect that problem representation has on learning and problem solving.

He is an expert in the use of human factors engineering and cognitive science to evaluate, design, and improve medical devices and health information technology (HIT). For the past 10 years he has been working to improve patient safety and the quality of care. He has developed guidelines for evaluating the usability and safety of medical devices, examined the role of HIT in remote ICU monitoring, and contributed to the evaluation, design, or redesign of several health-related software applications, As a consultant he has assisted with the identification of use-related hazards as part of the risk analysis process for a new medical device. He has also worked as a consultant on the evaluation of a medical device interface during early device development.

He has provided expert guidance on how to design and evaluate user interfaces in a variety of healthcare-based software, including software for use by genetic counselors, computer-based training programs for psychiatric nurses, and patient education software for women newly diagnosed with breast cancer. He conducted risk analysis associated with use-errors for a medical device manufacturer.