<p>Tony Solomonides studied mathematics at King’s College (1972-76) and computer science at Imperial College (1988-90), both in London. A lifelong academic, he made the transition from math to CS through pedagogy and by studying formal aspects of databases for his early research. In the mid-1980’s he undertook his first medical informatics project and has remained fascinated and engaged ever since.</p> <p>After his twin-track academic career as a biomedical informatician and as a computer scientist, culminating in his work in “healthgrids” and serving as Vice-President and Chair of the Scientific Board of HealthGrid from 2006 to 2010, Tony Solomonides was invited to join NorthShore in late 2011. He has contributed to the design, direction and analysis in several clinical research informatics projects. Lately he has served as co-PI on the PCORI-funded CAPriCORN network in the Chicago area. He chairs two Working Groups of the American Medical Informatics Association, the Ethics, Legal and Social Issues WG and the Clinical Research Informatics WG. He also has a longstanding relationship with CBMS, having participated over many years and served as Program Chair and host in 2011 in Bristol, UK.</p> <p>Tony has been working with colleagues at NorthShore, Case Western, Carnegie Mellon, Johns Hopkins and Weill Cornell to address the problem of diagnosis of “undifferentiated complaints”. He uses complementary methods from computer science and from cognitive science to understand physicians’ reasoning and practical actions in their effort to diagnose a patient’s condition.</p> <p>More broadly, Tony’s vision is to enhance the role of the patient as “expert” in his or her own condition and to engage the patient more directly in research in the “Learning Health System” movement. In this he hopes to leverage work done with his former student, Hanene Rahmouni, to create a system in which the patient can manage safely his or her own clinical data in a way that allows broad consent to be given for research, at the same time guaranteeing the integrity, privacy and confidentiality of the data through formal “norms” and data annotation.</p>