Kathrin Cresswell  

Professor Kathrin Cresswell is a social scientist with extensive experience in conducting formative evaluations of digitally enabled change and improvement programmes in health and care. She has consulted for the World Health Organization, Harvard Medical School, NHS England and Improvement. She is a member of the International Academy of Quality and Safety in Health Care, the Royal Society of Edinburgh Young Academy of Scotland, has received the Yvonne Carter Award for Outstanding New Researcher, and has been an invited speaker at the European Parliament and Harvard Medical School. She is also a Fellow of the International Academy of Health Sciences Informatics, and co-chair of the International Medical Informatics Association (IMIA) and European Federation of Medical Informatics Evaluation Working Groups on evaluation. She has over 140 peer-reviewed publications in international academic journals and £56 million in research grant funding. She is currently Professor of Digital Innovations in Health and Care at the Usher Institute at the University of Edinburgh, and Course Lead on a Scottish national digital health leadership programme. She was previously Module Lead on an English national digital health leadership programme and has taught over 450 national and international health information technology leaders about Technology Strategy and Health Information Systems Implementation.

She has researched the use of a variety of health information technologies in context. These have included both patient- and professional-facing technologies comprising electronic health records, robotics, health and fitness apps, artificial intelligence and decision support systems. She is an expert in conducting evaluations of digital applications, having applied formative methods in a variety of health and care settings (hospitals, primary care, and home). Bringing together stakeholders with varying perspectives is key to her ongoing work, where she examines how political, commercial, organisational, patient and health and care workers’ interests need to be aligned to transform health and care through safe and scalable technologies.

Charles Friedman  

Charles Friedman is Professor of Learning Health Sciences at the University of Michigan Medical School, where he directs the Knowledge Systems Laboratory.  He was formerly Founding Chair of the Department of Learning Health Sciences and the Josiah Macy Jr. Professor of Medical Education. He holds joint appointments in the Schools of information and Public Health. He is editor-in-chief of the open-access journal Learning Health Systems and co-chair of the multi-national movement to Mobilize Computable Biomedical Knowledge.

Throughout his career, Friedman has developed and studied methods to improve health, education, and research through innovative applications of information technology.  Most recently, Friedman has focused his academic interests and activities on the concept of Learning Health Systems that improve health by marrying discovery to implementation, and the socio-technical infrastructure required to sustain these systems.  

Friedman is a Distinguished Fellow of the American College of Medical Informatics, and a founding fellow of the International Academy of Health Sciences Informatics. He holds an honorary doctorate from the University of Lucerne in Switzerland for his contributions to the science of Learning Health Systems. Prior to coming to Michigan, Friedman held executive positions at the Office of the National Coordinator for Health IT (ONC) in the U.S. Department of Health and Human Services. Immediately prior to his work in the government, he was Associate Vice Chancellor for Biomedical Informatics, and Founding Director of the Center for Biomedical Informatics at the University of Pittsburgh.

Elia Lima-Walton  

Dr Elia Lima-Walton, MD, PA is a physician informaticist, data science and generative AI product leader with 12 years' experience in healthcare as a clinician, researcher, and AI developer. As a Principal Product Manager at the Mayo Clinic, Elia works on designing and incubating high-impact strategic data science and generative AI products focusing on education, clinical practice, and research.

Before working at the Mayo Clinic, she held various roles at Elsevier, Inc., including Director of Data Science and Clinical Analytics, where she partnered with executive leadership to enrich the product portfolio and aligned data initiatives with commercial and technical goals. She has also served as Clinical Analytics Manager and Clinical Knowledge Representation Specialist, where she managed resources, and developed pipelines for talent acquisition. Additionally, in these roles, Elia provided clinical, data science, and taxonomic expertise in development and optimization of Clinical Decision Support products, while supporting the growth of ontologies and knowledge graphs.

Prior to Elsevier, Elia worked in clinical research and healthcare roles at Biopharma Informatic, Inc., Spring Branch Health Ministry, Icahn School of Medicine at Mount Sinai, and the University of Texas MD Anderson Cancer Center. She has also been an advisor and speaker at various global conferences and events and has served as an academic advisor and mentor to Master’s and PhD students at Columbia University DSI, and Oxford University Big Data Institute, and at the University of Amsterdam. Elia holds a Doctor of Medicine degree from New York Medical College and a Título de Médico Cirujano from the Universidad Autónoma de Guadalajara Medical School. She has provided advisory consul to the European Commission’s European Health Data Space (EHDS), the NICE Content Advisory Board, and the German Government Affairs, to improve equity, interoperability, and access to data.

Elia’s interests include semantic pattern recognition, text mining, CDS, automatic item generation, knowledge graph development, computable clinical frameworks, linguistics, and Responsible AI best practices. In her free time, you can catch Elia hiking in the Smokey Mountains of North Carolina, traveling to exotic lands, or painting.