Maxim Topaz, PhD, RN, MA, is the Elizabeth Standish Gill Associate Professor of Nursing at the Columbia University Medical Center. He is also affiliated with Columbia University Data Science Institute and the Center for Home Care Policy & Research at the Visiting Nurse Service of New York. His research focusses on data science and he finds innovative ways to use the most recent technological breakthroughs, like text or data mining, to improve human health. Dr. Topaz’s research moto is “Data for good”. Dr. Topaz is one of the pioneers in applying natural language processing on data generated by nurses. His current work focusses on developing natural language processing solutions to advance clinical decision making. In the past, Dr. Topaz was involved with health policy (national and international levels), leadership (e.g. Chair of the Emerging Professionals Working Group of the International Medical Informatics Association) and health entrepreneurship. Dr. Topaz's clinical experience is in internal and urgent medicine. He earned his PhD degree as a Fulbright Fellow at the University of Pennsylvania and his Masters and Bachelors degrees from the University of Haifa, Israel. He completed a postdoctoral fellowship at the Harvard Medical School and Brigham Women's Hospital. He served as a Senior Lecturer at the School of Nursing, University of Haifa (Israel) where he was heading a Health Information Technology Lab. He published more than seventy articles on topics related to health informatics and received numerous prestigious awards for his work.
Charlene Ronquillio, PhD, RN, is a Filipina Scholar, Registered Nurse, and health informatician whose program of research focuses on health informatics, nursing, and health equity, underpinned by critical theory and implementation science. A key aim in her program of work is to ensure meaningful inclusion of non-dominant groups in the conceptualization, design, development, and implementation of health technologies in health systems. Dr. Ronquillio’s most recent work examines the role of nursing data in shaping opportunities to embed health equity in the development of machine learning algorithms and artificial intelligence for health systems. She has expertise in mixed methods, participatory, and co-production approaches and software design/development methods. Dr. Ronquillio also has experience with various aspects of health information technology in health systems and nursing, including nursing informatics competencies, usability research, user-centered design and development, rapid and exploratory prototyping, and technology adoption and usage. She obtained her BScN from McGill University (2007), and MSN (2010) and PhD (2021) from UBC. Prior to joining UBCO, she was a Health Service Improvement Research Fellow at the University of the West of England (2016), an Associate Research Fellow in Implementation Science at the University of Exeter Medical School (2016-19), and an Assistant Professor at Ryerson University in Toronto, ON (2019-21).
Laura-Maria Peltonen PhD, MNSc, RN, is an Adjunct Professor, Department of Nursing Science and Clinical Lecturer, Department of Nursing Science at the Unviersty of Turku, Finland. To date, Dr. Peltonen’s research has mainly focused on the role of information in decision-making on different levels in the provision of care. She contributed to developing tools to better support clinicians and health care managers in their daily work to support smooth and safe care provision. She worked with interdisciplinary and international teams with the most amazing people with similar interests in solving problems and in exploring, innovating, and improving clinical practice. She served in multiple elected positions with international informatics organizations, including International Medical Informatics Association and European Federation for Medical Informatics.
Lisianne Pruinelli, PhD, MS, RN, FAMIA is an Assistant Professor at the University of Minnesota School of Nursing. She earned a PhD degree from the University of Minnesota School of Nursing and a Master’s of Sciences and a Bachelor’s of Nursing Sciences degrees from the Federal University of Rio Grande do Sul, Brazil. Dr. Pruinelli teaches statistics and health informatics for undergraduate and graduate students. Her research leverages innovative nursing informatics tools and cutting-edge data science methods to investigate acute disease conditions, such as liver transplantation and sepsis. Her research uses multi-source electronic health data to discover new knowledge using a holistic approach to health, incorporating physiological, psychosocial, and other determinants of health. Dr. Pruinelli’s scholarship aims to increase the quality of health care delivery and improve the patient care experience in the continuum.
Martin Michalowski, PhD, MS, BSc, FAMIA, Dr. Martin Michalowski is an Assistant Professor in the Population Health and Systems Cooperative Unit in the School of Nursing at the University of Minnesota. Dr. Michalowski's domain of expertise is Artificial Intelligence (AI) with research interests spanning several AI areas of particular importance to medical informatics including data integration, data modeling, machine learning, clinical decision support, and knowledge representation. Automated reasoning, including constraint-based approaches, data analytics using spatio-temporal analysis methods, planning and scheduling, and Bayesian-based machine learning for game playing, rounds out his research background. His research philosophy in the area of medical informatics is centered on interdisciplinarity and brings advanced AI methods and approaches to clinical decision support, including the mitigation of computerized clinical practice guidelines for complex patients, and personalized medicine. Methodologically, Dr. Michalowski uses automated reasoning to provide clinicians with decision support at the point of care. He also applies problem modeling techniques to capture knowledge required for improving treatment decisions and uses big data analytics to support personalized medicine. He is also involved in the development of mobile educational tools for educators and students where he uses integrated automated reasoning, knowledge representation using ontologies, and human factors design. Dr. Michalowski is a member of the Association for the Advancement of Artificial Intelligence (AAAI) where he was awarded Senior Member status in 2018. Senior Member status is designed to recognize AAAI members who have achieved significant accomplishments within the field of artificial intelligence. He is also a member of the American Medical Informatics Association (AMIA) and is a program committee member for conferences including AMIA, AIME, and AAAI, among others. Dr. Michalowski serves on various grant review committees and he is co-chair of the International Workshop on Health Intelligence (W3PHIAI). His research has been funded by various government agencies including the NIH, DARPA, and the NSF, has been published in over 75 manuscripts across computer science and health informatics venues, has resulted in the co-founding of several companies, and has led to several issued patents.