Organizing Committee

Maxim Topaz, PhD, RN, MA, is the Elizabeth Standish Gill Associate Professor of Nursing at the Columbia University Medical Center. He is affiliated with the Columbia University Data Science Institute and the Center for Home Care Policy & Research at the Visiting Nurse Service of New York. His research focuses 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 motto is “Data for good.” Dr. Topaz is one of the pioneers in applying natural language processing to data generated by nurses. His work focuses 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 as a Fulbright Fellow at the University of Pennsylvania and completed a postdoctoral fellowship at the Harvard Medical School and Brigham Women's Hospital. He published more than 170 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 AMS Fellow in Compassion and Artificial Intelligence.  Dr. Ronquillo leads the Health Informatics Equity Lab at The University of British Columbia Okanagan School of Nursing. Her work aims to improve equity in BC’s healthcare with thoughtful and inclusive technologies. Dr. Ronquillo’s ongoing research aims to ensure the 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.

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 Associate Professor at the University of Florida College of Nursing with a joint appointment with the Department of Surgery, College of Medicine. At the UF, she is under the AI Health Initiative, a multicollegiate group of researchers harnessing AI in healthcare. 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 degree from the Federal University of Rio Grande do Sul, Brazil. She is a Fellow of the American Medical Informatics Association, the co-chair of the Nursing Knowledge Big Data Science Initiative, and co-founder and co-director of NAILCollab. She has extensive experience mentoring and providing guidance at the intersection of AI, data science, and mining EHR for holistic models. Dr. Pruinelli's research leverages innovative informatics tools and cutting-edge data science methods to investigate acute disease trajectories, specifically in transplantation. Her research mines 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 through biomedical informatics and advanced statistical modeling. Her list of publications can be found HERE. 

Martin Michalowski, PhD, FAMIA, FIAHSI, Dr. Michalowski is a School of Nursing Foundation Research Professor, a Co-Director of the Center for Nursing Informatics, and a Co-Leader of the Digital Health Lab at the University of Minnesota. He is also a co-leader of the Mobile Emergency Triage (MET) Research Group, an international research collaboration, and he serves as Co-Director of the Nursing and Artificial Intelligence Leadership Collaborative. His research portfolio includes novel contributions in information integration, record linkage, heuristic-based planning, constraint satisfaction problems, large language models, and leveraging artificial intelligence (AI) methods in nursing informatics research. His interdisciplinary research brings advanced AI methods and models to clinical decision support at the point of care and personalized medicine. Dr. Michalowski earned his Ph.D. in Computer Science from the University of Southern California, where he solved automated reasoning problems using AI. In 2018, he was elected Senior Member of the Association for the Advancement of Artificial Intelligence (AAAI); in 2021, he was named to the Fellows of the American Medical Informatics Association (FAMIA); in 2024, he was elected to the Academy Fellows of the International Academy of Health Sciences Informatics (IAHSI). He authored and co-authored over 100 peer-reviewed articles on a range of AI-related topics. Dr. Michalowski is the organizing chair of the International Workshop on Health Intelligence (W3PHIAI) held at the AAAI annual conference. He was co-chair of the 2020 International Conference on Artificial Intelligence in Medicine (AIME 2020) and served in the same role for AIME 2022. His research has received funding from the NSF, NIH, DARPA, DoD, and various private foundations. His work has resulted in two patents, various startup companies, and best paper awards at several top-tier health informatics and AI conferences.