Analytics Track Keynote

Aidong Zhang

Explainable Deep Tabular Learning Models for Biomedical and Healthcare Applications

Dr. Aidong Zhang

University of Virginia

Professor of Computer Science, Biomedical Engineering, and Data Science

Dr. Aidong Zhang is a Professor of Computer Science, Data Science, and Biomedical Engineering at University of Virginia (UVA). Prof. Zhang’s research interests include machine learning, data science, bioinformatics and computational biology, and health informatics. Prof. Zhang was the Editor-in-Chief of the IEEE Transactions on Computational Biology and Bioinformatics (TCBB) from 2017 to 2021. She served as the founding Chair of ACM Special Interest Group on Bioinformatics and Computational Biology (SIGBio) from 2011 to 2015 and also served as the Chair of its advisory board from 2015 to 2018. She was also the founding and steering chair of ACM international conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) from 2010 to 2019. Prof. Zhang is a fellow of ACM and IEEE. She is also a fellow of the American Institute for Medical and Biological Engineering (AIMBE).

System Track Keynote

Patricia C. Dykes

Challenges and Opportunities for Improving Patient Safety Through Data Science and Informatics

Dr. Patricia C. Dykes

Harvard Medical School

Program Director Research, Center for Patient Safety, Research, and Practice, Brigham and Women’s Hospital, Associate Professor of Medicine

Patricia Dykes is Associate Professor of Medicine at Harvard Medical School and Research Program Director for the Center for Patient Safety, Research and Practice at Brigham and Women’s Hospital in Boston. Her research aims to improve quality and safety through patient engagement and clinical decision support (CDS). Dr. Dykes is currently leading patient safety informatics clinical trials to improve fall prevention and care transitions in primary care for patients with multiple chronic illness. She is also leading development of CDS and an electronic clinical quality measure to prevent and quantify delayed diagnosis of venous thromboembolism. In addition, Dr. Dykes is the site PI for the CONCERN study which uses data science and machine learning approaches to identify hospitalized patients at risk for deterioration. Dr. Dykes is author of 2 books, over 175 peer reviewed publications, and has presented her work nationally and internationally. She is immediate past President and Board Chair of the American Medical Informatics Association, an elected fellow of American Academy of Nursing, the American College of Medical Informatics, and the International Academy of Health Sciences Informatics.

Industry Track Keynote

Ed Nykaza

Data and System Harmonization: Reflections and observations from 25 years of research in disparate fields

Dr. Ed Nykaza

Ed Nykaza, PhD, is Glooko’s VP, Data Science & Clinical Research. His 25-year research career spans the academic, government, non-profit, do-it-yourself (DIY) and industry sectors, including 100+ presentations and 35 published papers. Ed is passionate about building and leading high-performance teams, creating psychologically safe working environments, and using data and science to improve the quality of people’s lives.