Title: Past, present, and future of computing and health: Perspectives from a ubicomp researcher

Dr. Gregory Abowd

Regents’ Professor and J.Z. Liang Chair
School of Interactive Computing
Georgia Institute of Technology

Abstract: In 2011, in front of the American Medical Informatics Association (AMIA), I made a bold prediction that by 2016 more clinically-relevant data would be collected in non-clinical settings.  My point was that mobile and ubiquitous technologies were poised to present an opportunity (and challenge) to those who were concerned about the electronic health record.  In 2019, after almost two decades of doing research that in one way or another overlaps the health domain, I want to step back and reflect on progress we have made, as computing professionals, impacting an important outside domain, health.  I will give some brief research highlights (and lowlights) from my own career as a way of framing the trajectory of computing and health research. I will also reflect on some trends I feel are relevant today in a world that has mostly realized Mark Weiser’s 30-year old vision of “ubiquitous” computing. I will end with a quick view into another technology shift that could impact computing and health research for many years to come.

Short Bio: Gregory D. Abowd is a Regents' Professor and J.Z. Liang Chair in the School of Interactive Computing at Georgia Tech, where he has been on the faculty since 1994. An applied computer scientist, Dr. Abowd's research interests concern how the advanced information technologies of mobile, wearable and ubiquitous computing impact our everyday lives when they are seamlessly integrated into our living spaces. Dr. Abowd's work has involved applications as diverse as education (Classroom 2000), home life (The Aware Home) and health (technology and autism, CampusLife). He and his current and former students are active inventors of new sensing and interaction technologies. He has recently helped to co-create an interdisciplinary research effort, COSMOS, which investigates the collaboration of researchers in materials, manufacturing, electronics, computing and design to explore an alternative future computing industry. Dr. Abowd is an ACM Fellow and a member of the ACM SIGCHI Academy.

Title: Metric Learning for Health Informatics

Dr. Aidong Zhang

William Wulf Faculty Fellow and Professor
Department of Computer Science
University of Virginia

Abstract: Measuring similarities or distances between pairs of samples is a basic but important step toward successes of many data mining and machine learning approaches, in particular, in healthcare data analysis. In this talk, I will discuss how both linear and nonlinear metric learning can be approached to capture various important relationships for complex healthcare data sets and how the learned metrics can be used for complex healthcare data analysis.

Short Bio: Dr. Aidong Zhang is a William Wulf Faculty Fellow and Professor of Computer Science in the School of Engineering and Applied Sciences at University of Virginia (UVA). She is also affiliated with Department of Biomedical Engineering and Data Science Institute at University of Virginia. Her research interests include data mining/data science, machine learning, bioinformatics, and health informatics. Dr. Zhang currently serves as the Editor-in-Chief of the IEEE Transactions on Computational Biology and Bioinformatics (TCBB). She served as the founding Chair of ACM Special Interest Group on Bioinformatics, Computational Biology and Biomedical Informatics during 2011-2015 and is currently the Chair of its advisory board. She is also the founding and steering chair of ACM international conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB). Dr. Zhang is a fellow of ACM and IEEE.

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