Jianying Hu
Distinguished Research Staff Member
and Program Director of Center for Computational Health
IBM T. J. Watson Research Center

"Data Driven Healthcare Analytics"

Wednesday, May 3, 4:00 PM
Packard Lab room 466

Co-sponsored by the Healthcare Systems Engineering Program

Abstract:   The concept of Learning Health Systems (LHS) is gaining momentum as more and more electronic health data has become increasingly accessible. The core idea is to enable learning from the collective experience of a health eco-system as recorded in the observational data, to iteratively improve care quality as care is being provided in a real world setting. In line with this vision, the Center for Computational Health at IBM T.J. Watson Research Center has been developing machine learning, data mining and computer visualization methodologies that can be used to derive insights from diverse sources of healthcare data to provide personalized decision support for care delivery and care management, real world evidence, and precision medicine. Some of the methodologies developed in this effort have already led to foundational technologies in the solutions being rolled out by the newly formed IBM Watson Health business unit. In this talk I will give an overview of a wide range of analytics methodologies we have developed and their use cases, and describe some new directions we are taking.

Bio:  Jianying Hu is a Distinguished Research Staff Member and Program Director of Center for Computational Health at IBM T. J. Watson Research Center, NY. Prior to joining IBM in 2003 she was with Bell Labs at Murray Hill, New Jersey. Dr. Hu received the Ph.D. degree in Computer Science from SUNY Stony Brook in 1993. Her main research interests include machine learning, data mining, statistical pattern recognition, and signal processing, with applications to healthcare analytics, medical informatics, business analytics, document analysis, and multimedia content analysis. For the past six years her group has been focusing on developing advanced machine learning, data mining and visual analytics methodologies for deriving data-driven insights to facilitate “learning health systems”. Dr. Hu has published over 100 technical articles and holds 27 patents. She has served as associate editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Pattern Recognition and International Journal for Document Analysis and Recognition. Dr. Hu is a fellow of IEEE (class of 2015), a fellow of the International Association of Pattern Recognition (class of 2010), and a recipient of the Asian American Engineer of the Year Award (class of 2013).

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