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                            A Navigational Approach to Health: Actionable Guidance for Improved Quality of Life
                            2019-07-09 | 【 【打印】【關閉】



                              報告人:Ramesh Jain 教授, University of California, Irvine


                              Health and well-being are shaped by how lifestyle and the environment interact with biological machines. A navigational paradigm can help users reach a specific health goal by using constantly captured measurements to estimate how their health is continuously changing and provide actionable guidance. Norbert Weiner said “To live effectively is to live with adequate information.” Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geo-spatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. And, in this talk, a navigational approach to Health will be discussed to improve quality of life with multi-source data from daily life.


                              Ramesh has been an active researcher in Computer Vision, Artificial Intelligence, Multimedia Computing, Experiential computing, and Digital Health. While at the University of Michigan, Ann Arbor, he founded and directed artificial intelligence laboratory in 1987; and at University of California, San Diego, he founded visual computing lab in 1995. At University of California, Irvine, He is founding director of UCI Institute for Future Health. He was also the founding Editor-in-Chief of IEEE MultiMedia magazine and Machine Vision and Applications journal. His co-authored and co-edited books include two text books: Machine Vision (published in 1995), and Multimedia Computing (published in 2014). Ramesh has been elected Fellow of ACM, IEEE, AAAS, IAPR, AAAI, and SPIE. He is the recipient of several awards including the ACM SIGMM Technical Achievement Award 2010. His current research is in building computing and data-driven approaches for Future Health.

                              Ramesh co-founded multiple companies (Imageware, Virage, Praja, Seraja, mChron, and Krumbs), managed them in initial stages, and then turned them over to professional management. He enjoys working with companies, is involved in research, and enjoys writing.

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