2018第三届应用数学与数据科学国际会议
2018年5月29-31日 中国·杭州
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截止日期:2018年1月20日
(延期至 2018年4月20日) - 录用通知: 投稿后20-40天
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- 会议日期: 2018年5月29-31日
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ICAMDS2018演讲嘉宾信息如下:
Biography: Dr. Hui Zhang is an Assistant Professor of Computer Engineering and Computer Science at the University of Louisville, KY. Dr. Zhang has over 15 years of experience in the fields of scientific visualization, medical and dental simulation, and big data computing. His visualization research adopts a combination of computer-generated three-dimensional images and haptic/tactile devices, and has extensive practical uses in medical field such as surgical training scenarios using virtual manipulatives with a crucial sense of 3D touch, and haptic interfaces to help children with motor control disorders to improve motor skills. His research has been funded by NIH R21, NSF CAREER, NSF DUE, and Oak Ridge National Laboratory. Dr. Zhang has over 40 peer-reviewed publications, 2 book chapters, and some of his work has been featured articles in SPIE newsroom.
Topic: Large-scale Scientific Investigation with Visual Informatics and Advanced Computing
Abstract: We are generating digital data routinely from many areas of science and engineering in unprecedented scales and details. Unlike a traditional task, a large-scale scientific investigation calls for new techniques and tools to create images to communicate the essential information inherent in these large and complex data, and this often requires quantitative analyses and computing at different scales. If appropriately designed, visually based information can be used to effectively direct the overall large-scale analysis process. In this seminar I will discuss how I, along with my collaborators, have been marrying what we loosely term 'visual informatics', including visualization methods and interactive techniques, etc., with advanced computing. I will discuss two case studies, one for large-scale dental computing and the other one for the visualization of high-dimensional geometric data, to show how visual informatics and scalable computing are coupled and can work hand in hand for large-scale scientific investigations. Finally, I will discuss my vision for the evolution of these techniques into a framework deployed on cyber-infrastructure for the alliance of domain knowledge from human experts and computing powers of machines, to empower the future of scientific investigations.
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