題 目：Intelligent Data Visual Analytics
内容簡介：The advance in computing technology allows applications and simulations to produce a tremendous amount of data that should be shared, managed and analyzed in an effective and timely manner. However, the enormous growth in the size and complexity of data places a big challenge for the data analytics work done by geographically distributed groups of people. Developing an integrated, scalable, easily accessible, and intelligent solution in a distributed or online environment has become a critical research focus in many fields.
In this talk, Dr. Gao will highlight some of her work in intelligent data visual analytics. This will include her previous work on scalable data management, analysis, and visualization in distributed environments as well as her ongoing efforts in virtual reality enhanced data analysis, video information analysis for mobile health, finance data analysis, and visual predictive analysis for industries.
報告人：美國加州太平洋大學(University of the Pacific) 高勁竹 教授
報告人簡介：Prof. Jinzhu Gao received her Ph.D. degree in Computer Science from the Ohio State University in 2004. From June 2004 to August 2008, she worked at the Oak Ridge National Laboratory as a research associate and then the University of Minnesota, Morris, as an Assistant Professor of Computer Science. She joined the University of the Pacific (Pacific) in 2008 and is currently a Professor of Computer Science there. Her main research focus is on intelligent data visual analytics. Over the past fifteen years, Prof. Gao has been working closely with application scientists and Silicon Valley technology companies to develop online data visual analytics and deep learning platforms to support collaborative science, mobile health, IoT data analytics, business operational visibility, and visual predicative analysis for industries. Her work has been published in top journals such as IEEE Transactions on Visualization and Computer Graphics, IEEE Transactions on Computers, and IEEE Computer Graphics and Applications.
時 間：2019年7月18日（星期四）10：00
地 點：校本部南海樓727室
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2019年7月17日