High-Performance Heterogeneous Data Processing for AI Applications

Speaker:

Professor X. Sean Wang

Fudan University

The Title of Speech: High-Performance Heterogeneous Data Processing for AI Applications

Abstract of Speech:

At the current stage of its development, Artificial Intelligence mostly is via methods that seek knowledge from data, which often requires massive computing resources to process massive amounts of heterogenous data in order to gain useful knowledge that can be applied automatically in various scenarios. Due to the large differences in modes of computation between the various steps of data processing, high-performance data processing needs to handle heterogeneous hardware and software platforms. Some changes are needed regarding the software stack of the data processing system to achieve the goal of high performance. This talk is to outline some research towards this goal, and to present some relevant results.

Biography of the Speaker:

Xiaoyang Sean Wang is Professor at the School of Compute Science, Fudan University, Shanghai, China. He received his PhD degree in Computer Science from the University of Southern California, USA. Before joining Fudan University in 2011, he held the Dorothean Chair Professor in Computer Science position at the University of Vermont, USA, and served as a Program Director at the National Science Foundation, USA, in the IIS division. His research has been supported by NSF and NSFC, as well as other US and Chinese funding agencies. He has published widely in the general area of databases and information security, and was a recipient of the US National Science Foundation CAREER award. He served as the general chair of IEEE ICDE 2011 held in Washington DC and ACM CIKM 2014 in Shanghai, China, and in various other roles for international conferences and journals. He’s currently Editor in Chief of the Springer Journal of Data Science and Engineering, associate editor of IEEE TCC, and past associate editor of IEEE TKDE. He’s also currently on the steering committees of the IEEE ICDE and IEEE BigComp conference series, and past Chair of WAIM (now merged into ApWeb-WAIM) Steering Committee.