报告人：Mohamed Mokbel教授IEEE Fellow
报告时间：2022年3月24日(周四) 10:00 -11:30 am
报告形式：腾讯会议ID: 206 571 391
报告摘要：The need to manage and analyze spatial data is hampered by the lack of specialized systems to support such data. System builders mostly build general-purpose systems that are generic enough to handle any kind of attributes. Whenever there is a pressing need for spatial data support, it is considered as an afterthought problem that can be addressed by adding new data types, extensions, or spatial cartridges to existing systems. This talk advocates for dealing with spatial data as first class citizens, and for always thinking spatially whenever it comes to system design. This is well justified by the proliferation of location-based applications that are mainly relying on spatial data. The talk will go through various system designs and show how they would be different if designed while thinking spatially. Examples of these systems include big data systems, machine learning, recommender systems, and crowdsourcing.
Mohamed Mokbel (PhD, Purdue University, MS, BS, Alexandria University) is a Professor at the University of Minnesota. Prior roles while on leave/sabbatical from UMN include Chief Scientist of Qatar Computing Research Institute, Founding Technical Director of GIS Technology Innovation Center in Saudi Arabia, and multiple times Visiting Researcher at Microsoft Research, USA. His research interests include database systems, spatial data, and GIS. His research work has been recognized by the NSF CAREER Award, VLDB 10-years Best Paper Award, and four conference Best Paper Awards. Mohamed is the past elected Chair of ACM SIGSPATIAL, current Editor-in-Chief for Springer Distributed and Parallel Databases (DAPD) Journal, and on the editorial board of ACM Books, ACM TODS, VLDB Journal, ACM TSAS, and GeoInformatica journals. He has served as PC Co-Chair for ACM SIGMOD, ACM SIGSPATIAL, and IEEE MDM. Mohamed is an IEEE Fellow and ACM Distinguished Scientist. For more information, please visit: www.cs.umn.edu/~mokbel