Data Science and Analytics Thrust Seminar | Efficient and Effective Spatial/Graph Data Management and Analytics
Supporting the below United Nations Sustainable Development Goals:支持以下聯合國可持續發展目標：支持以下联合国可持续发展目标：
With the booming of internet and mobile technologies, the spatial and graph data are prevalent in various areas, such as social media, knowledge bases, e-commerce platforms. The spatial data are able to model the spatial locations of entities in location-based services (e.g., Google Maps) and geo-social networks (e.g., Flickr and Foursqure). The graph data are used to model the complex connectedness among entities in the social networks, communication networks, collaboration networks, biological networks, transportation networks, etc. What’s more, in many real-world applications, such as recommendations of POIs, trip planning, location-based viral marketing, and community discovery, the graph data and spatial data are often used jointly to model the activities among them. Driven by these applications, my research aims to provide efficient and effective solutions to spatial/graph data management and analytics, including scalable data management algorithms and novel data analytics models.
Dr. Xin Cao is senior lecturer (equivalent to a tenured position in the North American system) in the School of Computer Science and Engineering at The University of New South Wales (UNSW) in Australia. He is also an ARC DECRA (Discovery Early Career Researcher Award) Fellow currently (awarded in 2018). He obtained his PhD degree in 2014 from the School of Computer Science and Engineering at Nanyang Technological University, Singapore. Before joining UNSW, he worked as a lecturer in the School of Electronics, Electrical Engineering and Computer Science at Queen's University Belfast from 2014 to 2016. His research interests include big data management, databases, data analytics, and artificial intelligence (especially on spatial, textual, and graph data). He has published more than 50 research papers, and most of them are published in top-tier conferences and journals, such as SIGMOD, PVLDB, ICDE, IJCAI, NeurIPS, SIGIR, VLDBJ, TKDE, TOIS, and TODS. He has been a program committee member of several top conferences (such as SIGMOD, PVLDB, ICDE, AAAI, IJCAI, WWW, SIGIR, and KDD) and served as a reviewer for several top journals (such as TKDE, VLDBJ, TOIS, TODS, and TNNLS).