Keynote Speakers

Keynote Speakers (CSEE 2021)




Prof. Geoff Webb
IEEE Fellow
Monash University, Australia

 

Geoff Webb is Research Director of the Monash University Data Futures Institute. He is a data science consultant and a technical advisor to data science startups BigML and FROMMLE. He has been Editor in Chief of the premier data mining journal, Data Mining and Knowledge Discovery (2005 to 2014) and Program Committee Chair of the two leading data mining conferences, ACM SIGKDD (2015) and IEEE ICDM (2010), as well as General Chair of ICDM (2012). Many of his learning algorithms are included in the widely-used BigML, R and Weka machine learning workbenches. He is an IEEE Fellow and his many awards include the prestigious inaugural Eureka Prize for Excellence in Data Science (2017).

Speech Title: Time Series Classification at Scale

Abstract: Time series classification is a fundamental data science task, providing understanding of dynamic processes as they evolve over time. The recent introduction of ensemble techniques has revolutionised this field, greatly increasing accuracy, but at a cost of increasing already burdensome computational overheads. I present new time series classification technologies that achieve the same accuracy as recent state-of-the-art developments, but with many orders of magnitude greater efficiency and scalability. These make time series classification feasible at hitherto unattainable scale.

     



Prof. Hui Xiong
IEEE Fellow
Rutgers, the State University of New Jersey, USA

 

Dr. Hui Xiong is currently a Full Professor at the Rutgers, the State University of New Jersey. He also served as the Smart City Chief Scientist and the Deputy Dean of Baidu Research Institute in charge of several research labs (while on leave from Rutgers University). He received the Ph.D. degree from the University of Minnesota (UMN), USA. He is a co-Editor-in-Chief of Encyclopedia of GIS, an Associate Editor of IEEE Transactions on Big Data (TBD), ACM Transactions on Knowledge Discovery from Data (TKDD), and ACM Transactions on Management Information Systems (TMIS). Dr. Xiong has served as chair/co-chair for many international conferences in data mining, including a Program Co-Chair (2013) and a General Co-Chair (2015) for the IEEE International Conference on Data Mining (ICDM), and a Program Co-Chair of the Research Track (2018) and the Industry Track (2012) for the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD). Dr. Xiong’s research has generated substantive impact beyond academia. He is an ACM distinguished scientist and has been honored by the 2018 Ram Charan Management Practice Award as the Grand Prix winner from the Harvard Business Review, the 2017 IEEE ICDM Outstanding Service Award, and the ICDM-2011 Best Research Paper Award. In 2020, he was named as an AAAS Fellow and an IEEE Fellow.

Speech Title: Mobile Analytics: Prospects and Opportunities

Abstract: Advances in sensor, wireless communication, and information infrastructure such as GPS, WiFi, and mobile phone technology have enabled us to collect and process massive amounts of mobile data from multiple sources but under operational time. These big data have become a major driving force of new waves of productivity growth, application innovation, and consumer surplus. The big data are usually immense, fine-grained, diversified, dynamic, and sufficiently information-rich in nature, and thus demand a radical change in the philosophy of data analytics. In this talk, we discuss the technical and domain challenges of big data analytics in mobile environments. In particularly, it is especially important to investigate how the underlying computational models can be adapted for managing the uncertainties in relation to big data process in a huge nebulous environment. The theme to be covered will include AI enabled map services (e.g. multi-modal travel recommendation), context-aware POI recommendations, POI knowledge graph, and urban cognitive computing.