Keynote speakers


Prof. Lei Chen

HKUST, China

Professor
Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay, Kowloon, Hong Kong

Lei Chen received his BS degree in Computer Science at Tian Jin University, P.R.China(BS 94), and an MA degree in computer science at Asian Institute of Technology (AIT) Asian Institute of Technology (MS 97). He received a Ph.D. degree in Computer Science at University of Waterloo. Lie Chen research intenrests are: Data-Driven Machine Learning, Crowdsourcing-based Data Processing, Uncertain and Probabilistic databases, Web data management, Multimedia and Time series databases, Privacy.

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Prof. Jie LU

UTS, Australia

Associate Dean (Research Excellence) and Dist. Prof., University of Technology Sydney, Faculty of Engineering & Information Technology

Distinguished Professor Jie Lu is the Associate Dean (Research Excellence) in the Faculty of Engineering and Information Technology (FEIT). She is also the Director of Center for Artificial Intelligence (CAI.UTS). She was the Head of School of Software and the Director of Decision Systems & e-Service Intelligence (DeSI) lab in the FEIT. Her main research interests lie in the area of data-driven prediction and decision support systems, recommender systems, concept drift detection, fuzzy information processing and fuzzy transfer learning.

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Prof. Beng Chin Ooi

NUS, Singapore

Chair Professor
Department of Computer Science School of Computing National University of Singapore

Beng Chin is a Distinguished Professor of Computer Science, NGS faculty member and Director of Smart Systems Institute (SSI@NUS) at the National University of Singapore (NUS), and an adjunct Chang Jiang Professor at Zhejiang University, China. He obtained his BSc (1st Class Honors) and PhD from Monash University, Australia, in 1985 and 1989 respectively. He is a co-founder of yzBigData in 2012 for Big Data Management and analytics, and Shentilium Technologies in 2016 for AI- and data-driven Financial data analytics, and an advisory council member of a Fintech company, Cynopsis Solutions. Bneg Chin's research interests include database, distributed processing, machine learning and large scale analytics, in the aspects of system architectures, performance issues, security, accuracy and correctness. He is also interested in exploiting IT in production and process reengineering.

Abstract:

Modern Internet applications often produce a large volume of user activity records. Data analysts are interested in cohort analysis, or finding unusual user behavioral trends, in these large tables of activity records, as a means to improve sales and acquire new customers. In a traditional database system, cohort analysis queries are both painful to specify and expensive to evaluate. In this talk, I first present the extension of database systems to support cohort analysis. We do so by extending SQL with new operators and devise different evaluation schemes for cohort query processing. I then present our very efficient new columnar based system called COHANA. I will also discuss an experimental evaluation against the non-intrusive approaches on existing systems, and show a demo.

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