Prof. Geoff Webb
IEEE Fellow

Monash University, Australia

Geoff Webb is a leading data scientist. He is Research Director of the Monash University Data Futures Institute and a Technical Advisor to data science startups FROOMLE and BigML Inc. The latter have incorporated his best of class association discovery software, Magnum Opus, as a core component of their advanced Machine Learning service. He developed many of the key mechanisms of support-confidence association discovery in the late 1980s. His OPUS search algorithm remains the state-of-the-art in rule search. He pioneered multiple research areas as diverse as black-box user modelling, interactive data analytics and statistically-sound pattern discovery. He has developed many useful machine learning algorithms that are widely deployed. He has applied machine learning in a broad range of applications including manufacturing, finance, medicine, biology and geoscience. He was editor in chief of the premier data mining journal, Data Mining and Knowledge Discovery from 2005 to 2014. He has been Program Committee Chair of the two top data mining conferences, ACM SIGKDD and IEEE ICDM, as well as General Chair of ICDM. He is an IEEE Fellow. His many awards include the prestigious inaugural Australian Museum Eureka Prize for Excellence in Data Science. His 250+ academic papers have received over 14,000 citations with an h-index of 60. Seven of his recent papers have been recognised as Clarivate Web of Science High Cite papers (top 1% of citations for the discipline).

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Prof. Lei Chen
IEEE Fellow

The Hong Kong University of Science and Technology, Hong Kong, China

Lei Chen has BS degree in computer science and engineering from Tianjin University, Tianjin, China, MA degree from Asian Institute of Technology, Bangkok, Thailand, and PhD in computer science from the University of Waterloo, Canada. He is a professor in the Department of Computer Science and Engineering, Hong Kong University of Science and Technology (HKUST). Currently, Prof. Chen serves as the director of Big Data Institute at HKUST, director of Master of Science on Big Data Technology and director of HKUST MOE/MSRA Information Technology Key Laboratory. Prof. Chen’s research interests include human-powered machine learning, crowdsourcing, Blockchain, graph data analysis, probabilistic and uncertain databases and time seires and multimedia databases. Prof. Chen got the SIGMOD Test-of-Time Award in 2015.The system developed by Prof. Chen’s team won the excellent demonstration award in VLDB 2014. Prof. Chen has served as VLDB 2019 PC Co-chair. Currently, Prof. Chen serves as Editor-in-Chief of VLDB Journal, associate editor-in-chief of IEEE Transaction on Data and Knowledge Engineering. He is an IEEE Fellow, ACM Distinguished Member and an executive member of the VLDB endowment.

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Prof. Ling Liu
IEEE Fellow

Georgia Institute of Technology, USA

Ling Liu is a Professor in the School of Computer Science at Georgia Institute of Technology. She directs the research programs in the Distributed Data Intensive Systems Lab (DiSL), examining various aspects of large scale big data-powered artificial intelligence (AI) systems, and machine learning (ML) algorithms and analytics, including performance, availability, privacy, security and trust. Prof. Liu is an elected IEEE Fellow, a recipient of IEEE Computer Society Technical Achievement Award (2012), and a recipient of the best paper award from numerous top venues, including IEEE ICDCS, WWW, ACM/IEEE CCGrid, IEEE Cloud, IEEE ICWS. Prof. Liu served on editorial board of over a dozen international journals, including the editor in chief of IEEE Transactions on Service Computing (2013-2016) and currently, the editor in chief of ACM Transactions on Internet Computing (TOIT). Prof. Liu is a frequent keynote speaker in top-tier venues in Big Data, AI and ML systems and applications, Cloud Computing, Services Computing, Privacy, Security and Trust. Her current research is primarily supported by USA National Science Foundation under CISE programs and IBM.

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