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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