2025 Invited Speakers

Keynote Speakers
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Prof. Philippe Cudre Maoux

University of Fribourg

Full Professor, Department of Informatics, University of Fribourg; Head of eXascale Infolab.

Philippe Cudre-Mauroux is a Full Professor and the Director of the eXascale Infolab at the University of Fribourg in Switzerland. He received his Ph.D. from the Swiss Federal Institute of Technology EPFL, where he won both the Doctorate Award and the EPFL Press Mention in 2007. Before joining the University of Fribourg, he worked on information management infrastructures at IBM Watson (NY), Microsoft Research Asia and Silicon Valley, and MIT. He recently won the Verisign Internet Infrastructures Award, a Swiss National Center in Research award, a Google Faculty Research Award, as well as a 2 million Euro grant from the European Research Council. His research interests are in next-generation, Big Data management infrastructures for non-relational data and AI.

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Prof. John W Paisley

Columbia University

Associate Professor of Electrical Engineering, Dept of Electrical Engineering

John Paisley is an Assistant Professor in the Department of Electrical Engineering at Columbia University. John is also an affiliated member of the Data Science Institute at Columbia.
John received his Ph.D. in Electrical and Computer Engineering from Duke University, where he worked with Lawrence Carin. He was then a post-doc in the Computer Science departments at Princeton University with David Blei and UC Berkeley with Michael Jordan.
John’s research is in the general area of statistical machine learning. His interests include probabilistic modeling and inference techniques, Bayesian nonparametric methods, dictionary learning and topic modeling.

Guest Speakers
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Prof. Leye Wang

Peking University

Assistant Professor, Institute of Software, School of Computer Science,  Peking University

Leye Wang is an assistant professor at Key Lab of High Confidence Software Technologies, School of Computer Science, Peking University, China. His research interests include ubiquitous computing, mobile crowdsensing, and urban computing. Wang received a Ph.D. in computer science from the Institut Telecom SudParis and University Paris 6, France, in 2016, and was a postdoc researcher with Hong Kong University of Science and Technology. He has published 50+ papers and received 1500+ citations according to Google Scholar.
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Prof. Longbiao CHEN

Xiamen Univeristy
Associate Professor, Xiamen University Department of Computer Science, School of Informatics Fujian Key Laboratory of Sensing and Computing for Smart City
Longbiao CHEN is an associate professor with Department of Computer Science, Xiamen University, China. He obtained his Ph.D. degree in computer science from Sorbonne University, France in 2018 and Zhejiang University, China in 2016, respectively. Before joining Xiamen University, he worked as a research assistant in Institut Mines-Télécom, France. His research interests include Ubiquitous Computing, Mobile Crowdsensing, Urban Computing, and Big Data Analytics. Dr. Chen has published over 50 papers in top-tier journals and conferences, including ACM UbiComp, IEEE Trans. Mobile Computing, and IEEE Trans. Intelligent Transportation Systems. He received two UbiComp Honorable Mention Awards in 2015 and 2016, respectively. He is a senior member of China Computer Federation (CCF), technical committee member of ACM SIGSPATIAL China Chapter and CCF Ubiquitous Computing Committee. He serves as the PC members of several conferences including IJCAI and UIC.
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Prof. Defu LIAN

University of Science and Technology of China

Professor, Ph.D advisor
School of Data Science, School of Computer Science and Technology,
University of Science and Technology of China

Defu Lian is a professor from University of Science and Technology of China. His main research interest lies in data mining and deep learning. He has published more than 160 papers at prestigious conferences and journals, and received a best paper runner-up in APWeb 2016, best paper candidate in WWW 2021 and best paper award in WISE 2022. He developed a highly-modularized recommender system (RecStudio) and a learned vector retrieval library (LibVQ). He received the National Science Fund for Excellent Young Scholars.

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Prof. Mengzhou Zhuang

The University of Hong Kong

Assistant professor of Marketing at the University of Hong Kong

Mengzhou (Austin) Zhuang joined the University of Hong Kong in 2019, after receiving his Ph.D. in Business Administration (Marketing) from University of Illinois, Urbana-Champaign. Before that he received his M.Phil. in Marketing from Lingnan University, and Bachelor degrees in Business Administration from Xi’an Jiaotong University. His research interests lie in online advertising and multi-channel marketing strategy. His work primarily focuses on understanding the strategic decisions of multi-channel retailers, online advertisers, retailing platforms, and consumers.
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Mr. Paul Boniol

Inria
Researcher at Inria, Member of the VALDA project-team, a joint team between Inria Paris, École Normale Supérieure, and CNRS.
I am a researcher at Inria, member of the VALDA project-team, which is a joint team between Inria Paris, École Normale Supérieure, and CNRS. Before that, I was a Postdoctoral researcher at Ecole Normale Supérieure (ENS) Paris Saclay (Centre Borelli) in the team of Prof. Laurent Oudre. I completed my Ph.D. at the University of Paris and EDF R&D, working with Prof. Themis Palpanas, Emmanuel Remy, and Mohammed Meftah. During my Ph.D., I did an internship at the University of Chicago under the supervision of Prof. Michael J. Franklin and Prof. John Paparrizos. Before starting my Ph.D., I worked as a research engineer at the computer science lab of Ecole Polytechnique in Prof. Michalis Vazirgiannis’s team. My research interest lies in the intersections between: Massive time series analytics and management systems. Unsupervised and supervised anomaly detection methods for large time series. Machine learning for time series analytics.
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Prof. Tsz Nam Chan

Shenzhen University
Distinguished Professor, College of Computer Science and Software Engineering, Shenzhen University
Tsz Nam Chan (Edison) is currently a Distinguished Professor in the database group of the Big Data Institute in Shenzhen University (SZU). He is a data engineering researcher (for handling the efficiency issues in big data settings). He published several research papers in prestigious conferences and journals (CCF: A, CSRankings, and top ranking in Google scholar) in both database (data engineering) and data mining areas, including SIGMOD, VLDB, ICDE, SIGKDD, and TKDE. Prior to joining the SZU, he was a Research Assistant Professor in the Hong Kong Baptist University from Sep 2020 to Aug 2023 and a postdoctoral researcher in The University of Hong Kong from Sep 2018 to Aug 2020. He received the PhD degree in computing and the BEng degree in electronic and information engineering from The Hong Kong Polytechnic University in 2019 and 2014, respectively. He is an IEEE senior member and an ACM member.
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