• Working Hrs

    Mon-Fri: 10am to 6pm
  • Address

    Harbin, China

Keynote Speakers

Prof. Xiaofang Zhou
University of Queensland, Australia
IEEE Fellow

Professor Xiaofang Zhou is a Professor of Computer Science at The University of Queensland, leading the Data Science discipline at UQ. His research focus is to find effective and efficient solutions for managing, integrating and analyzing very large amount of complex data for business, scientific and personal applications. He has been working in the area of spatial and multimedia databases, data quality, high performance database systems, data mining, streaming data analytics and recommendation systems. He is a Program Committee Chair for PVLDB 2020, SSTD 2017, CIKM 2016, ICDE 2013, and a General Chair of MDM 2018 and ACM Multimedia 2015. He has been an Associate Editor of The VLDB Journal, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Cloud Computing, World Wide Web Journal, Distributed and Parallel Databases, and IEEE Data Engineering Bulletin. He was the Chair of IEEE Technical Committee on Data Engineering (2015-2018), and a Fellow of IEEE.

​Prof. Hayato YAMANA
Waseda University, Japan

Hayato YAMANA received his Dr. Eng. degree at Waseda University in 1993. He began his career at the Electrotechnical Laboratory (ETL) of the former Ministry of International Trade and Industry (MITI), and was seconded to MITI's Machinery and Information Industries Bureau for a year in 1996. He was subsequently appointed Associate Professor of Computer Science at Waseda University in 2000, and has been a professor since 2005. From 2003 to 2004, he was IEEE Computer Society Japan Chapter Chair. Since 2015, he has been director of IPSJ (Information Processing Society of Japan) and vice chairman of information and communication society of IEICE (the institute of electronics, information and communication engineers). At Waseda University, he has been deputy Deputy Chief Information Officer and WasedaX project director since 2015. His research area is big data analysis. Currently, his group engages in Japanese government funded project called “Secure Data Sharing and Distribution Platform for Integrated Big Data Utilization - Handling all data with encryption.” For more information, please refer to http://www.yama.info.waseda.ac.jp/crest/.

Prof. Adrian Hopgood
University of Porstmouth, UK

Adrian Hopgood is Full Professor of Intelligent Systems and Director of Future & Emerging Technologies at the University of Portsmouth in the UK. He is also a visiting professor at the Open University and at Sheffield Hallam University. He is a Chartered Engineer, Fellow of the BCS (the Chartered Institute for IT), and a committee member for the BCS Specialist Group on Artificial Intelligence. Professor Hopgood has extensive experience in both academia and industry. He has worked at the level of Dean and Pro Vice-Chancellor in four universities in the UK and overseas, and has enjoyed scientific roles with Systems Designers (now part of Hewlett-Packard) and the Telstra Research Laboratories in Australia. His main research interests are in artificial intelligence and its practical applications. He has supervised 19 PhD projects to completion and published more than 100 research articles. His text book "Intelligent Systems for Engineers and Scientists” has been published in three editions and is ranked as a bestseller.

Prof. Christophe Claramunt
Shanghai Maritime University (China) & Naval Academy Research Institute (France)

Professor Christophe Claramunt is currently the chair of the Naval Academy Research Institute in France. He was previously a senior lecturer in computing at the Nottingham Trent University and senior researcher at the Swiss Federal Institute of Technology in Lausanne. His research is oriented towards theoretical, computational and pluri-disciplinary aspects of geographical information systems. Over the past few years he has been regularly involved in EU funded projects such as the H2020 project datAcron "Big Data Analytics for Time Critical Mobility Forecasting". Amongst other affiliations, he is a research fellow at the Research Center for Social Informatics of the Kwansei University in Japan, Centre for Planning Studies at the Laval University, the Laboratory for Geographical Information Science at the Chinese University of Hong Kong and the Logistics Engineering Department at the Shanghai Maritime University.

Dr. Max Hoffmann
RWTH Aachen University, Germany

Dr. Max Hoffmann is a scientific researcher with the Institute of Information Management in Mechanical Engineering at the RWTH Aachen University since 2012. In the years from 2012 to 2017 he focused on the consulting of various industrial partners as part of the research group “Production Technology” as well as on his Ph.D. thesis (Dr.-Ing.). Since 2016, Max Hoffmann is Research Group Leader of the “Industrial Big Data” group, which focuses on the requirement of modern manufacturing with regard to the digitization. Prior to his engagement with the institute Max Hoffmann has studied Mechanical Engineering with emphasis on Process Engineering at the RWTH Aachen University until 2010. Parallel to his first consultancy activities in IT he acquired an additional degree in general economic science in 2012 by achieving a Master of Business Administration (MBA). In the context of his doctorate activities as well as in terms of his current research, Max Hoffmann is focusing on topics related to the digitization in the manufacturing industries. The covers the information technological process chain from the acquisition of data in the field by making use of semantic interface and IoT technologies (OPC UA, MQTT, …), the integration of information using highly scalable technologies (Big Data) as well as the creation of valuable insights for the production process by means of data-driven approaches (Machine Learning). A distinctive focus of the Industrial Big Data group hereby consists in the research novel concepts for processing and storage of huge data sets by making use of “Data Lake” approaches. These concepts allow for a holistic usage of data from the field together with information from higher systems of production planning and control (ERP, MES, …). Current research activities of Max Hoffmann besides topics related to the “Industrial Big Data” also cover fields such as semantic technologies, ontologies and the application of (Industrial) Internet of Things technologies in the production context. Additional research activities focus on multi-agent system technologies in manufacturing. In this context, Max Hoffmann is part of the expert group “Agent systems in automation technology”, member of the technical committee “Agent systems” of the VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik (GMA) as well as author of the standard of the working group.

Prof. Xin-She Yang
Middlesex University, UK

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and National Physical Laboratory (UK) as a Senior Research Scientist. Now he is Reader in Modelling and Optimization at Middlesex University, an elected Bye-Fellow at Cambridge University and Adjunct Professor at Reykjavik University (Iceland). He is the Chair of the IEEE CIS Task Force on Business Intelligence and Knowledge Management. He has given many keynote talks at over 20 international conferences such as IEEE Mendel'12 (Czech Republic), BIOMA'12 (Slovenia), EU/ME'14 (Turkey), ICCS'15 (Iceland), SIBGRAPI'15 (Brazil), OIPE'16 (Italy), ISCBI'16 (Switzerland), BDIOT'17 (UK) and HS'17 (Spain). He has published more than 250 articles in peer-reviewed journals and 20 books with over 32000 citations. He has been on the prestigious list of Clarivate Analytics/Web of Science Highly Cited Researchers in 2016, 2017 and 2018.

Prof. Paolo Terenziani
University of Piemonte Orientale, Italy

Since 2000, Paolo Terenziani is Full Professor at the Institute of Computer Science of DISIT, Università del Piemonte Orientale, Alessandria, Italy. The research activity of Paolo Terenziani has begun in 1987 and it concerns mainly the field of Artificial Intelligence, and specifically the areas of knowledge representation and automatic reasoning (with particular attention to representation and reasoning with temporal constraints), the fields of Temporal Databases and of Medical Informatics. Regarding these topics Paolo Terenziani has published more than 150 papers in peer-reviewed international journals, books, conference proceedings and workshops (in particular, he has achieved ten publications on the IEEE Transactions of Knowledge and Data Engineering in the last five years). Since 1997, Paolo Terenziani leads the GLARE project, in collaboration with the hospital San Giovanni Battista in Turin, for developing a prototype of a domain-independent software system for the acquisition, representation and execution of clinical guidelines. Since 2015 Paolo Terenziani is in the board of AIME (Artificial Intelligence in Medicine Europe). As early as in 1998, for his research activity, he won the “Artificial Intelligence Prize” from Italian Association for Artificial Intelligence. He has won “distinguished\best” paper awards in several international conferences, including AMIA 2012, Chicago, USA, November 2012 (more than 1000 submissions).

Prof. John MacIntyre
University of Sunderland, UK

I have worked at the University of Sunderland since 1992, having graduated from the University with a First Class Honours Degree in Combined Science (Computer Science and Physiology). I then went on to complete a PhD in applied artificial intelligence, focussing on the use of neural networks in predictive maintenance, which was awarded in 1996. During the 1990s I established a research centre – the Centre for Adaptive Systems – at the University, which became recognised by the UK government as a Centre of Excellence for applied research in adaptive computing and artificial intelligence. The Centre undertook many projects working with and for external organisations in industry, science and academia, and for three years ran the Smart Software for Decision Makers programme on behalf of the Department of Trade and Industry. I have successfully supervised in PhDs in fields ranging from neural networks, hybrid systems, and bioinformatics through to lean manufacturing, predictive maintenance, and business and maintenance strategies. I went on to become Associate Dean, and then Dean, of the School of Computing and Technology, covering Computer Science and Engineering; in 2008 I became the Dean of the Faculty of Applied Science, and in 2010 Pro Vice Chancellor of the University. I am, and have, been a member of many regional, national and international organisations linked to my own research or professional areas, or on behalf of the University. Since 1996 I have been the Editor-in-Chief of Neural Computing & Applications, an international scientific peer reviewed journal published by Springer Verlag. Prior to entering academia I worked in industry including several years working overseas on major civil and structural engineering projects, developing and implementing new computerised planning systems.

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