Keynote Speaker of ICCBDC 2019


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Keynote Speakers of ICCBDC 2018

Prof. Dr. Hong Zhu, Oxford Brookes University, United Kingdom

Hong Zhu obtained his BSc, MSc and PhD degrees in Computer Science from Nanjing University, China, in 1982, 1984 and 1987, respectively. He worked at Nanjing University 1987 to November 1998. From October 1990 to December 1994 while on leave from Nanjing University, he was a research fellow at Brunel University and the Open University, UK. He joined Oxford Brookes University, UK, in November 1998 as a Senior Lecturer in Computing and became a Professor of Computer Science in October 2004. Prof. Zhu chairs the Applied Formal Methods Research Group of the Department of Computing and Communication Technologies. He is a senior member of IEEE Computer Society, a member of British Computer Society, ACM, and China Computer Federation. His research interests are in the area of software development methodologies, including formal methods, agent-orientation, automated software development, foundation of software engineering, software design, modelling and testing methods, Software-as-a-Service, etc. He has published 2 books and more than 180 research papers in journals and international conferences. He has been a conference program committee chair of SOSE 2012 and ICWS 2015, etc., a conference general chair of SOSE 2013, MobileCloud 2014, MS 2016, EDGE 2017, etc. He is a member of the editorial board of the journal of Software Testing, Verification and Reliability, Software Quality Journal, International Journal of Big Data Intelligence, and the International Journal of Multi-Agent and Grid Systems.
Speech Title: Formally Analyzing Emergent Properties of Microservices with Scenario Calculus
Abstract: In recent years, the IT industry has widely employed the microservices architecture to implement cloud native applications. However, the design, implementation and operation of such systems are difficult because a software system in this architecture is highly dynamic. Instances of a service can be created or terminated according to the demand. Services in high demand would have more instances than those in low demand. Services running on a node of heavy workload would migrate to a less busy node in order to achieve better performance. New services are often added into the system and obsolete services are removed from the system without interrupting the operation of the whole system. In this sense, software in the microservices architecture is an ecosystem that consists of a large number of micro-scale services that compete with each other and rely on each other. The design of such systems commonly aims at global optimizations of, for example, scalability, resource utility, service processing capability, etc., which are emergent properties of such ecosystems and notoriously difficult to analyze and proof. In this talk, we will explore the uses of scenario calculus as a formal method to model the dynamic behaviors of software applications in microservices architecture and reasoning about their emergent properties. With load balance as an example, we will demonstrate how to construct formal models of microservices using sets of scenarios, how to valid such a model by proving its completeness and orthogonality, and how to use such a model to prove the reachability and stability of emergent properties of the system.


Assoc. Prof. Dr. Huseyin Seker The University of Northumbria at Newcastle, UK

Dr Huseyin Seker is a multi-disciplinary researcher and data scientist with a particular interest in big data mining, machine learning, and bio-medical and industrial applications. He has published over 100 peer-reviewed papers, led a number of projects, delivered keynote and invited talks at several events and organised a number of conferences and special sessions. He is currently a Reader in the Department of Computer and Information Sciences of Northumbria University in Newcastle-upon-Tyne (UK). He is also the Director of Enterprise and Engagement, and leads Bio-Health Informatics Research Team and Big Data Analytics Lab within the department. In addition to his academic duties, he is an Advisory Board Member of the North East Satellite Applications Centre of Excellence, Steering Group Member of Digital Catapult North East and Tees Valley, and a member of the CyberNorth Initiative in the UK. Further information about his projects and publications can be found at

Speech Title: Data-Driven Healthcare: Discovery of Life & Cost Saving and Profitable Knowledge From (Big) Data

Abstract: Data being generated at fast speed in this digital age is revolutionizing almost every aspect of science and the humanity. Turning big data into actionable, personalized, life-saving and profitable outcome depends on collaborative and intelligent mining of the data in an interdisciplinary environment. Such intellectual utilization of the big data is then expected to yield the state-of-the art evidence-based methods and tools not only for today but also for the future, and consequently will help drive life-saving knowledge in the digital age. Data mining using machine learning methods plays an important role in transforming data into such useful methods and tools. Several data mining methods have been developed and applied in different domains (e.g., health, finance, security). However, due to the complexity and diversity of such data, novel, fast, accurate and reliable data-mining methods are required to address “big data” challenges. This talk will therefore highlight several aspects of the big data mining and machine learning methods that we have developed to address such challenges in health-care domain with examples in the analysis of genomics and proteomics data including next-generation genome sequencing platform.


Prof. Alfredo Cuzzocrea, University of Trieste, Italy

Alfredo Cuzzocrea is currently Associate Professor in Computer Science Engineering at the DIA Department, University of Trieste, Italy. He is also habilitated as Full Professor in Computer Science Engineering by the the French National Scientific Habilitation of the National Council of Universities (CUN) under the egira of Ministry of Higher Education and Research (MESR). Previously, he has been Senior Researcher at the Institute of High Performance Computing and Networking of the Italian National Research Council, Italy, and Adjunct Professor at the University of Calabria, Italy. He got the habilitatation as Associate Professor in Computer Science Engineering by the Italian National Scientific Habilitation of the Italian Ministry of Education, University and Research (MIUR). During the past, he has also been Adjunct Professor at the University of Catanzaro “Magna Graecia”, Italy, Adjunct Professor at the University of Messina, Italy, and Adjunct Professor at the University of Naples “Federico II”, Italy. Previously, he was Adjunct Professor at the University of Naples “Parthenope”, Italy. He holds 36 visiting positions worldwide (Europe, USA, Asia, Australia). He serves as Springer Fellow Editor. He serves as Elsevier Ambassador. He holds several roles in international scientific societies, steering committees for international conferences, and international panels, some of them having directional responsibility. He served as Panel Leader and Moderator in international conferences. He served as Invited Speaker in several international conferences worldwide (Europe, USA, Asia). He is member of scientific boards of several PhD programs worldwide (Europe, Asia, Australia). He serves as Editor for the Springer series “Communications in Computer and Information Science”. He covers a large number of roles in international journals, such as Editor-In-Chief, Associate Editor, Special Issue Editor (including JCSS, IS, KAIS, FGCS, DKE, INS, BigData Research). He edited more than 30 international books and conference proceedings. He is member of editorial advisory boards of several international books. He covers a large number of roles in international conferences, such as General Chair, Program Chair, Workshop Chair, Local Chair, Liaison Chair and Publicity Chair (including CSE, ODBASE, DaWaK, DOLAP, ICA3PP, ICEIS, APWeb, SSTDM, IDEAS, IDEAL). He served as Session Chair in a large number of international conferences (including EDBT, CIKM, DaWaK, DOLAP, ADBIS). He serves as Review Board Member in a large number of international journals (including TODS, TKDE, TKDD, TSC, TIST, TSMC, THMS, JCSS, IS, KAIS, FGCS, DKE, INS). He serves as Review Board Member in a large number of international books. He serves as Program Committee Member in a very large number of international conferences (including VLDB, ICDE, EDBT, CIKM, IJCAI, KDD, ICDM, PKDD, SDM). His current research interests include multidimensional data modeling and querying, data stream modeling and querying, data warehousing and OLAP, OLAM, XML data management, Web information systems modeling and engineering, knowledge representation and management models and techniques, Grid and P2P computing, privacy and security of very large databases and OLAP data cubes, models and algorithms for managing uncertain and imprecise information and knowledge, models and algorithms for managing complex data on the Web, models and algorithms for high-performance distributed computing and architectures. He is author or co-author of more than 340 papers in international conferences (including EDBT, CIKM, SSDBM, MDM, DaWaK, DOLAP), international journals (including JCSS, IS, KAIS, DKE, INS) and international books (mostly edited by Springer). He is also involved in several national and international research projects, where he also covers responsibility roles.

Speech Title: Scalable Privacy-Preserving Big Data Management and Analytics: Where We Are and Where We Are Going

Abstract: The issue of supporting privacy-preserving big data management and analytics is playing the major role at now. Nevertheless, when applied to emerging application scenarios such as social network systems and cloud computing platforms, scalability of techniques and algorithms for supporting privacy-preserving big data management and analytics becomes a critical challenge to be faced-off. Inspired by these considerations, this talk proposes an overview of main scalable privacy-preserving big data management and analytics approaches, and a critical outlook on future research directions.