- Call For Papers
- Paper Submission
- Conference Venue
- Conference Schedule
- Keynote Speakers
Assoc. Prof. Dr. Huseyin Seker
The University of Northumbria at Newcastle, UK
Dr Huseyin Seker is a multi-disciplinary researcher with a particular interest in big data mining, machine learning, and bio-medical and industrial applications. He has published over 100 peer-reviewed papers, lead 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 member of the CyberNorth Initiative in the UK. Further information about his projects and publications can be found at http://computing.unn.ac.uk/staff/yqqd6/home.htm.
Title: Life-saving Knowledge Discovery 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. The talk will also cover examples of both academic and industrial projects that we are working on within our research teams (Bio-Health Informatics and Big Data Analytics).
Prof. Dr. ISLAM ELGEDAWY,
Middle East Technical University-Northern Cyprus Campus, Turkey
Islam Elgedawy is an Associate Professor at the Computer Engineering Department, Middle East Technical University, Northern-Cyprus Campus. He received his computer science degrees from Alexandria University-Egypt (B.Sc. in 1996, and M.Sc. in 2000), and RMIT University-Australia (Ph.D. in 2007). He was a senior software architect at Unilever-Egypt, and a research staff member at IBM India research lab. He received many academic and industrial awards. His work mainly focuses on the areas of service-oriented computing, cloud computing, organic computing, and software engineering. He is an author and co-author of many publications in international journals and conferences, also he has a growing record of consultancy and professional services.
Speech Title: Organic Composite Web Service Delivery: Opportunities and Challenges
Abstract: There are many uncertainty aspects that could hinder composite web services deliverysuch as the Byzantine failures of their components and/or the modules of theadopted delivery system. Furthermore, unplanned demand spikes could occurdepleting services' capacity and degrading their performance. Currently, suchuncertainty aspects are handled manually in a reactive manner by replacingproblematic components and/or modules, or by increasing infrastructurecapacity. Such an approach has a negative impact on service availability andresponsiveness, also it increases the delivery costs. To avoid such problems,service delivery should be automatically handled by a service management systemthat can fulfill customers' SLAs in spite of Byzantine failures and demandfluctuations. Therefore, we need to create an organic delivery system that cansense, rationalize, predict, decide, grow and communicate like an intelligenthuman being. In this talk, we will discuss the challenges and opportunities ofbuilding organic service delivery systems, also we present the CRESCENTframework, our first attempt towards having an organic composite servicesdelivery. CRESCENT has many self-properties, which enables automated SLAmanagement with differentiated levels of service for different customers.