1. Professor CheulWoo Ro
    Title: Smart city and Living Lab

    Biodata : Professor CheulWoo Ro has been with the department of computer engineering Silla University since 1991, where he is currently a professor, located in Busan KOREA. He was a senior researcher of ETRI (Electronic and Telecommunication Research Institute since 1982 and developed TDX (Time Division Exchange) system.

    He holds a PhD in computer engineering from the Sogang University, Korea Currently He is a senior vice president and chairman of cloud platform subcommittee of Korea Cloud Associationand is an IT Advisory and Evaluation Committee of Busan City.

    He is a chairman of Silla university mobile app. center and a member ofIoT living lab committee. He was a presenter at Transfiere forum for Science, Technology and Innovation at European level, held at Malaga Spain in 2016, underthe title “Global Smart City & Cloud Data Center in Busan”.
  2. Professor Zainal A. Hasibuan
    Title: Software Product Line Approach for Improving The Development of Customizable E-Business System for Small and Medium Enterprises

    Biodata : Zainal A. Hasibuan is a Professor of Computer Science at Universitas Indonesia. He earned a bachelor degree majoring in statistics at Bogor Agricultural Institute (IPB), a master of information science at Indiana University and then continued his Ph.D degree studies majoring in information storage and retrieval systems at Indiana University. He involved in professional organizations, Ikatan Profesi Komputer dan Informatika Indonesia (IPKIN) and Indonesian Association of Higher Education in Informatics and Computing (APTIKOM).

    Now, he is the chairman of APTIKOM. He is very active in development of research and education in computer science. He has a wide spectrum of research areas, including e-learning, e-business, information retrieval, information system and software engineering. According to Google Scholar, his publication had reached more than 1150 citations, with h-index 15, and Scopus h-index 7.

  3. Dr. Ninok Leksono
    Title: Palapa Ring and answering Indonesian Broadband needs

  4. Professor Bogdan Gabrys
    Title: Automated composition, optimisation and adaptation of complex predictive systems

    Abstract : There has been a lot of work done on the subject of intelligent data analysis, data mining and predictive modelling over the last 50 years with notable improvements which have been possible with both the advancements of the computing equipment as well as with the improvement of the algorithms. However, even in the case of the static, non-changing over time data there are still many hard challenges to be solved which are related to the massive amounts, high dimensionality, sparseness or inhomogeneous nature of the data to name just a few. What is also very challenging in today’s applications is the non-stationarity of the data which often change very quickly posing a set of new problems related to the need for robust adaptation and learning over time. In scenarios like these, many of the existing, often very powerful, methods are completely inadequate as they are simply not adaptive and require a lot of maintenance attention from highly skilled experts, in turn reducing their areas of applicability.

    In order to address these challenging issues and following various inspirations coming from biology coupled with current engineering practices, we proposed a major departure from the standard ways of building adaptive, intelligent predictive systems by utilising the biological metaphors of redundant but complementary pathways, interconnected cyclic processes, models that can be created as well as destroyed in easy way, batteries of sensors in form of pools of complementary approaches, hierarchical organisation of constantly optimised and adaptable components. In order to achieve such high level of adaptability we have proposed novel flexible architectures which encapsulate many of the principles and strategies observed in adaptable biological systems. The proposed approaches have been extensively and very successfully tested by winning a number of predictive modelling competitions and applying to a number of challenging real world problems including pollution/toxicity prediction studies, building adaptable soft sensors in process industry in collaboration with Evonik Industries or forecasting demand for airline tickets covering the results of one of our collaborative research projects with Lufthansa Systems.

    Following the drive towards automation of predictive systems building, deployment and maintenance, recent work at Prof. Gabrys’ group resulted in an approach and an open-source software which allows to automatically compose, optimise and adapt mutlicomponent predictive systems (MCPS) potentially consisting of multiple data preprocessing, data transformation, feature and predictive model selection and postprocessing steps. Our findings, supported by extensive experimental analysis, can have a major impact on development of high quality predictive models as well as their maintenance and scalability aspects needed in modern applications and deployment scenarios. All of these will be covered and discussed during this keynote talk.

    Biodata : Bogdan Gabrys is a Data Scientist, a Professor of Data Science and a Director of Advanced Analytics Institute at the Faculty of Engineering and IT, University of Technology Sydney, Australia. Immediately before moving to Sydney in September 2017, he held the positions of a Chair in Computational Intelligence (since 2005) and a Head of Data Science Institute (since 2014) at the Faculty of Science and Technology, Bournemouth University, UK.

    His research, consulting and advisory activities have concentrated on the areas of data science, complex adaptive systems, computational intelligence, machine learning, predictive analytics and their diverse applications. In particular, he has pursued the development of various statistical, machine learning, nature inspired and hybrid intelligent techniques especially targeting data and information fusion, learning and adaptive methods, multiple classifier and prediction systems, processing and modelling of uncertainty in pattern recognition, diagnostic analysis and decision support systems.

    He is an accomplished author (with over 150 publications), frequently invited speaker at international events and fora and sought after data science expert.More information can be found at his personal web page: http://bogdan-gabrys.com/

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