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Keynote Speakers

Keynote Talk By


Dr. Simon Fong
Associate Professor
Department of Computer and Information Science
University of Macau
Av. Padre Tomas Pereira, Taipa, Macau SAR


Title: Analyzing Sensor Data in Real-time by Data Stream Mining Methods: Challenges and Prospects

Analyzing real-time sensor data is expected to be a feasible but challenging task even equipped with the latest frontier of information technology. The volume of sensor data is predicted by experts that will vastly surpass from various sources of Big Data, such as wireless sensor network, IOT, CCTV videos, social media over the next decade. Enterprises are eager to discover the true benefits by data mining such sensor data in terms of real-time intelligence. Technically, from the perspective of analytics, a new breed of data mining techniques known as data stream mining seems to be a possible solution though it has a relatively short history of development. With the number of new sensor data sources and issues of Big Data that are emerging, data stream mining massive data sets in real-time has a strong application motivation. In particular, data stream mining which is unlike its predecessor, traditional data mining, is able to process and incrementally induce a prediction model on the fly without the need of loading in the full archive of data. This attractive property makes it a potentially suitable candidate for the next generation real-time sensor data analtyics solution. In this talk, the pros and cons as well as some recommended solutions are discussed on the possibilities of applying data stream mining methods for analyzing sensor data in real-time. Computer simulation demo will be conducted for showing the efficacy of some current data stream mining methods over sensor data.

Speaker's bio
Simon Fong graduated from La Trobe University, Australia, with a 1st Class Honours BEng. Computer Systems degree and a PhD. Computer Science degree in 1993 and 1998 respectively. Simon is now working as an Associate Professor at the Computer and Information Science Department of the University of Macau. He is also one of the founding members of the Data Analytics and Collaborative Computing Research Group in the Faculty of Science and Technology. Before joining the University of Macau, he worked as an Assistant Professor in the School of Computer Engineering, Nanyang Technological University, Singapore. Prior to his academic career, Simon took up various managerial and technical posts, such as systems engineer, IT consultant and e-commerce director in Melbourne, Hong Kong and Singapore. Some companies that he worked before include Hong Kong Telecom, Singapore Network Services, AES Pro-Data and United Oversea Bank, Singapore. Dr. Fong has published over 289 international conference and peer-reviewed journal papers, mostly in the area of E-Commerce technology, Business Intelligence and Data-mining.


Dr. Amara Satharasinghe
Director General - Department of Census and Statistics
Sri Lanka

Title: Producing Official Statistics Using Big Data


Statistics are numerical representations of information. They are very credible in our society, as evidenced by their frequent use by news agencies, government offices, politicians, and academics.

Diversity of data sources are used in the production of official statistics for decades, including ˇ°designedˇ± data sources such as censuses and surveys, and ˇ°foundˇ± data sources such as administrative and transactional data.

The increasing capability of modern technologies new sources of data is becoming increasingly available. Such sources include data from sensor networks and tracking devices e.g. satellites and mobiles phones, behavior metrics e.g. search engine queries, and on-line opinion e.g. social media commentaries. The collective term for such data sources is Big Data. The characteristics of the big data are large volume, large variety, and speed of generation and complexity. Key enablers for growth of Big Data are increasing of storage capacity, increasing of processing power and high availability.

All around the world, big data is regarded as a key resource for creating enormous value. These trends ask official statistical agencies to find counter measures against the statistical production by the public sector by using big data and to find ways to use big data by themselves. Currently, statistically advanced countries and international organizations such as OECD and UNECE are discussing statistical policies related to big data, and roles of national statistical offices.

It is worthwhile to review the possibility of combining big data in statistical production. This presentation elaborates a few examples how big data can be used for production of official statistics.

Speaker's bio

Dr. Amarajeewa Jinabandu Satharasinghe is the present Director General of the Department of Census and Statistics of Sri Lanka.

Dr. Satharasinghe graduated from University of Colombo, Sri Lanka, with a 1st Class Honours B.Sc. Degree in 1983. He did his MSc and MA at the University of Colombo in 1988 and 1998 respectively. He obtained a PhD. in Applied Sciences at the University of Peradeniya in 2002.

Before receiving the post of Director General at the Department of Census and Statistics he served as a Statistician, Senior Statistician, Deputy Director, Director and Additional Director General (Action) at the same Department. He is a receiver of Hubert H. Humphrey Fellowship at University of California. He was also awarded the CIC Charitable and Educational Trust Fund Award for the best performances of the first two years of his basic degree programme, 1981/82 at the University of Colombo. He had won several prizes and awards such as the best presentation of the Session on GIS Applications and Climatology of the 13th Annual Congress of the Postgraduate Institute of Agriculture, University of Peradeniya in 2001 and Prize for the Commendable presentation at the Second National Symposium on Geo-informatics organized by the Geo-Informatics Society of Sri Lanka in 2005.

He had initiated several special activities and projects and introduced dynamic frameworks for data analysis at the Department of Census and Statistics in Sri Lanka. Dr. Satharasinghe had contributed immensely to many research conferences in the field and has number of highly cited papers and publications to his credit.




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