Series of Dept Research Seminars - “Opportunities in Data Science Research: HKU Perspective" (Date: 11 June 2015)
Dr. Andrew Kusiak, Professor and Chair, Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, Iowa, USA Visiting Research Professor, Department of Industrial & Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China
His research interests include applications of computational intelligence and big data in industrial automation, energy, sustainability, manufacturing, product development, and healthcare.
Dr. Andrew Kusiak shared his views on Opportunities in Data Science Research.
Examples of successful clinical medicine projects initiated in a small data environment were discussed.
Abstract
The growth of data streams and data analysis will significantly impact developments in the 21st century. Big data will play a key role in shaping the design of products, systems and services by making them smarter, better connected, more efficient and widely accessible. Data will become a powerful economic engine. Data analysis has been enlarging its footprint in business and engineering applications for the last two decades. In particular, the two labels of data science and big data have emerged recently, attracting attention and receiving massive press coverage. Expectations from data science are enormous. In the research community, the interest in data is not new, as it has accompanied developments in science and practice for centuries. The novelty is in the scale at which the data is available, its growth and the acknowledgement that data research has been equated to data science. The industrial engineering profession can be at the forefront of applying big data analysis and research in a number of business sectors.
Hong Kong’s economy is undergoing transformation which creates opportunities and challenges for research at the University of Hong Kong. Research opportunities for the Department of Industrial and Manufacturing Systems Engineering in collaboration with other academic unites are presented. A two-stage process has been used to elicit feasible research opportunities with maximum potential for success. At the first stage, nine research areas has been identified. At the second stage three areas were given attention, namely: innovation science, digital awareness devices, and data-driven healthcare research. Examples of successful clinical medicine projects initiated in a small data environment are discussed. The insights gained in these projects are useful in undertaking big data projects.
| Date | 11th June 2015 (Thursday) |
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| Time | 10:30 - 11:30 |
| Venue | Room 8-28, Haking Wong Building, The University of Hong Kong |
| Speaker | Dr. Andrew Kusiak |
| Biography | Dr. Andrew Kusiak is a Visiting Research Professor at The University of Hong Kong and a Professor and Chair of the Department of Mechanical and Industrial Engineering at The University of Iowa, Iowa City. Dr. Kusiak directs research in the Intelligent Systems Laboratory. He speaks frequently at international meetings, conducts professional seminars, and consults for industrial corporations. He has served on the editorial boards of over 40 journals. He is the author, coauthor, and editor of numerous books and hundreds of technical papers published in journals sponsored by professional societies, such as the Association for the Advancement of Artificial Intelligence, American Society of Mechanical Engineers, Society of Manufacturing Engineers, Institute of Industrial Engineers, Institute of Electrical and Electronics Engineers, and other professional organizations. Professor Kusiak is a Fellow of the Institute of Industrial Engineers and the Editor-in-Chief of the Journal of Inte |
| Research Interests | includes applications of computational intelligence and big data in industrial automation, energy, sustainability, manufacturing, product development, and healthcare.
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| Selected Publications | Please refer to: http://user.engineering.uiowa.edu/~ankusiak/recent-paper.html http://user.engineering.uiowa.edu/~ankusiak/prog.html |