System Informatics and Management Science (SiMS) laboratory is established in 2011 summer in Department of Industrial Management of National Taiwan University of Science and Technology. The director of SiMS lab is Dr. Chao-Lung Yang. The research focus of SiMS lab is applying data mining, statistical decision making, information technology, and optimization for managerial problem solving in the complex systems. Our interdisciplinary perspective is engaging System Informatics analytical models in the managerial problem domains to deliver the better decision making.
What is System Informatics (SI)?
System informatics is an interdisciplinary learning that endeavors to streamline the processing, analysis, and utilization of information in a complex system. The complex system here does not limit to an “information system”, it could be any system in nature science, engineering, service, or management domain congested with the information flow. In order to handle a large-scale, high-speed, and real time information, the information technology integrated with analytical models with empirical data-driven methodologies is needed.
What is Management Science (MS)?
Management Science is a discipline that aims at providing managerial decision making by applying a scientific approach to resolve the managerial problem. A managerial problem can described as the gap between a current state and a desired state of decision domain, such as resource allocation or cost-benefit-trade-off problems. A problem solving process is formed to analyze the situation and develop a scientific approach including mathematics and computer science to bridge the gap.
There are three major learning activities created in SiMS Lab: 1) data analysis (statistical and multivariate analysis), 2) data processing (programming and database management), and 3) managerial decision making (case study, optimization modeling). We hope our student researchers can cultivate their capability of scientific data analysis and become a data scientist or data analyst for their future career.
Currently, SiMS Lab has four main research directions which start from building up fundamental data analysis tools and apply them on Big Data analytics platform (Hadoop), to solve or create an innovative service application in the industry.
1. Data Mining and Big Data Analytics (data analysis of customer behavior)
2. Industry 4.0 Data Analytics (preventive maintenance and factor analysis)
3. Service Management (recommendation system development)
4. Human Action Recognition on Operation Management (quality improvement and action recording)
Source: http://www.pursuant.com/blog/tag/dikw-model/
