Hong Kong University of Science and Technology (HKUST)
Operations Management is a division of the Department of Information Systems, Business Statistics and Operations Management. The department was ranked 12th worldwide by INFORMS in research productivity based on publications in Information Systems and Operations Management journals. The division includes two research areas: Operations Management and Statistics.
The PhD program in Operations Management emphasizes model-based methodology and practice-motivated research. The program trains students to use quantitative tools and analytical frameworks from operations research, economics, and other disciplines to study managerial problems in business processes, such as supply chains, manufacturing, and service systems.
Faculty members in this area have PhD degrees from top universities such as Carnegie Mellon, Columbia, MIT, Stanford and UBC. They are frequent contributors to top academic journals, such as Operations Research, Management Science, Manufacturing and Service Operations Management, and IIE Transactions. Several of them have served or are currently serving on the editorial boards of these journals.
The research foci of the Operations Management area are supply chain contracting, information sharing in supply chains, supply chain coordination, interface of marketing and supply chain management, production and inventory management, incentives in operations, and quality management.
The PhD program in Statistics emphasizes both the theoretical development of statistical methodologies and applications to the real business world. The program trains students to have a solid theoretical foundation and statistical expertise in applications to various areas like finance, economics and marketing, and statistical consulting.
Faculty members in this area have PhD degrees from top universities such as Stanford and UC Berkeley. Their works appear in top journals like Annals of Statistics, Journal of the American Statistical Association and Biometrika. The research foci of the Statistics area are Bayesian statistics, missing data problems, cluster analysis, semiparameteric models, data mining, sequential analysis, stochastic control, financial time series modeling, statistical methods for risk management and nonlinear time series.