Industrial Engineering and Decision Analytics

Overview

This program emphasizes training in original thinking and independent research. Students can design their program of study to suit their interests and needs. 

The program should cover a specialized area in industrial engineering and at least one minor area. It also aims at developing students’ skills in identifying issues related to a theoretical problem or a practical application, formulating an original research project that addresses some of the significant issues, and independently creating an effective solution to the problem. 

A candidate for a PhD degree is expected to demonstrate mastery of knowledge in the chosen discipline and to synthesize and create new knowledge, making an original and substantial contribution to the discipline.

Research Foci

Operations Research and Decision Analytics

Stochastic analysis and simulation, optimization (linear, convex, robust, stochastic), statistical and machine learning, game theory, with applications in supply chain management (manufacturing, inventory, and logistics), revenue management, and healthcare management.

Financial Engineering and Technology

Quantitative finance and stochastic modeling, derivative pricing, investment technology and portfolio management, risk analysis, financial data analysis, cryptocurrency and blockchain analysis, and machine learning in finance.

Engineering Management

Design and manufacturing, human factors and ergonomics, biomechanics, cognitive decision and functional brain studies, virtual reality, and industry 4.0.

Learning Outcomes

On successful completion of the PhD in Industrial Engineering and Decision Analytics from The Hong Kong University of Science and Technology , graduates will be able to:

• An ability for original thinking and independent research;
• Identify issues related to a theoretical problem or a practical application;
• Formulate an original research project that addresses some of the significant issues;
• Independently create an effective solution to the problems and to to design and use the computer/IT tools to solve problems in industrial engineering and decision analytics;
• Apply knowledge of mathematics, science, and engineering to problems in industrial engineering and decision analytics; and
• Use the techniques, skills, and modern engineering tools necessary for solving data driven decision-making problems.