About us

The Department of Systems Engineering and Engineering Management was established in the year 1991 (in the name of Department of Systems Engineering) as the first of its kind in tertiary educational institutions in Hong Kong.  In August the same year, the Department was one of the 4 founding departments of the newly established Faculty of Engineering.  In the past twenty seven years, the Department not only has made itself become a regional and internationally renowned academic program, but also has contributed significantly to the growth of the Faculty, by its vigorous pursuit in teaching, research and service.

The Bachelor of Engineering in Systems Engineering and Engineering Management is currently organized around four focal areas: Business Information Systems; Financial Engineering; Logistics and Supply Chain Management; and Service Engineering and Management.

Four Focal Area

LOGISTICS AND SUPPLY CHAIN MANAGEMENT

Hong Kong is one of the world’s logistics and supply chain management hubs, which expands to include non-industrial operations involving supply, distribution, transportation, communication and information handling, medical care and safety. According to The Association for Operations Management (APICS), nowadays supply chain management covers the design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand and measuring performance globally.

To increase the agility and flexibility of today’s complex business environment, systems engineers can process huge amounts of business data for decision-making, optimization, and effective execution along the supply chain networks. They possess professional knowledge in the design and control of these operational and information-rich systems, which require the use of many different kinds of scientific management methodologies.

SERVICE ENGINEERING AND MANAGEMENT

Major pillars of the Hong Kong economy are related to services such as finance, professional services, medicine, education and logistics. Those service systems are complex systems in which specific arrangements of people and technologies take actions that provide value for others. Systems are designed and built to provide and sustain services, yet because of their complexity and size, operations do not always go smoothly, and all interactions and results cannot be anticipated. As a result, systems engineers are trained to develop quantitative decision-making tools and methodologies for smooth, agile and resilient operations in data-intensive service systems such as finance, healthcare, and logistics.

FINANCIAL ENGINEERING

The stability of financial markets benefits billions of people. In order to respond to the challenge of maintaining healthy and stable markets, today’s systems engineers must possess quantitative and business know-how to understand and manage the complexity of financial instruments and inter-bank dynamics.

Systems engineers master the core skills of modelling economic and human behaviours, and provide insights regarding how to reach economic, social and individual investors’ objectives.

Financial engineering covers modelling, analysis, implementation of financial decision making and risk management. More than just theories, systems engineers develop practical tools with a combination of multiple disciplines including statistics, probability, optimization and stochastic analysis. Related research topics include pricing and hedging, systematic risk management, stochastic volatility models, and portfolio choice.

INFORMATION SYSTEMS

Information Systems is about data-intensive computing for information processing and intelligence extraction to enable better decision-making and execution for complex systems in our changing society.

In order to leverage today’s rapidly-advancing technology, new generations of algorithms and technologies are applied. Systems engineers are well-trained with solid computer-related and programming knowledge for analysing and mining data, building large-scale analytic models, both stochastic and deterministic, creating algorithms for solving problems, executing large-scale simulation models, and allowing users to easily visualize and manipulate the data.