Potential Research Topics for October 2018 entry

Evolving Serious Games
Serious games are designed for a particular purpose other than entertainment, usually for training. For example, WBS uses games to teach students about supply chain concepts or leadership. The students playing the game may take on various roles in such a game, apply the knowledge learned in class, and directly observe and learn from the consequences of actions in a virtual and save environment.
While they are a great way to engage students, designing serious games, as designing any other game, is challenging. To support the design process, in recent years certain aspects of games for entertainment have been formulated and tackled as optimisation problems, such as designing the rules, or designing opponents, that make the game interesting or difficult to predict. When formulated as optimisation problem, computational algorithms can be used to automate the game design process. They can even be used to online adapt and personalise a game to a player’s preferences and abilities.
The aim of this PhD research would be to design a framework and develop algorithms to support the design of serious games. There are various interesting research questions to tackle, including how to measure the quality and pedagogical value of a serious games, the definition of the design space, and the development of efficient evolutionary algorithms for the optimisation.
Please contact Juergen Branke if interested

Business analytics in infrastructure asset management for sustainable urban rail network: Rail transportation is an important part of urban cities’ mass transportation system and a large and costly investment. To protect the investment and the sustainability of the rail infrastructure, it is vital to manage these long-life assets as efficiently as possible. Today’s demanding transportation environment requires solutions to deliver services which are safe, reliable, flexible, and economic. The common current practice of reactive maintenance simply can’t cope with the increasing pressure. Therefore the need arises in understanding the long-term behaviour of the assets and for improved predictive maintenance which can reduce disruption time and maintenance costs and most importantly reduce risk associated accidents. This research seeks to develop a decision support system that provides the tools to evaluate critical factors during the life cycle of the assets, and helps set optimized investment priorities. The work will involve using large data sets, modelling, real time conditions monitoring and visualization to optimise critical infrastructure systems. The applicant should have good modelling and programming skills, and ability to work with partners from rail industries. Please contact Wenjuan Zhang if interested.

Application Procedure

Our Doctoral Programme begins in October. Apply by 30 June to guarantee consideration for entry in October of the same year. Later applications may sometimes be considered but we cannot guarantee that they will be processed in time.
You are strongly advised to apply to us as early as possible, particularly as funding often depends on securing a place early. Most funding is allocated by the beginning of January, some earlier still. Please note that as the first year of our programme contains a compulsory taught research training element, it is not usually possible to start at other times of the year. For details on the application process, go to the WBS Application Procedure webpage.