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Data-informed Decision Making for Crisis Management (Advert Reference: SF21/BL/MOS/TANG)

   Faculty of Business and Law

  Dr Jing Tang  Applications accepted all year round  Self-Funded PhD Students Only

About the Project

A timely response to a crisis situation, e.g. COVID-19, faces great challenges given the surrounding uncertainties and potential future consequences. Such a crisis leads to alternative scenarios and limited/nonexistent data under which a series of timely decisions need to be made to manage shifting circumstances. Making decisions in such crises contexts requires situational knowledge, experience in dealing with past events and intuitions about the uncertain future. The current decision methods using data-driven approaches cannot handle such decision problems since they require sufficient quantitative data and measurable domain knowledge. Decision analysis in crisis management demands more input of qualitative knowledge from domain experts, where the knowledge needs to be encoded in a user-friendly decision model to allow closer interactions between knowledge engineers and decision makers, leading to a new line of research on data-informed decision analysis.     

Data-informed decision analysis involves transferring knowledge from other scenarios and applying past experience in both similar and different cases. The decision process and potential outcomes are to be transparent and effectively communicated to multiple stakeholders. Data-informed approach is aligned with human-centric decision analysis where artificial intelligence (AI) could be applied in a wide range of practical applications including crisis management. When a crisis scenario is freshly new and highly dynamic under uncertainty, such as the pandemic crisis, end-users or policy makers shall be actively engaged in the decision-making process.

This project aims to tackle research challenges in data-informed decision making in crisis situations. It includes the following main objectives:

·        Proposing a new decision model (e.g. on the basis of probabilistic graphical decision models) that can represent a portfolio of knowledge and data. The new model needs to accommodate the transferred knowledge from other domains while being clearly understood by both knowledge engineers and decision makers. For example, the experience in dealing with the SARS event is useful to inform responses to COVID-19 pandemic and needs to be clearly represented in the COVID-19 pandemic decision model.

·        Developing a set of methods to solve the new model, which provides optimal decisions with best benefits to decision makers. The methods will deal with the joint influence of mixture information on possible decisions and find the optimal decisions efficiently in a limited amount of time.  

·        Studying the new decision-making techniques in some specific crisis situations. We may choose the global COVID-19 crisis as one example and formulate a manageable pandemic scenario as a starting point. Meanwhile, we may investigate other crisis situations, e.g. critical cyber-attacks, terrorism, natural disasters.

This project will lead to a new way of conducting decision analysis in crisis management through AI modeling and reasoning methods. The research outcomes will provide novel theoretical inputs to decision science research and exhibit significant impact on good practice in crisis management.  

This multi-disciplinary project will cover research in the area of management science, social psychology, data science and artificial intelligence and explore interesting practical applications in important problem domains.

This project is supervised by Dr Jing Tang

Eligibility and How to Apply:

Please note eligibility requirement:

·       Academic excellence of the proposed student i.e. 2:1 (or equivalent GPA from non-UK universities [preference for 1st class honours]); or a Masters (preference for Merit or above); or APEL evidence of substantial practitioner achievement.

·       Appropriate IELTS score, if required.

For further details of how to apply, entry requirements and the application form, see 

Please note: Applications that do not include a research proposal of approximately 1,000 words (not a copy of the advert), or that do not include the advert reference (e.g. SF21/…) will not be considered.

Deadline for applications: Open

Start Date: March 2022 or October 2022

Northumbria University takes pride in, and values, the quality and diversity of our staff and students. We welcome applications from all members of the community.

Funding Notes

Please note this is a self-funded project and does not include tuition fees or stipend.

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