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Dr Peng Xu

 D.Sc.
Lecturer in Management Science

Research interests

  • Data-driven decision analytics: Prescriptive and behavioral
  • Decision support models and systems
  • Stochastic dominance

More research

Accepting applications from PhD students.

Connect with Peng

Email: [email protected]

ORCID
LinkedIn

Profile photo 
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Name 
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Job title 
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Research interests (for researchers only) 
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In Pure (opens in a new tab), select ‘Edit profile’. Under the heading 'Curriculum and research description', select 'Add profile information'. In the dropdown menu, select 'Research interests: use separate lines'.

Contact details 
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ORCID ID 
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Accepting PhD applicants (for researchers only) 
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About Research Publications Supervision Teaching External roles and responsibilities Biography
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About

Dr. Peng Xu is a Lecturer (Assistant Professor) in Management Science at the University of Southampton Business School, England, United Kingdom.

 

His primary research areas include management science, operations research, and business analytics. In particular, his work focuses on data-driven decision analytics (both prescriptive and descriptive) and developing decision support models and systems with data science and mathematical optimization techniques to address production, operations management, economics, finance, and healthcare problems.

 

Dr. Xu has published his scholarly research in top-tier journals, such as European Journal of Operational Research and International Review of Financial Analysis. His research (PI) has been funded by internationally prestigious organizations, including the British Academy (UK), the Foundation for Economic Education (Finland), and Marcus Wallenberg Foundation (Finland).

You can update this in Pure (opens in a new tab). Select ‘Edit profile’. Under the heading and then ‘Curriculum and research description’, select ‘Add profile information’. In the dropdown menu, select - ‘About’.

Write about yourself in the third person. Aim for 100 to 150 words covering the main points about who you are and what you currently do. Clear, simple language is best. You can include specialist or technical terms.

You’ll be able to add details about your research, publications, career and academic history to other sections of your staff profile.

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