Centre for Technology, Operations and Supply Chain Analysis (TOSCA) Seminar Series

Open to Leeds University Business School Staff and Students ReImagining the Supply Chains Network Plus (RiSC+): lessons learned from grant application and implementation experience

The Analytics, Technology & Operations Department (ATOD) and the Centre for Technology, Operations and Supply Chain Analysis (TOSCA) kindly invite all Leeds University Business School Staff and Students to attend this online seminar. There is no need to register. Simply join us online using the teams link below. 

1pm to 2pm - Seminar
2pm to 2.30pm - Q&As

Dr Guo will share with her how she and her team develop ideas and partners for the ReImagining the Supply Chains Network Plus (RiSC+), how they manage the complexity involved in the grant application processes. She will further share some lessons she learned from implementing the Network Plus together with her partners.
 
Bio:
Hangfei is a Reader in Supply Chain Management at Queen's Business School, Queen's University Belfast. Hangfei gained her Ph.D. in Business (Management Science) from McMaster University (Canada) and MPhil in Business from Lingnan University (Hong Kong).  
https://www.qub.ac.uk/schools/queens-business-school/people/academic-staff/AllAcademicStaffProfiles/Guo.html
 
 
Hangfei is the Principal Investigator for the ReImagining the Supply Chains Network Plus (RiSC+). This is a £6.25m funding award from UK Research and Innovation (UKRI), as part of its Building a Secure and Resilient World strategic theme, to model and reimagine supply chains across the UK in food, critical minerals and fashion. The RiSC+ project will offer evidence that exposes vulnerabilities, remedies current risks and demonstrates future potential, ultimately helping to empower the UK to move towards more resilient and secure supply chains.
 
Hangfei's main research areas are operational research, operations management and supply chain management. Her current work aims to bridge the gap between mathematical tractability and practical applicability by using analytical models and optimization techniques on one hand and empirical studies employing data-driven and prescriptive methods on the other hand.
 
Hangfei has completed a knowledge transfer project that develops an innovative method to manage and optimize supply chains. The method combines simulation, big data analytics and machine learning tools and techniques to develop a digital representation of the supply chain that can be used to support data-driven decision-making in supply chain management. This AKT2I project with SDG has been selected by Innovate UK to be a featured case study on the official KTP website: Supply chain transformation using big data https://www.ktp-uk.org/casestudy/supply-chain-transformation-using-big-data/. 
 
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Microsoft Teams meeting 
Join: https://teams.microsoft.com/meet/38930401696366?p=2LzvbSRN058PXuHOjJ 
Meeting ID: 389 304 016 963 66 
Passcode: qy7LE2XH