Wu Siqing from China

Wu Siqing
PhD topic
Data-driven optimization for Smart and Circular reverse logistics management

My PhD topic is "Data-driven optimization for Smart and Circular reverse logistics management".

Who are you and what is your background?

My name is Wu Siqing, I am from China. I pursued my bachelor and master both in China. I hold a Bachelor's degree in logistics management from Zhongnan University of Economics and Law. Following my undergraduate studies, I attained a Master's degree in operation and supply chain management at Zhongnan University of Economics and Law, where fueled my desire to pursue advanced studies in logistics management. Throughout my academic journey, I have consistently demonstrated strong academic performance. I published an article in the International Journal of Production Research as the second author. I have always been passionate about reverse logistics, particularly in designing logistics networks that integrate sustainability and efficiency. My research interests focus on utilizing data-driven methods to optimize these systems and address critical societal challenges. 

What is your PhD research/ topic about?

My PhD topic is “Data-driven optimization for Smart and Circular  reverse logistics management”. Reverse logistics involves handling end-of-life (EOL) and end-of-use (EOU) products, like electronic waste, to maximize value recovery and minimize environmental and societal harm. The project leverages Industry 4.0 technologies to design resilient reverse logistics networks, addressing challenges such as uncertainties and risks in waste management. Using advanced optimization techniques and real-world case studies from France and Australia, the research aims to develop decision-support models for sustainable solutions. The goal is to enhance the efficiency of collection, recycling, and disposal processes while promoting circular economy principles. This work contributes to reducing environmental impacts and supporting industries in achieving sustainable development objectives.

What are the big challenges to be tackled and possible future impacts?

The thesis focuses on developing a data driven multi objective for smart decision-supports of circular reverse logistics management. Then, several types of problems will be addressed:

  1. to configure a resilience reverse network for managing WEEE; 
  2. optimize strategic and operational decisions in a circular RLND with the aim of WEEE
  3. data driven based decision-supports of circular reverse logistics management for managing WEEE. 

The biggest challenge is to establish connection with qualified industrial partners to have access to required data. The second challenge is developing operations research models and optimization algorithms to find sustainable and robust solutions to solve the above problems. 

The expected impact of the project's activities is substantial in both the industrial and academic spheres. The development of a smart decision-support system will enable companies to make more informed, sustainable decisions regarding reverse logistics. This will facilitate the wider adoption of data-driven models for circular economy practices in industries across regions like France and Australia, promoting greater environmental responsibility and resource efficiency. 

What is the configuration of your PhD research?

I have three supervisors, including two supervisors in IMT Atlantique and a foreigner supervisor from Australia. We have a regular meeting every two or three weeks. The three supervisors are pretty nice. They give me detailed and helpful suggestions. Since I am on academic track, I am supposed to spend 24 months at IMT Atlantique and 12 months in Australia at the University of Adelaida, who is the international academic co-supervision partner.

After a few weeks embarked as PhD fellow at IMT Atlantique, what is your first feeling about the programme and your institution?

After a few weeks embarked as PhD fellow at IMT Atlantique, I think everything goes well. I appreciate the programme and IMT Atlantique for several reasons. First, I am really interested in the topic, the programme offers a good opportunity to continue my research on reverse logistics and start my research on data-driven. Second, the programme offers me good chance to gain supervision from excellent researchers. I learned a lot from my supervisors and also colleagues.

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