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A Look from Researchers – Interview with EL KHALFI Zeineb

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3 questions to EL KHALFI Zeineb
Teacher–Researcher, member of the “Multimodal Transport Systems Management” theme at CESI LINEACT

Since 2019, she has been working at the intersection of teaching and applied research around multimodal transport systems. As a member of the “Multimodal Transport Systems Management” theme, she collaborates closely with the Mobility and Intelligent Transport Chair at the University of Bordeaux through a skills-based sponsorship, supervising internships and PhD projects, and contributing to several studies conducted by the chair.
She is also involved in the “Mon trajet vert” program, awarded by the French Energy Savings Certificates scheme in 2023, which aims to improve students’ daily mobility. She currently co-supervises a PhD thesis focused on predicting university students’ mobility needs within a dynamic multimodal system.

Your work intersects artificial intelligence, decision support, and intelligent transportation systems. What sparked your interest in these themes ?

I became interested in artificial intelligence because it is a constantly evolving field, both scientifically stimulating and rich in practical applications. What particularly attracted me is its ability to address and adapt to complex, diverse, and very real issues that lie at the heart of today’s challenges.
AI makes it possible to model, optimise, and improve many processes in various contexts—for example, route optimisation and prediction in urban mobility, or decision support in transportation system management. It offers powerful levers to improve urban mobility, enhance safety, and optimise network management in real time.
This multidisciplinarity, combined with the concrete impact that developed solutions can have on daily life, was a key factor in my choice to specialise in this field.

You contribute to applied research projects related to intelligent transport systems. In your view, what are the most promising challenges for bringing AI closer to mobility needs ?

Urban mobility is becoming increasingly complex due to the temporal and spatial variability of flows and the rise of multimodality. In this context, current systems are showing their limits, making it necessary to develop more efficient and truly intelligent tools.

One major challenge lies in exploiting mobility data more effectively to improve service quality. The issue is not only collecting these data but integrating AI at the heart of engineering and deployment processes for decision-support systems.

AI is not meant to directly control transport networks, but rather to provide relevant, anticipatory, and robust recommendations to support decision-makers and enhance operational management. These advances represent, in my view, the most promising paths for aligning AI with real mobility needs.

If you had to summarise your work in one powerful idea, what would it be ?

AI is a powerful and constantly evolving tool. When used thoughtfully and responsibly, it has the potential to profoundly transform services and significantly strengthen the quality of decision-making. However, its deployment must always be accompanied by vigilance, ethics, and genuine critical thinking to ensure responsible and beneficial use.

Research is to see what everybody else has seen and think what nobody else has thought.

Albert Szent-Györgyi