International Railway Brokerage Event 2025

24–25 Jun 2025 | Lille, France

Shahin Gelareh

Academic

Université d Artois

Villeneuve d'Ascq, France

Foreign SME / Foreign research center

Operations researcher & AI enthusiast working on predictive maintenance, multimodal logistics, and data-driven optimization for smart transport systems.

My organisation

Université d'Artois is a public university. Our activities lie at the intersection of applied research, logistics optimisation, and artificial intelligence. Our recent projects focus on the development of strategic and operational planning models in the following areas : • Optimisation of multimodal networks, including rail corridors and combined transport, • Predictive maintenance in complex technical systems (infrastructure, rolling stock), • Reduction of logistics costs and delays in value chains integrating rail freight. One of our most recent works is: N Monemi, Rahimeh, MajidiParast S., Gelareh, S. , A graph convolutional network for optimal intelligent predictive maintenance of railway tracks https://www.sciencedirect.com/science/article/pii/S2772662224001462 We are interested in engaging with partners in the rail sector who are interested in implementing optimisation, digitalisation or AI solutions in their processes.
Read more

About me

Shahin Gelareh is an Associate Professor at Université d’Artois (France), with a specialization in applied operations research, logistics optimization, and artificial intelligence. His research focuses on designing advanced decision-support systems for transportation and logistics, particularly in multimodal and railway networks.

He actively collaborates with industrial and institutional partners through European programs (Interreg, Horizon, DUT), contributing to the development of predictive maintenance models, dynamic fleet and hub management strategies, and data-driven planning tools for sustainable freight transport.

His recent work includes a scientific publication on predictive maintenance in railway systems, combining sensor data analysis and machine learning to optimize intervention schedules and reduce system failures.

Shahin Gelareh is also a scientific collaborator with industries, where he supports innovation in intelligent mobility and infrastructure resilience.

He is eager to connect with partners interested in integrating AI, digitalization, and optimization tools into the railway and logistics sectors.

Social media

Skills

  • AI
  • Machine Learning
  • predictive rail mainetnance
  • Predictive maintenance
  • optimisaiton
  • Simulation

Interests

  • optimisation
  • Combinatorial and network optimization
  • Multi-criteria decision analysis
  • Multiceiteria Optimisation
  • Artificial Intelligence & Machine Learning
  • Operations Research & Optimization
  • Transport & Mobility Systems
  • Maintenance & Reliability Engineering
  • Digital Transformation in Industry
  • Applied Research & Innovation Projects