Recently, Shadi Haj Yahia began a three-month visit to our group to collaborate with Prof. Carlos Lima Azevedo on leveraging advanced modeling techniques. This visit is part of the EIT Urban Mobility Doctoral Training Network program, which aligns perfectly with his ambition to bridge the gap between theoretical and practical research in transport planning.

Shadi is a Ph.D. candidate in Transportation Engineering from the Technion – Israel Institute of Technology. His research focuses on expanding machine learning approaches for travel behavior modeling. Among his works are the integration of machine learning methods in travel demand models and enhancing interpretability by incorporating domain knowledge into deep neural networks for better policy-making decisions. Additionally, he developed a grammatical evolution approach to data-driven utility specification for discrete choice models, combining machine learning with domain knowledge to automate utility specification, ensuring interpretability and predictive performance.

We hope he has a great time staying with us!