Selim Dündar
Civil Engineering Department Chair
Istanbul Okan University
Tuzla/Akfırat, Türkiye
Associate Professor in Transportation Engineering at Istanbul Okan University, working on smart mobility, CCAM, micromobility, traffic simulation, digital twins and AI. Seeking partners for Horizon Europe and international R&I projects.
My organisation
About me
I am an Associate Professor of Civil Engineering and Head of the Civil Engineering Department at Istanbul Okan University, specialising in transportation engineering and smart mobility.
My research focuses on connected and automated mobility (CCAM), intelligent transportation systems, traffic modelling and simulation, micromobility, road safety, digital twins, data-driven transportation systems, and the application of artificial intelligence and machine learning to mobility challenges. I am also increasingly involved in research on transport resilience, Urban Air Mobility (UAM), multimodal integration and emerging mobility technologies.
I have experience in European R&I projects, including Horizon Europe and other EU-funded initiatives, with particular involvement in mobility-related research, pilot design, traffic simulation, societal and behavioural aspects, and the development and validation of innovative transport solutions. I am interested in contributing to international consortia as a research partner, task/work-package leader, pilot partner or co-developer of new project concepts.
Beyond transportation, I am interested in interdisciplinary research connecting mobility with AI, digitalisation, sustainability, circular economy, cultural heritage and historical transportation systems.
I am particularly interested in meeting universities, research organisations, technology companies, public authorities and mobility operators interested in developing joint proposals for upcoming Horizon Europe and other European R&I calls.
Skills
- civil engineering
- Transportation Engineering
- Transportation Planning
- autonomous vehicles
- micromobility
- Artificial Intelligence
- Machine Learning
- cultural heritage
- History
- circular economy