Hamburg, Germany
Institute of Traffic, Logistics and Production I explore hybrid approaches combining discrete choice models with machine learning to enhance predictive accuracy without compromising interpretability.
At the Institute for Logistics, Traffic and Production, I supported the development of macroscopic crowd simulations through targeted programming work. I also calibrated macroscopic models using microsimulation data to improve behavioral accuracy and model reliability.
Institute for Operations Management Built data-driven dashboards to support the analysis of simulation outcomes, ensuring efficient data handling through optimized database structures.
Independent consulting alongside my research at the University of Hamburg. I'm currently advising a public authority in Saudi Arabia on pilgrim safety during Umrah and Hajj across the holy sites of Makkah, Mina, Muzdalifah, and Arafat, as part of Saudi Vision 2030 and 2040. The problem is easy to state and genuinely hard to solve. Pilgrim numbers keep rising into the millions while the sites themselves cannot grow, and the margin between a smooth flow and a dangerous one is narrow. To address this, we developed a mesoscopic crowd simulation of the entire pilgrimage, formulated the scheduling and admission control as a large scale optimization problem, and integrated machine learning and behavioral analytics to anchor the models in real movement patterns.
Supported operational planning for the FIFA World Cup Qatar 2022 by developing microsimulation-based crowd flow visualizations for Msheireb Metro Station, enabling risk analysis and stakeholder communication.
Designed and developed software for the automated generation of technical drawings.