Michail Makridis

Dr. Michail Makridis is a Senior Lecturer at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, where he leads the Road Traffic Technology Group. He serves as the main responsible lecturer for Microscopic Modelling and Simulation of Traffic Operations and has taught Traffic Engineering courses. His work focuses on developing innovative approaches to transportation challenges with a particular emphasis on system resilience and antifragility.

Dr. Makridis's research interests span multiple dimensions of modern transportation systems. His primary focus areas include traffic flow modeling and simulation, intelligent transportation systems, and traffic estimation and control. He has made significant contributions to understanding vehicle dynamics and driver behavior simulation, with particular attention to vehicle energy demand and emissions. His work on antifragile transportation systems represents a cutting-edge approach to designing networks that improve performance under disruption.

His recent publications demonstrate a strong trend toward integrating machine learning with traditional transportation engineering. The research shows increasing focus on antifragility concepts in traffic networks, congestion-aware prediction models, and multimodal transportation solutions that balance the needs of different road users. His work spans theoretical frameworks and practical applications, with several publications addressing real-world challenges in urban mobility.

• MFC and Battery Consumption Model (April 2022)
• Simsub Best Simulation Development Paper Award (TRB 2020) for Enhanced MFC: Introducing dynamics of electrified vehicles for free flow microsimulation modeling

Dr. Makridis leads multiple significant research projects including AntifragiCity, which aims to revolutionize how urban mobility systems respond to disruptions, and ANTIGONES, focusing on designing anti-fragile large-scale traffic frameworks. His work on ASTRA BGT examines the impact of autonomous vehicles on tunnel safety and efficiency, while BikeZ develops models for mass cycling as a service. He also contributes to OptFlow, which focuses on travel-time estimation using FLIR camera sensors. His research has practical applications in improving urban transportation resilience and efficiency.