Kai Nagel
Person

Prof. Kai Nagel

Technische Universität Berlin

Kai Nagel’s focus lies on the application of large-scale agent-based simulation to problems of societal interest. He is one of the authors of MATSim (Multi Agent Transport Simulation), which is used for the development of measures for, e.g., the reduction of emissions incl. CO2, noise, and the spread of COVID-19.

Werdegang

Academic Education

1994: Ph.D. in Computer Science about “Fast microscopic traffic simulations”, University of Cologne, Germany
1991: Diploma in Physics, University of Cologne, Germany
1989: DEA (French diploma) in Oceanology and Meteorology, University of Paris 6, France

Professional Experience (selected)

Since 2004: Full professor (C4) for Transport systems planning and transport telematics, Technische Universität Berlin, Berlin, Germany
1999 – 2004: Assistant professor for Computer Science, Swiss Federal Institute of Technology (ETH) Zürich, Switzerland
1995 – 1999: Postdoc promoted to Technical Staff Member (permanent position) promoted to Research Team Leader, Los Alamos National Laboratory, TSA-Division, Simulation Applications Group, Los Alamos (New Mexico), U.S.A.
1991 – 1993: Research Associate, Department of Mathematics and Center for Parallel
Computing (now Center for Applied Informatics), University of Cologne,
Germany

Mitgliedschaften (maximal 5)

Since 2020: Scientific Policy Advisor for the Federal Government concerning COVID-19
2016 – 2020 & 2008-2012: Supervisory referee (Fachkollegiat) for “systems engineering in traffic, Transport systems, and logistics” for the German National Science Foundation (DFG)
2014 – 2020: Member of the price committee for the Heinz-Maier-Leibnitz price of DFG
2008 – 2016: Member of Transportation Research Board committee on Travel Behavior and Values (ADB10)
Since 1999: Area Editor for “Networks and spatial economics”

Projekte (maximal 5)

2021 – 2023: NaMAV - Nachhaltige Mobilität und städtebauliche Qualitäten durch Automatisierung im Verkehr, BMBF

2019-2022: MOSAIK - 2 - Stadtklima im Wandel: Modellbasierte Stadtplanung und Anwendung im Klimawandel, BMBF

2018-2022: zeroCUTS - Analyse von Strategien zur vollständigen Dekarbonisierung des urbanen Verkehrs, DFG

2017-2020: New Emscher Mobility, Stiftung Mercator

2013-2016: Simulation-based system for the sustainable management of electrically powered taxi fleets, Einstein Stiftung

Publikationen (maximal 5)

Müller, S. A., M. Balmer, W. Charlton, R. Ewert, A. Neumann, C. Rakow, T. Schlenther, and K. Nagel (2021): Predicting the effects of COVID-19 related interventions in urban settings by combining activity-based modelling, agent -based simulation, and mobile phone data. PLOS ONE,
doi:10.1371/journal.pone.0259037.

Kaddoura, I., J. Laudan, D. Ziemke, and K. Nagel (2020): Verkehrsmodellierung für das Ruhrgebiet. In H. Proff, ed., Neue Dimensionen der Mobilität, pp. 361 – 386. Springer Fachmedien Wiesbaden,
doi:10.1007/978-3-658-29746-6_31.

Agarwal, A., D. Ziemke, and K. Nagel (2020)_ Bicycle superhighway: An environmentally sustainable policy for urban transport. Transportation Research Part A: Policy and Practice, 137, 519, doi:10.1016/j.tra.2019.06.015.

Creutzig, F., M. Franzen, R. Moeckel, D. Heinrichs, K. Nagel, S. Nieland, and H. Weisz (2019):
Leveragingdigitalization for sustainability in urban transport. Global Sustainability, 2, doi:10.1017/sus.2019.11.

Kaddoura, I., L. Kröger, and K. Nagel (2017): An activity-based and dynamic approach to calculate road traffic noise damages. Transportation Research Part D: Transport and Environment, 54, 335,
doi:10.1016/j.trd.2017.06.005

Ziemke, D., I.Kaddoura, and K. Nagel (2019): The MATSim Open Berlin Scenario: A multimodal agent-based transport simulation scenario based on synthetic demand modeling and open data. Procedia Computer Science, 151, 870, doi:10.1016/j.procs.2019.04.120.

Horni, A., K. Nagel, and K.W. Axhausen, eds. (2016): The Multi Agent Transport Simulation MATSim. Ubiquity, London, doi:10.5334/baw.