Lehmacher W., Lind M., Poikonen J., Meseguer J., Cervera J.L.C. (2022) Reducing port city congestion through data analysis, simulation, and artificial intelligence to improve the well-being of citizens, Journal of Mega Infrastructure & Sustainable Development, DOI: 10.1080/24724718.2022.2133524

Lind M., Lehmacher W., Poikonen J., Gardeitchik J. (2022) Flattening the curve of infrastructure utilization by flexible port opening hours – an artificial intelligence use case for smart resource allocation, 2/3-2022, The Loadstar

Lind M., Lehmacher W., Hoffmann J., Jensen L., Notteboom T., Rydbergh T., Sand P., Haraldson S., White R., Becha H., Berglund P. (2021) Finite port resources can be stretched with dynamic digital developments, The Loadstar, 30/6-2021

Lind M., Lehmacher W., Hoffmann J., Jensen L., Notteboom T., Rydbergh T., Sand P., Haraldson S., White R., Becha H., Berglund P. (2021) Improving a congested maritime supply chain with time slot management for port calls, The Maritime Executive, 29/6-2021

Lind M., Lehmacher W., Jensen L., Notteboom T., Rydbergh T., White R., Becha H., Rodriguez L., Sand P. (2021) Resolving the ship backlog puzzle in the Suez Canal: predicting ship transits in capacity-constrained areas, The Smart Maritime Network, 22/4-2021 (https://smartmaritimenetwork.com/2021/04/22/resolving-the-suez-backlog-predicting-ship-transits-in-capacity-constrained-areas/)

Lind M., Lehmacher W., Jensen L., Notteboom T., Rydbergh T., White R., Becha H., Rodriguez L., Sand P. (2021) The Suez Canal blockage as a catalyst for innovation, Splash247.com, 26/4-2021 (https://splash247.com/the-suez-canal-blockage-as-a-catalyst-for-innovation/ )

Lind M., Lehmacher W., Knäpper Jensen L., Rydbergh T., Becha H., Rodriguez L. (2021) The Suez Canal puzzle – pulling the pieces together, The Maritime Executive, 2021-03-31 (https://www.maritime-executive.com/editorials/the-suez-canal-puzzle-pulling-the-pieces-together)

Evmides N., Aslam S., Televantos A., Karagiannis A., Paraskeva A., Michaelides M., Herodotou H. (2021) Employing fuzzy matching for cleaning manual AIS entries, World of Shipping Portugal. An International Research Conference on Maritime Affairs 28 – 29 January 2021, CIMOSM (Instituto Superior de Engenharia de Lisboa), Portugal

Fu X., Xiao Z., Xu H., Jayaraman V., Othman N. B., Chua C. P., Lind M. (2021), AIS Data Analytics for Intelligent Maritime Surveillance Systems, in M. Lind, M. Michaelides, R. Ward, R. T. Watson (Ed.), Maritime informatics. Heidelberg: Springer.

Herodotou H., Aslam S., Holm H., Theodossiou S. (2021), Big Maritime Data Management, in M. Lind, M. Michaelides, R. Ward, R. T. Watson (Ed.), Maritime informatics. Heidelberg: Springer.

Kyriakides I., Hayes D., Tsiantis P. (2021), Intelligent Maritime Information Acquisition and Representation for Decision Support, in M. Lind, M. Michaelides, R. Ward, R. T. Watson (Ed.), Maritime informatics. Heidelberg: Springer.

Schmitt P., M. L. Bartosiak, Rydbergh T. (2021), Spatiotemporal Data Analytics for the Maritime Industry, in M. Lind, M. Michaelides, R. Ward, R. T. Watson (Ed.), Maritime informatics. Heidelberg: Springer.