Matthias Wildemeersch

Research Scholar

Exploratory Modeling of Human-natural Systems Research Group

Advancing Systems Analysis Program

Biography

Matthias Wildemeersch is a research scholar with the Exploratory Modeling of Human-Natural Systems (EM) research group within the Advancing Systems Analysis (ASA) program. His research interests range from decision making under uncertainty to the study of cooperation. His research aims to provide decision support for problems in multiple fields, extending across welfare economics, environmental economics, and risk management.

Dr. Wildemeersch first joined IIASA in 2014 through the IIASA postdoctoral program. He received his PhD degree in 2013 in Electrical Engineering, Mathematics and Computer Science at the University of Twente, the Netherlands. He gained professional experience at the Joint Research Centre of the European Commission, the Agency for Science, Technology and Research (A*STAR) in Singapore, and the Singapore University of Technology and Design (SUTD).

Last update: 16 FEB 2021

Publications

Wildemeersch, M. , Rovenskaya, E. , & Ilmola, Leena (2017). A collaborative expert system for group decision making in public policy. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-17-011

Wildemeersch, M. , Chan, W.H.R., Rovenskaya, E. , & Quek, T.Q.S. (2016). Characterization and Control of Conservative and Nonconservative Network Dynamics. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-16-026

Sun, H., Sheng, M., Wildemeersch, M. , Quek, T., & Li, J. (2016). Traffic Adaptation and Energy Efficiency for Small Cell Networks with Dynamic TDD. IEEE Journal on Selected Areas in Communications 34 (12) 3234-3251. 10.1109/JSAC.2016.2600442.

Wildemeersch, M. , Strelkovskii, N. , Poledna, S., & Leduc, M. (2016). Network reslience and systemic risk. Methodological approaches to address network resilience. In: European Meetings on Cybernetics and Systems Research, 30 March-1 April 2016, Vienna.

Geraci, G., Wildemeersch, M. , & Quek, T. Q. S. (2016). Energy Efficiency of Distributed Signal Processing in Wireless Networks: A Cross-Layer Analysis. IEEE Transactions on Signal Processing 64 (4) 1034-1047. 10.1109/TSP.2015.2494865.