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Research Scholar Exploratory Modeling of Human-natural Systems Research Group - Advancing Systems Analysis Program
+43(0) 2236 807 235
Piotr Zebrowski is a research scholar in the Exploratory Modeling of Human-natural Systems Research Group of the IIASA Advancing Systems Analysis (ASA) Program. His current research focuses on modeling persistence in human-natural systems and on questions of fair distribution of burdens of global warming mitigation action.
Zebrowski is involved in projects assessing response delays to policies aiming at greenhouse gas (GHG) emission reductions in the transport sector and investigating the effectiveness of measures to limit the spread of the COVID-19 virus. He also contributed to projects that identified viable scenarios for deep GHG emission reductions in agriculture and in the economy. Zebrowski's research interests include novel methods of data analysis, particularly the analysis of dynamics of global and national GHG emissions and uncertainty of their estimates, as well as multi-objective optimization and Bayesian network models for cybersecurity.
Prior to joining IIASA, Zebrowski was a research assistant at the Department of Probability Theory and Mathematics of Finance of the Institute of Mathematics at the Polish Academy of Sciences, where he conducted research in the fields of probability theory, stochastic processes, and their applications in finance and statistical physics. He holds a PhD degree in mathematics obtained from the Institute of Mathematics in the Faculty of Mathematics and Computer Science at the University of Wroclaw, Poland.
Last update: 23 JUL 2021
Lin, H., Żebrowski, P. , Fath, B. , Liljenström, H., & Rovenskaya, E. (2021). Modelling stakeholder satisfaction for conflict resolution in wildlife management: a case of wolf population in Sweden. European Journal of Wildlife Research 67 (4), e61. 10.1007/s10344-021-01495-1.
Cristino, C.T., Żebrowski, P. , & Wildemeersch, M. (2020). Assessing the time intervals between economic recessions. PLoS ONE 15 (5), e0232615. 10.1371/journal.pone.0232615.
Rovenskaya, E. , Aghababaei Samani, K., Baklanov, A. , Ermolieva, T., Folberth, C. , Fritz, S., Hadi, H., Javalera Rincón, V. , et al. (2019). Artificial Intelligence and Machine Learning for Systems Analysis of the 21st Century. IIASA Working Paper. Laxenburg, Austria: WP-19-010
Jarnicka, J. & Żebrowski, P. (2019). Learning in greenhouse gas emission inventories in terms of uncertainty improvement over time. Mitigation and Adaptation Strategies for Global Change 24 (6), 1143-1168. 10.1007/s11027-019-09866-5.
Mancuso, A., Żebrowski, P. , & Couce Vieira, A. (2019). Risk-based Selection of Mitigation Strategies for Cybersecurity of Electric Power Systems. In: SRA-E 2019 conference, 26 June 2019, Potsdam, Germany.
Jonas, M. , Zebrowski, P. , & Jarnicka, J. (2018). The crux of reducing emissions in the long-term: The underestimated “now” versus the overestimated “then”. In: 19. Österreichischer Klimatag, 23 –25 April 2018, Salzburg, Austria.
Jonas, M. , Zebrowski, P. , & Jarnicka, J. (2018). Towards Handling Uncertainty in Prognostic Scenarios: Advanced Learning from the Past. IIASA Report. Vienna, Austria: Austrian Academy of Sciences
Jonas, M. & Żebrowski, P. (2018). The crux with reducing emissions in the long-term: The underestimated “now” versus the overestimated “then”. Mitigation and Adaptation Strategies for Global Change, 1-22. 10.1007/s11027-018-9825-9.
Jonas, M. & Zebrowski, P. (2017). Learning from the Past: Supplementary Exercise on Memory, Persistence and Explainable Outreach. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-17-016
Zebrowski, P. , Jonas, M. , & Jarnicka, J. (2017). Towards Handling Uncertainty in Prognostic Scenarios: Advanced Learning from the Past. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-17-015
Jonas, M. & Zebrowski, P. (2017). ASA Outreach: Workshop Series on Uncertainty in Greenhouse Gas Emissions. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.
Zebrowski, P. & Jonas, M. (2017). ClimTrans2050-A Research Plan for Open Source Model for Analyzing Austria's Transition to a Low-Carbon Economy by 2050. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.
Zebrowski, P. & Jonas, M. (2017). Toward handling uncertainty in prognostic scenarios: Advanced learning from the past. In: IIASA Institutional Evaluation 2017, 27 February-1 March 2017, IIASA, Laxenburg, Austria.
Jonas, M. & Żebrowski, P. (2016). Uncertainty in an Emissions Constrained World: Method Overview and Data Revision. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-16-009
Haluschak, M., Jonas, M. , Zebrowski, P. , Jarnicka, J., Bun, R., & Nahorski, Z. (2016). Taking advantage of the UNFCCC Kyoto Policy Process: What can we learn about learning? In: Public Scientific Conference of Institute of Applied Mathematics and Fundamental Science. pp. 112-113 Lviv, Ukraine: Lviv Polytechnic National University. ISBN 978-617-607-398-7
Magdziarz, M., Scheffler, H.P., Straka, P., & Żebrowski, P. (2015). Limit theorems and governing equations for Levy walks. Stochastic Processes and their Applications 125 (11), 4021-4038. 10.1016/j.spa.2015.05.014.
Jonas, M. , Żebrowski, P. , & Rovenskaya, E. (2015). A metric for the prognostic outreach of scenarios: Learning from the past to establish a standard in applied systems analysis. In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 78-89 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X
Żebrowski, P. , Jonas, M. , & Rovenskaya, E. (2015). Assessing the improvement of greenhouse gases inventories: Can we capture diagnostic learning? In: Proceedings, 4th International Workshop on Uncertainty in Atmospheric Emissions, 7-9 October 2015, Krakow, Poland. pp. 90-96 Warsaw, Poland: Systems Research Institute, Polish Academy of Sciences. ISBN 83-894-7557-X
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