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Dr. Piotr Zebrowski is a research scholar with the IIASA Advanced Systems Analysis (ASA) Program. His current research focus is on questions of fair distribution of burdens of global warming mitigation action, and on propagation of uncertainty in climate models. He contributes to projects developing models aiming at informing policymakers about options for deep greenhouse gas (GHG) emission reductions in agriculture and in economy. He is also interested in novel methods of data analysis, particularly in the analysis of uncertainty of national GHG emissions inventories, and in methods of assessing the inertia of a system given a time series of its observations (retrospective learning).
In 2008, Dr. Zebrowski graduated from the Institute of Mathematics and Computer Science, Faculty of Fundamental Problems of Technology, Wroclaw University of Technology, Poland. His specialization was the Financial and Actuarial Mathematics. In 2012, he completed his PhD studies in the Institute of Mathematics, Faculty of Mathematics and Computer Science, University of Wroclaw, Poland and obtained a PhD degree in mathematics. In his PhD dissertation Dr. Zebrowski explored a subject of weak convergence of continuous-time random walks with various spatio-temporal types of dependences. After completing his PhD studies, Dr. Zebrowski joined the Department of Probability Theory and Mathematics of Finance of the Institute of Mathematics of the Polish Academy of Sciences, where he worked as a research assistant in the fields of probability theory, stochastic processes and their applications in finance and statistical physics.
Last update: 14-JAN-2019
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. DOI: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. DOI: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 HP, Straka P, & Żebrowski P (2015). Limit theorems and governing equations for Levy walks. Stochastic Processes and their Applications 125 (11): 4021-4038. DOI: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
Cristino CT, Żebrowski P , & Wildemeersch M Assessing the time intervals between economic recessions. PLoS ONE 15 (5): e0232615. DOI:10.1371/journal.pone.0232615.
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