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Dr. Piotr Żebrowski joined IIASA’s Advanced Systems Analysis (ASA) Program as a Research Assistant in February 2015.
In 2008, he graduated from the Institute of Mathematics and Computer Science, Faculty of Fundamental Problems of Technology, Wrocław University of Technology, Poland. His specialization is Financial and Actuarial Mathematics. In 2012, he completed his PhD studies in the Institute of Mathematics, Faculty of Mathematics and Computer Science, University of Wrocław, Poland and obtained a PhD degree in mathematics. In his dissertation Dr. Żebrowski explored a subject of weak convergence of continuous-time random walks with various spatio-temporal types of dependences. After completing his PhD studies, Dr. Żebrowski worked as a Research Assistant in the Department of Probability Theory and Mathematics of Finance, Institute of Mathematics, Polish Academy of Sciences.
Prior to joining IIASA, Dr. Żebrowski worked in the fields of probability theory, stochastic processes and their applications in finance and statistical physics. His current research focus on uncertainty propagation in climate models and on retrospective learning.
Last update: 25-MAR-2015
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
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