System of Systems and Complex Systems
Using the Complex System science paradigm to open new ways of assessing the Systemic Risk in Financial Systems
Master student in Sustainable Development at Uppsala University
Postdoctoral researcher at Institute of Economics, Polish Academy of Sciences and in Macroprudential Research Division at National Bank of Poland. She graduated in Mathematics (Jagiellonian University, Poland) and in Economics (University of Alcala, Spain). In 2017 she obtained Fulbright Advanced Research Award. In the United States, she carried out research on systemic risk and complex systems. Her doctoral dissertation was about the measurement and modeling of systemic risk using simulation methods and complex systems approach (the results to be published by Palgrave Macmillan US). Previously, she gained experience on agent-based modeling while working with Juan Luis Santos on the European Commission FP 7 MOSIPS project (http://www.mosips.eu/).
Mathematics, complex systems, financial modeling, agent-based modeling, econometrics, macroprudential policies, systemic risk, cental banking
My field of interests concerns two axes:
First, epistemology of computational modeling and simulation of complex systems. I am particularly interested in a sociological inquiry about social implication of knowledge derived from complex systems’ study.
Second, assessing the possibilities and limits of studying social complexity with complex systems tools, particularly, agent-based modeling and simulation.
Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.
Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory
Multi-agent Systems, Agent Based Modeling, Artificial Intelligence
Representations in C2 systems