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Senior Researcher at Helmholtz Centre for Environmental Research - UFZ in Leipzig, Germany
Since 2022 Professorship for Modelling of Human-Environment Systems, Joint appointment of Brandenburg University of Technology Cottbus-Senftenberg and UFZ
PhD in Applied System Science, University of Osnabrück
Diploma in Business Mathematics, University of Leipzig
I am currently head of the Working Group POLISES which uses agent-based models to study the impact of policies on land user behavior and consequences on the social-ecological system. This includes agri-environmental schemes for European agriculture and climate related policies such as insurance. In prior projects we investigated intended and unintended effects of global policy instruments on the social-ecological resilience of smallholders. We focused on the impact of policies targeting climate risk in common property regimes of pastoralists in Africa (Morocco and Kenya/Ethiopia).
On a conceptual level, I work in an international team of modellers, psychologists, agroeconomists and natural scientists on adequate representations of human behaviour in agent-based models. Furthermore, I am interested in how to describe models in an appropriate and standardised manner to increase their comprehensibility and comparison and how to foster model reuse and building up on each others work.
I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.
Using the Complex System science paradigm to open new ways of assessing the Systemic Risk in Financial Systems
System of Systems and Complex Systems
Dr. Mariam Kiran is a Research Scientist at LBNL, with roles at ESnet and Computational Research Division. Her current research focuses on deep reinforcement learning techniques and multi-agent applications to optimize control of system architectures such as HPC grids, high-speed networks and Cloud infrastructures.. Her work involves optimization of QoS, performance using parallelization algorithms and software engineering principles to solve complex data intensive problems such as large-scale complex decision-making. Over the years, she has been working with biologists, economists, social scientists, building tools and performing optimization of architectures for multiple problems in their domain.
The aim of this project is to complement the approach developed by UMR-Geographie-Cité (“SimPop” Models), using an approach based on the organization and deployment of multinational corporation networks in urban system. We will simulate the interactions between networks of multinational corporation and the urban system.
Community assembly after intervention by coral transplantation
The potential of transplantation of scleractinian corals in restoring degraded reefs has been widely recognized. Levels of success of coral transplantation have been highly variable due to variable environmental conditions and interactions with other reef organisms. The community structure of the area being restored is an emergent outcome of the interaction of its components as well as of processes at the local level. Understanding the
coral reef as a complex adaptive system is essential in understanding how patterns emerge from processes at local scales. Data from a coral transplantation experiment will be used to develop an individual-based model of coral community development. The objectives of the model are to develop an understanding of assembly rules, predict trajectories and discover unknown properties in the development of coral reef communities in the context of reef restoration. Simulation experiments will be conducted to derive insights on community trajectories under different disturbance regimes as well as initial transplantation configurations. The model may also serve as a decision-support tool for reef restoration.
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