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Ecological modelling
Social Ecnomic/ecological complexity
Human behavioral ecology, marine ecology, cognitive sciences, decision making under uncertainty
Using agent based models to look at ecosystem-based or integrated management of oceans and coastal zones
Archaeological Simulation of Social Interactions, mainly between hunter gatherers societies.
Modelling of socio-ecological systems and management of common property resources in artisanal fisheries. Population dynamics of coastal marine invertebrates exploited by artisanal fisheries.
Main Research Topics :
1) Agent-based Modeling (Communication between agents)
2) Economic and Econometric Algorithms and Software Development
3) Optimal International Trade Configuration
I’m a Senior Fellow at Fors Marsh who has a PhD in Industrial-Organizational Psychology and a PStat accreditation by the American Statistical Association.
Career Progression; Job Characteristics; Occupational Stress and Health
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.
I am a Ph.D. candidate in Computational Social Science (CSS) program at George Mason (GMU). I hold a MAIS from GMU and a Bachelor of Economics from the University of Tasmania. My research interests are the application of ABMs, network analysis, and machine learning to financial markets. My email address and website is [email protected] and www.aussiecas.com
I am interested in using agent-based model to understand the behavior of financial markets
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