I study small- and large-scale sustainable resource management using a variety of techniques including mathematical modeling, agent-based simulation, and Statistical Inference
I have developed several agent-based and cellular automata applications combining agent-based modelling, geographical information systems and visualisation to understand the complex mechanisms of decision making in land use change and environmental stewardship in order to analyse:
• the role of pastoral agriculture in regional development,
• the tradeoffs between land use intensification and water quality,
• the adoption of land-based climate change mitigation practices, and
• the incorporation of cultural values into spatial futures or scenario modelling.
Use of ABM in areas related to Systems Engineering and Automatic Control.
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.
Industrial Engineering, Multi-criteria Decision Making, Optimization Techniques, Global/International Facility Location, Agent-based Modeling
Analyzing economic dynamics through game theory and agent based evolutionary models. My research topics go from dynamics of organizations to industrial dynamics, macroeconomic dynamics and economic policy analysis.
Modeling of Social Phenomena, Graph Algorithms, Opinion and Information Dynamics