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.
Behavioural aspects of environmental problems: Use of evolutionary approaches to investigate how people react to environmental policy.
Climate-economic Models: Understand how economic agents think and decide about climate change and climate protection
Modeling of Social Phenomena, Graph Algorithms, Opinion and Information Dynamics
Use of ABM in areas related to Systems Engineering and Automatic Control.
Main Research Topics :
1) Agent-based Modeling (Communication between agents)
2) Economic and Econometric Algorithms and Software Development
3) Optimal International Trade Configuration
Industrial Engineering, Multi-criteria Decision Making, Optimization Techniques, Global/International Facility Location, Agent-based Modeling
André Calero Valdez does research on Computational Communication Science investigating the influence of network structure and algorithms on communication flow using agent-based modeling.
I study small- and large-scale sustainable resource management using a variety of techniques including mathematical modeling, agent-based simulation, and Statistical Inference