As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.

Direction of the Vector-Borne Disease Network (www.vecnet.org), an international research consortium developing modeling tools that support the development of new strategies to eliminate malaria.

• Agent-Based Modeling, Geosimulation
• labor market policy evaluation
• economic forecasting

My research is focused on autonomous agents and multiagent systems. Specifically: Trust and reputation models, cognitive architectures, cognitive models and social simulation.

Research focuses on the coupled dynamics of human and natural systems, specifically in the context of forest dynamics. I utilize a variety of modeling and analysis techniques, including agent-based modeling, cellular automata, machine learning and various spatial statistics and GIS-related methods. I am currently involved in projects that investigate the anthropogenic and biological drivers behind native and invasive forest pathogens and insects.

• societal transitions under climate change
• models as learning tools
• communication of scientific results and uncertainties to decision makers
• efficient information processing and knowledge management in science

Agent-based computing in economics and finance
Large-scale agent-based models
Agent models calibrated by micro-data
Complex adaptive systems
Mathematical analysis of agent systems