Agent based modelling;
Land use/land cover change;
Payment for ecosystem services;
Agent Based Modeling (ABM), Agent Based Social System (ABSS), Multi-Agent Systems (MAS), Bayesian learning, Social networks Analysis (SNA), Socio ecological Dynamics.
Interested in IWRM approach, analyzing coupled human-water relationship, Hydrological modelling, Bayesian networks, Agent based modelling
Using Bayesian statistics for improving Agent based models and visa versa.
I am a data scientist employing a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I am also working to apply Science and Technology Studies to my modeling processes in order to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling, both teaching mapping and modeling skills as well as analyzing and synthesizing community-held data as appropriate. At the same time, I look for ways to create space for qualitative and other forms of knowledge to reside alongside quantitative analysis. Recent projects include: 1) studying Californian forest dynamics using Bayesian statistical models and object-based image analysis (datasets included forest inventories and historical aerial photographs); 2) indigenous mapping and community-based modeling of agro-pastoral systems in rural Zimbabwe (methods included GPS/GIS, agent-based modeling and social network analysis).
For my Ph.D. thesis, I developed a system to play poker.
I’m interested to see whether a similar approach can be applied to agent based models.
My research interests include policy informatics and decision making, modeling in policy analysis and management decisions, public health management and policy, and the role of public value in policy development. I am particularly interested in less mainstream approaches to modeling that account for learning, feedback, and other systems dynamics. I include Bayesian inference, agent-based models, and behavioral assumptions in both my research and teaching.
In my dissertation research, I conceptualize state Medicaid programs as complex adaptive systems characterized by diverse actors, behaviors, relationships, and objectives. These systems reproduce themselves through both strategic and emergent mechanisms of program management. I focus on the mechanism by which citizens are sorted into or out of the system: program enrollment. Using Bayesian regression and agent-based models, I explore the role of administrative practices (such as presumptive eligibility and longer continuous eligibility periods) in increasing enrollment of eligible citizens into Medicaid programs.
Down Networks is a real time, progressively agile non profit startup whose goals are to fund its research via pragmatically aggressive altruistic entrepreneurial pursuits informed by proprietary in-house techniques, open source technology and refined scientific methodology.
Mainly interested in studying social networks of learners, teachers, and innovators. Uses Social Network Analysis, but also sentiment analysis, data mining, and recommender system techniques.