Displaying 10 of 612 results for "Lee-Ann Sutherland" clear search
Amin is a PhD student in the quantitative and systems biology graduate program at UC Merced. He has been passionate about entrepreneurship since his undergraduate years in his hometown of Isfahan and then later in Bologna, Italy, where he completed his masters. Once a recipient of the Innovators Under 35 Award in Italy, he believes there is massive opportunity for society to train and motivate younger minds to acquire an entrepreneurial mindset, along with entrepreneurship skills.
Entrepreneurship, management, mathematical modeling, agent based modeling.
My core research interest is to understand how humans and other living creature perceive and behave; respond and act upon their environment and how this dynamic interplay shapes us into who we are. In recognition of the broad scope of this question I am a strong believer in the need for inter- and multi-disciplinary approaches and have worked at research groups in a wide range of departments and institutions, including university departments of Physics as well as Psychology, a bio-medical research lab, a robotics research laboratory and most recently the RIKEN Brain Science Institute. Though my work has primarily taken the form of computational neuroscience I have also performed psychophysical experiments with healthy human subjects, been involved in neural imaging experiments and contributed towards the development of a humanoid robot.
Based on the philosophy of ‘understanding through creating’ I believe that bio-mimetic and biologically inspired computational and robotic engineering can teach us not only how to build more flexible and robust tools but also how actual living creatures deal with their environment. I am therefore a strong believer in the fertile information exchange between scientific as well as engineering research disciplines.
Currently Associate Professor of Anthropology, University of Colorado Colorado Springs. I took my first modelling class in Repast with Dr. Mark Lake as part of my M. Sc. at UCL. After a workshop with Dr. Luke Premo and Dr. Anne Kandler, I moved to NetLogo and haven’t looked back.
Find our recent textbook, Agent-based modeling for Archaeology: Simulating the Complexity of Societies here: https://santafeinstitute.github.io/ABMA/
I am a formally oriented philosopher, applying computational techniques to questions of social epistemology and political philosophy. My current research is focused on explanations and interventions for phenomena of collective irrationality.
My research is focused on the security of water, food, and energy resources as well as natural resources planning and managaement. A lot of my work involves the integration of physical and social science research.
Modeling and simulation of future impacts of information and communication technologies on environmental sustainability using agent based modeling and system dynamics
Research fellow, PhD Candidate (University of Kassel)
Energy system transiton modelling
* stakeholder and market modelling, governance and policy modelling,
* agent-based modelling (ABM), optimisation,
* model coupling, open and integrative modelling framework,
* open source, S4F
Peter Gerbrands is a Researcher at the of Utrecht University School of Economics, where is develops the data infrastructure FIRMBACKBONE. He teaches data science courses and econometrics as well as supervising bachelor, master, and Ph.D. theses. His research interests are agent-based simulations, social network analysis, complex systems, big data analysis, statistical learning, and computational social science. He applies his skills primarily for policy analysis, especially related to illicit financial flows, i.e. tax evasion, tax avoidance and money laundering and has published in Regulation & Governance, and EPJ Data Science. Prior to becoming an academic, Peter had a long career in IT consulting. In the Fall of 2023, he was a Visiting Research Scholar at SUNY Binghamton in NY.
agent-based simulations
social network analysis
complex systems
big data analysis
statistical learning
computational social science
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