The goal of my research program is to improve our understanding about highly integrated natural and human processes. Within the context of Land-System Science, I seek to understand how natural and human systems interact through feedback mechanisms and affect land management choices among humans and ecosystem (e.g., carbon storage) and biophysical processes (e.g., erosion) in natural systems. One component of this program involves finding novel methods for data collection (e.g., unmanned aerial vehicles) that can be used to calibrate and validate models of natural systems at the resolution of decision makers. Another component of this program involves the design and construction of agent-based models to formalize our understanding of human decisions and their interaction with their environment in computer code. The most exciting, and remaining part, is coupling these two components together so that we may not only quantify the impact of representing their coupling, but more importantly to assess the impacts of changing climate, technology, and policy on human well-being, patterns of land use and land management, and ecological and biophysical aspects of our environment.
To achieve this overarching goal, my students and I conduct fieldwork that involves the use of state-of-the-art unmanned aerial vehicles (UAVs) in combination with ground-based light detection and ranging (LiDAR) equipment, RTK global positioning system (GPS) receivers, weather and soil sensors, and a host of different types of manual measurements. We bring these data together to make methodological advancements and benchmark novel equipment to justify its use in the calibration and validation of models of natural and human processes. By conducting fieldwork at high spatial resolutions (e.g., parcel level) we are able to couple our representation of natural system processes at the scale at which human actors make decisions and improve our understanding about how they react to changes and affect our environment.
land use; land management; agricultural systems; ecosystem function; carbon; remote sensing; field measurements; unmanned aerial vehicle; human decision-making; erosion, hydrological, and agent-based modelling
Research fellow at the Agricultural Economics and Policy Group at ETH Zurich.
I am interested in modeling social behavior. I have been working in the field of labor economics and industrial relations and how micro-simulations determine aggregate outcomes.
Master student in Sustainable Development at Uppsala University
I am investigating the use of machine learning techniques in non-stationary modeling environments to better reproduce aspects of human learning and decision-making in human-natural system simulations.
ABM applied to socio-economic systems: opinion evolution, industry dynamics, spatial models of voting, diffusion of innovations, macroeconomic with microfoundations, etc.
I have only just started becoming active in research/agent based modeling.
I find agent based computational economics interesting. I would also be interested in combining agent based modeling to explore cultural anthropology, government policies, socioeconomic stratification, and the diffusion of information.
Intrapreneur and experienced Consultant with a demonstrated history in the energy industry. Skilled in Business Planning, Corporate Finance, Digital Transformation and Analytics. Strong consulting professional focused in Organizational Development and Project Management. I have a degree in Industrial Engineering from the Rio de Janeiro State University (2000) and a master’s degree in Economics from Brazilian Institute of Capital Markets IBMEC (2003). Has experience in the area of Computer Science, with emphasis on Modeling of Complex Systems.