Displaying 10 of 101 results for "Alison Heppenstall" clear search
I studied Molecular Biology and Genetics at Istanbul Technical University. During my undergraduate studies I became interested in the field of Ecology and Evolution and did internships on animal behaviour in Switzerland and Ireland. I then went on to pursue a 2-year research Master’s in Evolutionary Biology (MEME) funded by the European Union. I worked on projects using computer simulations to investigate evolution of social complexity and human cooperation. I also did behavioural economics experiments on how children learn social norms by copying others. After my Master’s, I pursued my dream of doing fieldwork and investigating human societies. I did my PhD at UCL, researching cultural evolution and behavioural adaptations in Pygmy hunter-gatherers in the Congo. During my PhD, I was part of an inter-disciplinary Hunter-Gatherer Resilience team funded by the Leverhulme Trust. I obtained a postdoctoral research fellowship from British Academy after my PhD. I am currently working as a British Academy research fellow and lecturer in Evolutionary Anthropology and Evolutionary Medicine at UCL.
Modeling land use change from smallholder agricultural intensification
Agricultural expansion in the rural tropics brings much needed economic and social development in developing countries. On the other hand, agricultural development can result in the clearing of biologically-diverse and carbon-rich forests. To achieve both development and conservation objectives, many government policies and initiatives support agricultural intensification, especially in smallholdings, as a way to increase crop production without expanding farmlands. However, little is understood regarding how different smallholders might respond to such investments for yield intensification. It is also unclear what factors might influence a smallholder’s land-use decision making process. In this proposed research, I will use a bottom-up approach to evaluate whether investments in yield intensification for smallholder farmers would really translate to sustainable land use in Indonesia. I will do so by combining socioeconomic and GIS data in an agent-based model (Land-Use Dynamic Simulator multi-agent simulation model). The outputs of my research will provide decision makers with new and contextualized information to assist them in designing agricultural policies to suit varying socioeconomic, geographic and environmental contexts.
Primate evolutionary biologist and geneticist at the University of Texas at Austin
I conduct long-term behavioral and ecological field research on several species in the primate community of Amazonian Ecuador to investigate the ways in which ecological conditions (such as the abundance and distribution of food resources) and the strategies of conspecifics together shape primate behavior and social relationships and ultimately determine the kinds of societies we see primates living in. This is a crucial and central focus in evolutionary anthropology, as understanding the ways in which behavior and social systems are shaped by environmental pressures is a fundamental part of the discipline.
I complement my field studies with molecular genetic laboratory work and agent-based simulation modeling in order to address issues that are typically difficult to explore through observational studies alone, including questions about dispersal behavior, gene flow, mating patterns, population structure, and the fitness consequences of individual behavior. In collaboration with colleagues, I have also started using molecular techniques to investigate a number of broader questions concerning the evolutionary history, social systems, and ecological roles of various New World primates.
Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.
Angelos Chliaoutakis received his PhD in Electronic & Computer Engineering in 2020 at Technical University of Crete (TUC), Greece. During 2005-2020 he was a research assistant at the Intelligent Systems Laboratory of TUC, participating in several research projects associated with NLP, semantic similarity and ontology based information systems. Since 2010 he is also a research assistant at the Laboratory of Geophysical - Satellite Remote Sensing and Archaeo-environment (GeoSat ReSeArch Lab) of the Institute for Mediterranean Studies of Foundation for Research and Technology (IMS-FORTH), were he is involved in various research projects related to the full-stack development of Geographical Information Systems (GIS), web-based GIS applications and Geoinformatics in the cultural and archaeological domain. This ultimately transformed his interest and research direction towards computational archaeology, in particular, agent-based modeling and simulation, while intertwining ideas and approaches from Artificial Intelligence, Multi-agent Systems and GIS.
Research activities range between Computer Science, Information Systems and Natural Language Processing (NLP), Agent-based modeling/simulation (ABM), Artificial Intelligence (AI) and Multi-Agent Systems (MAS) and Geographical Information Science (GIScience).
Dr. Roger Cremades is a complex systems scientist and heterodox global change economist integrating human-Earth interactions across systems and scales into modular quantitative tools, e.g. connecting drought risks in cities with land use at the river basin scale. He is elected Council member of the Complex Systems Society (2022-2025) and previously served as co-Chair of the Development Team of the Finance and Economics Knowledge-Action Network of Future Earth, the largest global research programme in global change (2020-2022). Roger coordinated research and co-production projects above €1M, and published in top journal like PNAS, Nature Climate Change, and Nature Geoscience. As a scientific modeler in the Social and Ecological Sciences, Roger integrates complex systems concepts into integrated assessment models of global change, with a focus on cities.
The future of CoMSES.Net, in Roger’s vision, is to augment its projection into a hub for discussing state-of-the-art approaches on modeling for the Social and Ecological Sciences, e.g. via bi-annual webinars, so that the Model Library becomes a lighthouse from where all communities developing, sharing, using, and reusing agent-based and other computational models also find valuable discussions to advance their research, education, and computational practice.
Global change, human-Earth interactions, complex systems.
As a data scientist, I employ a variety of ecoinformatic tools to understand and improve the sustainability of complex social-ecological systems. I also apply Science and Technology Studies lenses to my modeling processes in order to see potential ways to make social-ecological system management more just. I prefer to work collaboratively with communities on modeling: teaching mapping and modeling skills, collaboratively building data representations and models, and 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, using mixed and integrative methods.
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); 3) Supporting Tribal science and environmental management on the Klamath River in California using historical aerial image analysis of land use/land cover change and social networks analysis of water quality management processes; 4) Bayesian statistical modeling of community-collected data on human uses of Marine Protected Areas in California.
My primary research interests lie at the intersection of two fields: evolutionary computation and multi-agent systems. I am specifically interested in how evolutionary search algorithms can be used to help people understand and analyze agent-based models of complex systems (e.g., flocking birds, traffic jams, or how information diffuses across social networks). My secondary research interests broadly span the areas of artificial life, multi-agent robotics, cognitive/learning science, design of multi-agent modeling environments. I enjoy interdisciplinary research, and in pursuit of the aforementioned topics, I have been involved in application areas from archeology to zoology, from linguistics to marketing, and from urban growth patterns to materials science. I am also very interested in creative approaches to computer science and complex systems education, and have published work on the use of multi-agent simulation as a vehicle for introducing students to computer science.
It is my philosophy that theoretical research should be inspired by real-world problems, and conversely, that theoretical results should inform and enhance practice in the field. Accordingly, I view tool building as a vital practice that is complementary to theoretical and methodological research. Throughout my own work I have contributed to the research community by developing several practical software tools, including BehaviorSearch (http://www.behaviorsearch.org/)
I am a scientist at the Johns Hopkins Applied Physics Laboratory. Previously, I worked for the Board of Governors of the Federal Reserve System as an internal consultant on statistical computing. I have also been a consultant to numerous government agencies, including the Securities and Exchange Commission, the Executive Office of the President, and the United States Department of Homeland Security. I am a passionate educator, teaching mathematics and statistics at the University of Maryland University College since 2010 and have taught public management at Central Michigan University, Penn State, and the University of Baltimore.
I am fortunate to play in everyone else’s backyard. My most recent published scholarship has modeled the population of Earth-orbiting satellites, analyzed the risks of flood insurance, predicted disruptive events, and sought to understand small business cybersecurity. I have written two books on my work and am currently co-editing two more.
In my spare time, I serve Howard County, Maryland, as a member of the Board of Appeals and the Watershed Stewards Academy Advisory Committee of the University of Maryland Extension. Prior volunteer experience includes providing economic advice to the Columbia Association, establishing an alumni association for the College Park Scholars Program at the University of Maryland, and serving on numerous public and private volunteer advisory boards.
I’ve been building cyberinfrastructure and research software for computational social science and the study of complex adaptive systems at Arizona State University since 2006. Past and current projects include the Digital Archaeological Record, the Virtual Commons, the Social Ecological Systems Library, Synthesizing Knowledge of Past Environments (SKOPE), the Port of Mars, and CoMSES Net, where I serve as co-director and technical lead.
I also work to improve the state of open, transparent, reusable, and reproducible computational science as a Carpentries instructor and maintainer for the Plotting and Programming in Python and Good Enough Practices for Scientific Computing lessons, currently co-chair the Consortium of Scientific Software Registries and Repositories and Open Modeling Foundation Cyberinfrastructure Working Group, and serve on the DataCite Services and Technology Steering Group and CSDMS’s Basic Model Interface open source governance council.
My research interests include collective action, social ecological systems, large-scale software systems engineering, model componentization and coupling, and finding effective ways to promote and facilitate good software engineering practices for reusable, reproducible, and interoperable scientific computation.
Displaying 10 of 101 results for "Alison Heppenstall" clear search