Displaying 10 of 34 results for "Abraham Mawere Ndlovu" clear search
I am fascinated by unraveling water-scarcity patterns. I am an expert in Integrated Assessment Modelling and Water Footprint Assessment. The concepts and tools that I have developed and applied all aim at availing knowledge at scales relevant to decision-makers in the water sector. During my PhD at the University of Twente I evaluated how spatiotemporal patterns of water availability relate to patterns of water use for a river basin in the semi-arid Northeast of Brazil. I have used agent-based modelling and developed the downstreamness concept to analyze the emergence of basin closure. This concept is helpful to water managers for identifying priority locations for intervention inside a river basin system. As a postdoc I continued to evaluate the relation between water use and availability and further broadened my scope to a wider range of related topics.
Charlotte is an International PhD graduate originally from New Zealand who first came to ASU to pursue her PhD in Anthropology in Aug 2013, thanks to receiving a Science and Innovation Scholarship through the Fulbright Program. She holds a BS majoring in Genetics and a BA majoring in Anthropology from Otago University, New Zealand. She received her Masters in Anthropology in May 2015 and her PhD in Anthropology in 2022 both from ASU. Her main areas of interest are Human Migration, Migration Decision Making, and Environmental Perceptions.
At present she is an Assistant Research Scientist with the School of Complex Adaptive Systems at ASU where she is primarily focused on her roles as the administrative coordinator for CoMSES.NET and The Open Modeling Foundation. She is also adjunct Anthropology faculty at Phoenix College, and Chandler-Gilbert Community College teaching various undergraduate anthropology courses. She is deeply interested in how computational tools and technologies can be used to explore complex adaptive systems, explore possible futures, and better inform policy and decision makers at the leading edge of change.
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.
Alma Mater: FT Ranked No. 10 Business Economics school.
Ranked No 1 in an engineering mathematics national level test.
Ranked No 1 in an analytics program at IIT Bombay.
B.E. Mechanical Engineering.
MTech 1st year Modelling and Simulation.
PhD 1st year Strategy Simulation at The University of Texas at Dallas.
Tuition scholarships at the Santa Fe Institute.
GMAT 730
5 years of operations research work experience.
Published and presented a poster at the The Operational Research Society, UK Annual Conference 2021 integrating strategy and applied math. Took on and resolved a longstanding problem.
Solo authored leadership article in the Analytics magazine Nov/Dec 2021 issue from INFORMS.
Solo authored theoretical optimization abstract at the ICORES 2022 Conference.
Authoring the black-tie, board room manual - The Change Management Series Volume 1 Kindle edition on Amazon March, 2022.
I am a participant at the Financial Modeling World Cup 2022.
Build spiders for scraping web data.
Agent-based computer simulation in strategy, the resource-based view in strategy, agency theory and top & middle management incentives, organizational economics, algorithmic game theory, financial friction, financial econometrics.
As of my incorporation into the Department of Computer Architecture and Operating Systems of the UAB as a postgraduate student, it is possible to divide my scientific-technical career into the following stages:
Simulation of Parallel Applications (1992-99): Focused on the design and development of simulators of parallel applications. This research main objective was the definition of abstractions for parallel programs, based on characterizing tasks and their dependences. Two main abstractions were developed, at first a simpler one, which was easier to parametrize, and, next, a more complex an accurate one. Using these characterizations, several simulation tools were programmed and used in the context of national and European projects. As part of my Master’s thesis, I was involved in the design and development of some of these simulation applications.
National projects: 4, European: 2
International conferences: 3, National: 1, Journal papers: 3
Security in Distributed Systems (2007-12): Focused on the design and development of the FPVA (First Principles Vulnerability Assessment) methodology for the evaluation of vulnerabilities in Grid applications. This methodology clearly defined a set of steps for the assessment of Grid applications vulnerabilities, most of these steps could be automatized or at least supported by specific tools. Jointly with other professors of our group and from the University of Wisconsin, I was involved in the original definition and application of this methodology.
International projects: 2
Master Thesis: 1, Ph.D. Thesis: 1
International conferences: 2, National: 1, Journal papers: 2
Parallel Application Modeling (1999-present): This is my main line of research, aimed at defining high-level performance models for parallel applications. Initially, models were defined for MPI applications with a master-worker and pipeline structure, but later this line has been expanded with the definition of models for memory-intensive OpenMP applications, composed (mix of several structures) applications, applications based on mathematical libraries, distributed data-intensive applications and, finally, applications based on the simulation of agents (ABS) with SPMD structure.
As a result of the work on modeling the performance of ABS parallel systems, we have opened a new line for the definition and implementation of a benchmark for assessing the performance of the parallel simulators generated by well-known platforms, such as FLAME, Repast-HPC or D-Mason. In addition, the knowledge we have gained on this topic has opened new ways of collaboration for optimizing real parallel ABS in the health sciences area (tumor growth and infection spread).
National projects: 12, European: 1
International conferences: 17, National: 4, Journal papers: 11
International Presentations: 4
Parallel Applications Tuning Tools (2010-present): Focused on the design and development of tools for automatic tuning and, in some cases, also dynamic tuning of parallel applications. These tools allow the integration of performance models in the form of external components provided by the analyst. For this reason, this research line is tightly coupled with the Parallel Application Modeling one. The two main tools developed totally or partially by our group are Monitoring Analysis and Tuning Environment-MATE (and its highly scalable evolution ELASTIC) and Periscope Tuning Framework-PTF.
National projects: 2, European: 1
International conferences: 11, Journal papers: 2
Tools: MATE, ELASTIC, PTF
International Presentations: 5
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).
1987-1989: assistant professor at the Neuchâtel University (Switzerland)
1990-2001: full professor at the Neuchâtel University (Switzerland): artificial intelligence & software engineering
2001- : senior researcher at CIRAD in the unit “Gestion des Ressources et Environnement” (GREEN) and from 2021 “Savoirs ENvironnement Sociétés” (UMR SENS)
Former professor at the University of Neuchatel in Switzerland and now senior researcher at CIRAD in France, I am doing research on artificial intelligence since 1984. Having begun with logic programming, I naturally applied logics and its extensions (i.e. modal logics of various sorts) to specify agent behaviour. Since 1987, I moved both to embedded intelligence (using mobile robots) and multi-agent systems applied, in particular, to job-shop scheduling and complex system simulation and design. Since 2001, I exclusively work on modelling and simulation of socio-ecosystems in a multidisciplinary team on renewable resources management (GREEN). I am focusing on modelling complex systems in a multi-disciplinary (economist, agronomist, sociologists, geographers, etc.) and multi-actor (stakeholders, decision makers) setting. It includes:
- representing multiple points of view at various scales and levels on a complex socio-ecosystem, using ontologies and contexts
- representing the dynamics of such systems in a variety of formalisms (differential equations, automata, rule-based systems, cognitive models, etc.)
- mapping these representations into a simulation formalism (an extension of DEVS) for running experiments and prospective analysis.
This research is instantiated within a modelling and simulation platform called MIMOSA (http://mimosa.sourceforge.net). The current applications are the assessment of the sustainability of management transfer to local communities of the renewable ressources and the dynamics of agro-biodidversity through networked exchanges.
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
Social network analysis has an especially long tradition in the social science. In recent years, a dramatically increased visibility of SNA, however, is owed to statistical physicists. Among many, Barabasi-Albert model (BA model) has attracted particular attention because of its mathematical properties (i.e., obeying power-law distribution) and its appearance in a diverse range of social phenomena. BA model assumes that nodes with more links (i.e., “popular nodes”) are more likely to be connected when new nodes entered a system. However, significant deviations from BA model have been reported in many social networks. Although numerous variants of BA model are developed, they still share the key assumption that nodes with more links were more likely to be connected. I think this line of research is problematic since it assumes all nodes possess the same preference and overlooks the potential impacts of agent heterogeneity on network formation. When joining a real social network, people are not only driven by instrumental calculation of connecting with the popular, but also motivated by intrinsic affection of joining the like. The impact of this mixed preferential attachment is particularly consequential on formation of social networks. I propose an integrative agent-based model of heterogeneous attachment encompassing both instrumental calculation and intrinsic similarity. Particularly, it emphasizes the way in which agent heterogeneity affects social network formation. This integrative approach can strongly advance our understanding about the formation of various networks.
I studied Mathematics at Oxford (1979-1983) then did youth work in inner city areas for the Educational Charity. After teaching in Grenada in the West Indies we came back to the UK, where the first job I could get was in a 6th form college (ages 16-18). They sent me to do post16 PCGE, which was so boring that I also started a part-time PhD. The PhD was started in 1992 and was on the meaning and definition of the idea of “complexity”, which I had been pondering for a few years. Given the growth of the field of complexity from that time, I had great fun reading almost anything in the library but I did finally finish it in 1999. Fortunately I got a job at the Centre for Policy Modelling (CfPM) in 1994 with its founder and direction, Scott Moss. We were doing agent-based social simulation then, but did not know it was called this and did not meet other such simulators for a few years. With Scott Moss we built the CfPM into one of the leading research centres in agent-based social simulation in the world. I became director of the CfPM just before Scott retired, and later became Professor of Social Simulation in 2013. For more about me see http://bruce.edmonds.name or http://cfpm.org.
All aspects of social simulation including: techniques, tools, applications, philosophy, methodology and interesting examples. Understanding complex social systems. Context-dependency and how it affects interaction and cognition. Complexity and how this impacts upon simulation modelling. Social aspects of cognition - or to put it another way - the social embedding of intelligence. Simulating how science works. Integrating qualitative evidence better into ABMs. And everything else.
Displaying 10 of 34 results for "Abraham Mawere Ndlovu" clear search