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Agent-based modeling in political science
Research Assistant Professor at the Virginia Modeling, Analysis and Simulation Center at Old Dominion University. I work in the Storymodelers research group at VMASC where we use computational modeling approaches to try to understand complex social issues. Our main project is currently focused on modeling the dynamics of how host communities respond to the rapid influx of forced migrants.
I am an Associate Professor of Industrial Engineering with over two decades of experience in teaching, research, and supervision in data-driven decision making, operations research, and computational modeling. My research integrates Multi-Criteria Decision Analysis (MCDA), Agent-Based Modeling (ABM), and Reinforcement Learning (RL) to support strategic decision systems in sustainability, investment, and industrial operations. My recent work explores human-centric and multi-actor systems, leveraging simulation-based optimization and AI-driven analytics to enhance resilience, efficiency, and sustainability in complex socio-technical environments. I have published extensively in international journals, reviewed over 75 manuscripts, and am an active member of INFORMS and the System Dynamics Society. My long-term goal is to bridge industrial systems modeling with intelligent decision support, aligning academic research with real-world sustainability and innovation challenges.
đš Experience
Associate Professor â Industrial Engineering, University of Engineering and Technology, Taxila (2018 â Present)⢠Teach graduate and undergraduate courses in Operations Research, Data Mining, Advanced Statistics, System Simulation, and Soft Computing.⢠Conduct funded research in agent-based and reinforcement learning models for sustainable and data-driven decision systems.⢠Supervise doctoral students in decision analytics, multi-agent modeling, and MCDM applications.⢠Reviewer for international journals including Neural Computing and Applications, the Journal of Cleaner Production, Annals of Operations Research, Environment, Development and Sustainability, Energy for Sustainable Development, Scientific Reports, IEEE Access, Cleaner Energy Systems, Utilities Policy, and Sustainable Futures
đš Research Interestsâ˘
Data-Driven Decision Making⢠Agent-Based Modeling (ABM)⢠Reinforcement Learning (RL)⢠Multi-Criteria Decision Analysis (MCDA / MAMCA)⢠Sustainable Supply Chains⢠System Dynamics; Simulation⢠E-Health and Humanitarian Systems
đš Selected Achievementsâ˘
30+ peer-reviewed publications; ~360+ citations⢠Reviewer for 75+ international journal papers⢠Completed Coursera Specializations in Machine Learning, Deep Learning, and Reinforcement Learning⢠20+ years of experience integrating data science with sustainability modeling
Data-Driven Decision Making | Agent-Based & Reinforcement Learning Models | Multi-Criteria Decision Analysis | Sustainable Systems | Operations Research | Netlogo | R
I have a strong background in building and incorporating agent-based simulations for learning. Throughout my graduate career, I have worked at the Center for Connected Learning and Computer Based Modeling (CCL), developing modeling and simulation tools for learning. In particular, we develop NetLogo, the gold standard agent-based modeling environment for learners around the world. In my dissertation work, I marry biology and computer science to teach the emergent principles of ant colonies foraging for food and expanding. The work builds on more than a decade of experience in ABM. I now work at the Center for the Science and the Schools as an Assistant Professor. We delivered a curriculum to teach about COVID-19, where I incorporated ABMs into the curriculum.
You can keep up with my work at my webpage: https://kitcmartin.com
Studying the negative externalities of networks, and the ways in which those negatives feedback and support the continuities.
Development and usage of demographic microsimulation tools and applications, in particular combining statistical modeling and social theory
Associate Professor
School of Management Science and Engineering, Shandong Technology and Business University (Yantai 264005, P. R. China)
Ph. D. Degree, 09/2009 â 07/2015
School of Economics and Management, Beihang University (P. R. China)
M. A. Degree, 09/2003 â 02/2006
The Institute of Systems Engineering, Dalian University of Technology (P. R. China)
B. A. Degree, 09/1999 â 07/2003
Department of Information and Control Engineering, Zhengzhou University of Light Industry (P. R. China)
Visiting Scholar at GECS â Research Group of Experimental and Computational Sociology (March, 2017 â February, 2018)
ď UniversitĂ degli Studi di Brescia (Italy)
ď Co-supervisor: Professor Flaminio Squazzoni
Summer school in âAgent-based modeling for social scientistsâ (September 4-8, 2017)
ď University of Brescia, Italy
ď Instructors: Flaminio Squazzoni, Simone Gabbriellini, Nicolas Payette, Federico Bianchi
The Santa Fe Institute’s Massive Open Online Course: Introduction to Agent-Based Modeling (Jun 5 â September 8, 2017)
ď The Santa Fe Institute, Complexity Explore Web: abm.complexityexploer.org
ď Instructors: Bill Rand
Summer school in âComplex systems and managementâ (July 2-12, 2012)
ď National Defense University, P. R. China
ď Instructors: Xinjun Mao, Yongfang Liu, Dinghua Shi, Qiyue Cheng
Routine dynamics, Agent-based modeling, Computational social/organization science, Industrial systems engineering, etc.
Currently working on agent-based modeling of wealth and income distributions; formalizing some of Luhmann’s theories of communication; modeling social norms; and modeling generative mechanisms of status hierarchies.
Sae Schatz, Ph.D., is an applied humanâsystems researcher, professional facilitator, and cognitive scientist. Her work focuses on humanâsystems integration (HSI), with an emphasis on human cognition and learning, instructional technologies, adaptive systems, human performance assessment, and modeling and simulation (M&S). Frequently, her work seeks to enhance individualâs higher-order cognitive skills (i.e., the mental, emotional, and relational skills associated with âcognitive readinessâ).
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 smallholderâs 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.
I am Professor of Management at Paris School of Business and have held positions at the University of Southern Denmark, Bournemouth University (UK), University of Wisconsin (US), and at the University of Insubria (Italy). My current research efforts are on socially-based decision making, agent-based modeling, cognitive processes in organizations and socially responsible behavior in organizations. With a coauthor network of 50 colleagues located in over 10 different countries, I have published 126 (as of 2025) among articles, book chapters, and books. The monograph Computational organizational cognition (2021, Emerald), and the edited Agent-Based Simulation of Organizational Behavior with M. Neumann (2016, Springer Nature) specifically target computational simulation research in the social sciences. The book How do I Develop an Agent-Based Model? (2022, Elgar) is the first specifically written for business and management scholars.
My simulation research focuses on the applications of ABM to organizational behavior studies. I study socially-distributed decision makingâi.e., the process of exploiting external resources in a social environmentâand I work to develop its theoretical underpinnings in order to to test it. A second stream of research is on how group dynamics affect individual perceptions of social responsibility and on the definition and measurement of individual social responsibility (I-SR).
Displaying 10 of 189 results modeling clear search