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I study human dimensions of natural resource management and resource use by under-represented populations—often in developing nations—to enhance our understanding of conflicts involving land use, natural resources, and conservation from an interdisciplinary, systematic lens. My research spans subjects such as common pool resource management and policy, decentralization, and land use/land cover change drivers and trends relating to population rise and environmental change.
Dr. Morteza Mahmoudzadeh is an assitant professor at the University of Azad at Tabriz in the Department of Managent and the director of the Policy Modeling Research Lab. Dr. Mahmoudzadeh did a degree in Software Engineering and a PhD in System Sciences. Dr. Mahmoudzadeh currently works on different regional and national wide projects about modeling sustaiblity and resilience of industrial ecosystems, innovation networks and socio-environmental systems. He also works on hybrid models of opinion dynamics and agent based models specifically in the field of modeling customers behavior and developing managerial tools for strategic marketing policy testing. His team at Policy Modeling Research Lab. currently work on developing a web based tool with python for systems modeling using system dynamics, Messa framework for agent-based modeling and Social Networks Analysis.
Modeling Complex systems, Simulation: System Dynamics, Agent Based and Discrete Event
System and Complexity Theory
I am an assistant professor in the Department of Computer Science at the Hamedan University of Technology, Hamedan, IRAN. I have completed my Ph.D. in Futures Studies (foresight) as an interdisciplinary field, an intersection of social sciences and engineering. My
background comes from computer science. For my Ph.D., I decided to pursue my education in Futures Studies; the field I thought I could apply engineering principles such as requirements engineering, analytical skills, design, modeling, planning, and, test engineering to shape the
desired futures. In PhD, I started the complex systems research field and agent-based modeling with NetLogo. In addition to several publications of papers, I published a book on complex systems titled “Futures Studies in Complex Systems” which was awarded as the book of the year by the Iranian Foresight Association.
Since May 2021, I started a research collaboration with TISSS Lab at the Johannes Gutenberg University Mainz as a project coordinator, the German Research Centre for AI, Human-Centered Multimedia, and the Centre for Research in Social Simulation. The project title is “AI for Assessment” and its objective is to understand the status quo and the future options of AI-based social assessment in public service provisions to help in the creation of improved AI technology for social welfare systems.
On the executive side, I have also various experiences, including head of the department, deputy of the Technology Incubator Center, director of university’s research affairs, and head of the International Scientific Cooperation Office.
Complex Systems, Social Modeling and Simulation
Engineering the Futures
Doing research on how the flood insurance system in the UK should be structured in the future to make it resilient for environmental change.
My research focuses on applied marine ecology and environmental management, particularly with coastal fish assemblages. Research interests include fish ecology, environmental monitoring and assessment methodology and individual-based models.
The Ph.D. research project is mainly focused on the study of the influence of emotional intelligence inside decision-making processes and on the social and emotional aspects of organizations.Furthermore, the research has taken into account the generative science paradigm: in this way, the general aim is the development of social simulations able to account organizational processes related with emotions and with the emotional intelligence from the bottom-up.
I have a particular interest in the way in which social network structure influences dynamic processes operating over the netowrk, such as adoption of behaviour or spread of disease. More generally, I am interested in using complex systems methods to understand social phenomena.
Direction of the Vector-Borne Disease Network (www.vecnet.org), an international research consortium developing modeling tools that support the development of new strategies to eliminate malaria.
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.
🔹 Experience
Associate Professor — Industrial Engineering, University of Engineering and Technology, Taxila (2018 – 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
🔹 Research Interests•
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
🔹 Selected Achievements•
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
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