As an Assistant Professor I am a scientific member at the Department of Computer Science in Hamedan University of Technology.
I have completed my Ph.D. in Futures Studies as an interdisciplinary field. My background comes from computer science.
Complex Systems, Social Modeling and Simulation
Enginnering the Futures
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
My research aims to explore the potential of network science for the archaeological discipline. In my review work I confront the use of network-based methods in the archaeological discipline with their use in other disciplines, especially sociology and physics. In my archaeological work I aim to develop and apply network science techniques that show particular potential for archaeology. This is done through a number of archaeological case-studies: archaeological citation networks, visibility networks in Iron Age and Roman southern Spain, and tableware distribution in the Roman Eastern Mediterranean.
I received a Ph.D. in Economics at the University of Namur (Belgium) in June 2012 with a thesis titled “Essays in Information Aggregation and Political Economics”.
After two years at the Research Center for Educational and Network Studies (Recens) of the Hungarian Academy of Sciences, I joined the Department of Economics “Marco Biagi” of the University of Modena and Reggio Emilia in January 2015 and then the Department of Agricultural and Food Sciences of the University of Bologna.
I am currently a Lecturer in Financial Computing at the Department Computer Science (Financial Computing and Analytics group) - University College London. Moreover I am an affiliated researcher of the DYNAMETS - Dynamic Systems Analysis for Economic Theory and Society research group and an affiliate member of the Namur Center for Complex Systems (Naxys).
My research interests concern the computational study of financial markets (microstructure, systemic properties and behavioral bias), of social Interactions on complex networks (theory and experiments), the evolution of cooperation in networks (theory and experiments) and the study of companies strategies in the digital economy.
Dr. Mariam Kiran is a Research Scientist at LBNL, with roles at ESnet and Computational Research Division. Her current research focuses on deep reinforcement learning techniques and multi-agent applications to optimize control of system architectures such as HPC grids, high-speed networks and Cloud infrastructures.. Her work involves optimization of QoS, performance using parallelization algorithms and software engineering principles to solve complex data intensive problems such as large-scale complex decision-making. Over the years, she has been working with biologists, economists, social scientists, building tools and performing optimization of architectures for multiple problems in their domain.
Down Networks is a real time, progressively agile non profit startup whose goals are to fund its research via pragmatically aggressive altruistic entrepreneurial pursuits informed by proprietary in-house techniques, open source technology and refined scientific methodology.
Without Central Control is self organization possible?
Considering the seemingly preplanned, densely aggregated communities of the prehistoric Puebloan Southwest, is it possible that without centralized authority (control), that patches of low-density communities dispersed in a bounded landscape could quickly self-organize and construct preplanned, highly organized, prehistoric villages/towns?
Mazaher Kianpour is a PhD candidate at NTNU. He holds a Bachelor’s degree in Computer Engineering (Software) from the Payame Noor University. He obtained his Master’s degree in Architecture of Computer Systems from Shahid Beheshti University, Tehran, Iran. He started his PhD in Information Security at NTNU in May 2018. His PhD research lies at the intersection of economics and information security with a socio-technical perspective. He has several years of work experience at Tehran University of Medical Sciences, and his professional training includes Computer Networks, Cybersecurity and Risk Management.
My main research interest is modelling of information security, business operations and deterrents in complex ICT ecosystem. I will in particular focus on the complex interaction between various stakeholders and actors in the information security business domain. In order to model and better understand the information security ecosystem, I rely on agent-based simulation and quantitative modelling techniques such as stochastic modelling, discrete event simulations and game theory. Of particular interest is to gain increased understanding on how various security threats and measures influence business operations in the digital ecosystem.
I am an Assistant Professor at the School of Computer Science, University of Nottingham, UK.
My main research interest is the application of computer simulation to study human-centric complex adaptive systems. I am a strong advocate of Object Oriented Agent-Based Social Simulation. This is a novel and highly interdisciplinary research field, involving disciplines like Social Science, Economics, Psychology, Operations Research, Geography, and Computer Science. My current research focusses on Urban Sustainability and I am a co-investigator in several related projects and a member of the university’s “Sustainable and Resilient Cities” Research Priority Area management team.
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/)