I am interested in the interface between biology and computation. I am especially focused on modelling and simulation of evolutionary processes.
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.
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.
As publically funded science has become increasingly complex, the policy and management literature has begun to focus more attention on how science is structured and organized. My research interests reside at the nexus of science and technology policy, organizational theory, and complexity theory—I am interested in how the management and organization of S&T research influences the implementation of policies and the emergence of organizational strategies and innovation. Although my research involves the use of multiple qualitative and quantitative methods, I rely heavily on agent based modeling and system dynamics approaches in addressing my research questions.
Simulation games, systemic complexity, learning, business cycles, and discrete-event simulation, modeling sustainability challenges in urban context.
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/)
For my Ph.D. thesis, I developed a system to play poker.
I’m interested to see whether a similar approach can be applied to agent based models.