ABM modelling of molecular and cellular interactions in Lymph Nodes
I live in Salento (Italy) the tiny land between two seas, where I work as a teacher in a school for adults. My education includes a degree in Life Sciences; in my post-graduate training, I have been involved in searching for the genetic and molecular responses of some cellular systems to environmental and genomic stresses. Now, one of my great interests is the approach to theoretical biology through agent-based modeling techniques, even if - I know - nothing can be more surprising than the complexity of Nature and the cognition about it.
Complex Adaptive Systems, Agent Based Simulation, Technology Enhanced Learning, and Theoretical Biology
agent-based modeling and simulation, traffic control and operation, emergency evacuation and disaster response
Complex Adaptive Systems, Data Analytics and Visualization
Working on decision modeling in emergency healthcare. We are trying to design and develop service machine for emergency medical services.As a part of that, we are developing agent based models for emergency medical services
I have a backround in computer science, worked in natural resource management, and ended up with a PhD in Sustainability Sciences!
My interests are to explore aspects of sustainability, resilience, and adaptive management in social-ecological systems using agent-based models and other simulation models.
Development of dynamic, adaptive, complex models of financial markets.
Kenneth D. Aiello is a postdoctoral research scholar with the Global BioSocial Complexity Initiative at ASU. Kenneth’s research contributes to cross disciplinary conversations on how historical developments in biological, social, and cultural knowledge systems are governed by processes that transform the structure, dynamics, and function of complex systems. Applying computational historical analysis and epistemology to question what scientific knowledge is and how we can analyze changes in knowledge, he uses text analysis, social network analysis, and machine learning to measure similarities and differences between the knowledge claims of individual agents and groups. His work builds on how to assess contested knowledge claims and measure the evolution of knowledge across complex systems and multiple dimensions of scale. This approach also engages in dynamic new debates about global and local structures of knowledge shaped by technological innovation within microbiology related to public policy, shrinking resources given to biomedical ideas as opposed to “translation”, and the ethics of scientific discovery. Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge emerges.