Displaying 10 of 129 results for "Kam L Yeung" clear search
I am a scientist at the Johns Hopkins Applied Physics Laboratory. Previously, I worked for the Board of Governors of the Federal Reserve System as an internal consultant on statistical computing. I have also been a consultant to numerous government agencies, including the Securities and Exchange Commission, the Executive Office of the President, and the United States Department of Homeland Security. I am a passionate educator, teaching mathematics and statistics at the University of Maryland University College since 2010 and have taught public management at Central Michigan University, Penn State, and the University of Baltimore.
I am fortunate to play in everyone else’s backyard. My most recent published scholarship has modeled the population of Earth-orbiting satellites, analyzed the risks of flood insurance, predicted disruptive events, and sought to understand small business cybersecurity. I have written two books on my work and am currently co-editing two more.
In my spare time, I serve Howard County, Maryland, as a member of the Board of Appeals and the Watershed Stewards Academy Advisory Committee of the University of Maryland Extension. Prior volunteer experience includes providing economic advice to the Columbia Association, establishing an alumni association for the College Park Scholars Program at the University of Maryland, and serving on numerous public and private volunteer advisory boards.
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.
Postdoctoral Research Associate at the CyberGIS Center for Advanced Digital and Spatial Studies, University of Illinois at Urbana-Champaign
Leonardo Grando is a Ph.D. Student at the University of Campinas (UNICAMP) in Brazil. I am interested in complex systems, agent-based simulation, artificial intelligence, the Internet of Things, programming, and machine learning tools. I have expertise in Netlogo, Python, R, Latex, SQL, and Linux tools.
My Ph.D. work project is an IoT devices (UAVs) swarm agent-based modeling simulation (ABMS) aiming the perpetual flight. The workflow is Netlogo to ABMS simulate, Python and R to data analysis, and I use Latex for my thesis writing.
I live in Salento, a small land located between two seas in Southeastern Italy. I work as an educator in an adult school. My educational background includes a degree in Life Sciences. During my post-graduate training, I was involved in researching the genetic and molecular responses of cells to environmental and genomic stresses. Currently, I am interested in exploring theoretical biology and complex adaptive systems through agent-based modelling.
Artificial Life, Adaptive Cognition, Evolvability
I am a computational archaeologist interested in how individuals and groups respond to both large scale processes such as climate change and local processes such as violence and wealth inequality. I am currently a PhD Candidate in the Department of Anthropology at Washington State University.
My dissertation research focuses on experimenting with paleoecological data (e.g., pollen) to assess whether or not different approaches are feasible for paleoclimatic field reconstructions. In addition, I will also use pollen data to generate vegetation (biome) reconstructions. By using tree-ring and pollen data, we can gain a better understanding of the paleoclimate and the spatial distribution of vegetation communities and how those changed over time. These data can be used to better understand changes in demography and how people responded to environmental change.
In Summer 2019, I attended the Santa Fe Institute’s Complex Systems Summer School, where I got to work in a highly collaborative and interdisciplinary international scientific community. For one of my projects, I got to merry my love of Sci-fi with complexity and agent-based modeling. Sci-fi agent-based modeling is an anthology and we wanted to build a community of collaborators for exploring sci-fi worlds. We also have an Instagram page (@Scifiabm).
Displaying 10 of 129 results for "Kam L Yeung" clear search