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Kenneth Aiello Member since: Thursday, January 23, 2020 Full Member

Ph.D., Biology and Society, Arizona State University, B.S., Sociology, Arizona State University,, B.S., Biology, Arizona State University

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 Using interdisciplinary methods for understanding historical content and context rich narratives contributes to understanding new domains and major transitions in science and provides a richer understanding of how knowledge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.

Sedar Olmez Member since: Wednesday, November 06, 2019 Full Member

Sedar is a PhD student at the University of Leeds, department of Geography. He graduated in Computer Science at King’s College London 2018. From a very early stage of his degree, he focused on artificial intelligence planning implementations on drones in a search and rescue domain, and this was his first formal attempt to study artificial intelligence. He participated in summer school at Boğaziçi University in Istanbul working on programming techniques to reduce execution time. During his final year, he concentrated on how argumentation theory with natural language processing can be used to optimise political influence. In the midst of completing his degree, he applied to Professor Alison Heppenstall’s research proposal focusing on data analytics and society, a joint endeavour with the Alan Turing Institute and the Economic and Social Research Council. From 2018 - 2023 he will be working on his PhD at the Alan Turing Institute and Leeds Institute for Data Analytics.

Sedar will be focusing on data analytics and smart cities, developing a programming library to try simulate how policies can impact a small world of autonomous intelligent agents to try deduce positive or negative impact in the long run. If the impact is positive and this is conveyed collectively taking into consideration the agent’s health, happiness and other social characteristics then the policy can be considered. Furthermore, he will work on agent based modelling to solve and provide faster solutions to economic and social elements of society, establishing applied and theoretical answers. Some other interests are:

  • Multi-agent systems
  • Intelligent agents
  • Natural language processing
  • Artificial intelligence planning
  • Machine learning
  • Neural networks
  • Genetic programming
  • Geocomputation
  • Argumentation theory
  • Smart cities

Claudine Gravel-Miguel Member since: Thursday, November 01, 2012 Full Member Reviewer

M.A., Anthropology, University of Victoria, Ph.D., Anthropology, Arizona State University

Dr. Gravel-Miguel currently works as a Postdoctoral Research Scholar for the Institute of Human Origins at Arizona State University. She does research in Archaeology and focuses on the Upper Paleolithic of Southwest Europe. She currently works on projects ranging from cultural transmission to human-environment interactions in prehistory.

Archaeology, GIS, ABM, social networks, portable art, ornaments, data science

John Murphy Member since: Wednesday, August 31, 2011 Full Member Reviewer

PhD. Anthropology, University of Arizona (2009), MA Education, Ohio State University (1993)

My research uses modeling to understand complex coupled human and natural systems, and can be generally described as computational social science. I am especially interested in modeling water management systems, in both archaeological and contemporary contexts. I have previously developed a framework for modeling general archaeological complex systems, and applied this to the specific case of the Hohokam in southern Arizona. I am currently engaged in research in data mining to understand contemporary water management strategies in the U.S. southwest and in several locations in Alaska. I am also a developer for the Repast HPC toolkit, an agent-based modeling toolkit specifically for high-performance computing platforms, and maintain an interest in the philosophy of science underlying our use of models as a means to approach complex systems. I am currently serving as Communications Officer for the Computational Social Science Society of the Americas.

Ken Buetow Member since: Thursday, November 15, 2018 Full Member

PhD, Human Genetics, University of Pittsburgh, MS, Human Genetics, University of Pitttsburgh, BA, Biology, Indiana University

Ken Buetow is a human genetics and genomics researcher who leverages computational tools to understand complex traits such as cancer, liver disease, and obesity. He currently serves as director of Computational Sciences and Informatics program for Complex Adaptive Systems at Arizona State University ([email protected]), is a professor in the School of Life Sciences in ASU’s College of Liberal Arts and Sciences; is a core faculty in the Center for Evolution and Medicine in the Biodesign Institute at ASU; and is director of bioinformatics and data management for the National Biomarker Development Alliance.

Professor Buetow previously served as the Founding Director of the Center for Biomedical Informatics and Information Technology within the National Institutes of Health’s National Cancer Institute.

Andrew Gillreath-Brown Member since: Thursday, July 25, 2019 Full Member

A.S., Pre-Engineering, Wallace State Community College, B.S., Mathematics and Natural Sciences, Freed-Hardeman University, B.A., Religious Studies, Freed-Hardeman University, B.A., Anthropology, Middle Tennessee State University, M.S., Applied Geography: Environmental Archaeology, University of North Texas

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).

Joseph A. E. Shaheen Member since: Wednesday, April 01, 2020 Full Member

Ph.D., Computational Social Science, George Mason University, MBA, Georgetown University, BSc, Engineering:Physics, Murray State University

Joseph is an Intelligence Community Postdoc Fellow (ODNI/NCTC) co-located with the faculty of the Department of Computational and Data Sciences at George Mason University. Since his first day of university training at age 15 and having earned his undergraduate degree in Engineering:Physics at age 19, his 15 years of industry experience has been diverse, ranging from industrial engineering to people analytics.

Dr. Shaheen earned his doctorate in Computational Social Science from GMU with a dissertation on economic policy and population-scale data analysis of Internal Revenue Service records. There, he studied all U.S. firms from a biologically-grounded perspective under the guidance of Professor Rob Axtell’s research group.

Following his U.S. State Department-funded assignment with the NATO STRATCOM Centre of Excellence where he conducted large scale analysis and provided policy recommendations in the fight against ISIS/ISIL/Daesh, he has been a guest speaker on issues of Information and \textit{Social Media Warfare}–a term closely associated with his 2015 NATO report–at the Pentagon (J-39 SMA), NATO Defense Against Terrorism COE, National Defense University, OMCC and others.

A life-long scholar, Joe has received training from academic leaders in Social Network Analysis and has been recognized as an honorary Links Center Fellow in 2015 and by GMU’s Teaching Excellence award in 5 consecutive iterations.

He has appeared on CNN HLN, FOX NEWS, NBC News, Entrepreneur Magazine and has been invited to participate in the 2020 (postponed to 2021) Heidelberg Laureate Forum (Heidelberg, Germany) where he will spend time with fellow scholars of the mathematical and computer sciences as well as Fields Medal, Abel Prize, Turing Award, and Nevanlinna prize winners.

In his free time, Joe enjoys a sense of humor and practices portrait, landscape and wildlife photography. Even so - he admits, he has never been able to successfully take one decent photo of himself

Agent-based Modeling
Social Network Analysis
Network Science
Public Policy
Security Policy
Taxation Policy

Saeed Moradi Member since: Thursday, June 04, 2020

Dr. Saeed Moradi received his Ph.D. in Civil Engineering from Texas Tech University in Lubbock, Texas. Saeed has 11+ years of experience in research, policymaking, housing sector, construction management, and structural engineering. His career developed his enthusiasm for the enhancement of post-disaster recovery plans. Through his research on disaster recovery, community resilience, and human-centered complex systems, Saeed aims to bridge the gap between social sciences and civil/infrastructure engineering.

Community and Infrastructure Resilience
Disaster Recovery
Complex Systems Modeling
Agent-Based Modeling
System Dynamics
Machine Learning
Pattern Recognition
Data Mining
Spatial Analysis and Modeling
Construction Management
Building Information Modeling

Calvin Pritchard Member since: Monday, May 16, 2016 Full Member Reviewer

Bachelor of Environment (Joint Honours Economics and Planning), University of Waterloo, Master of Arts (Economics), Queen's University

I am a developer for CoMSES Net as part of the Global Biosocial Complexity Initiative at Arizona State University. I work on improving model reuse, accessibility and discoverability through the development of the comses.net website and the CoMSES bibliographic database (catalog.comses.net). I also provide data analysis and software development advice on coupling models, version control, dependency management and data analysis to researchers and modelers.

My interests include model componentization, statistics, data analysis and improving model development and resuability practices.

Christopher Parrett Member since: Sunday, October 20, 2019 Full Member

I am a lowly civil servant moonlighting as a PhD student interested in urban informatics, Smart Cities, artificial intelligence/machine learning, all-things geospatial and temporal, advanced technologies, agent-based modeling, and social complexity… and enthusiastically trying to find a combination thereof to form a disseration. Oh… and I would like to win the lottery.

  • Applied data science (machine/deep learning applications) and computational modeling (agent-based
    modeling) in U.S. Government
  • Geographic Information Systems and analysis of dense urban environments and complex terrain
  • Complexity theory and computational organizational design of distributed enterprise teams.
  • Human Capital Management and Talent Management policy development
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