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H. Van Dyke Parunak
AxonAI, Inc.
Harrisonburg, Virginia

H. Van Dyke Parunak is Vice President for Technology Innovation at AxonAI, Inc. He has extensive experience in both academic and industrial environments with chaos and complex systems, artificial intelligence, distributed computing, and human interfaces. Since 1984, he led the Agent-based and Complex Systems Research group, housed since 1984 in a variety of companies, studying swarm intelligence, emergent behavior, and nonlinear dynamics. In 2013, AxonAI was formed to commercialize these results.

His major research accomplishments include fine-grained agent architectures for a variety of manufacturing and defense functions, emphasizing applications of nonlinear dynamics and chaos theory to analyzing and controlling agent communities. He and his colleagues develop applications that take advantage of the self-organizing potential of very simple agents when they interact through a shared environment, inspired by examples in biological and ecological systems. He is the author or co-author of more than 200 technical articles and reports, and the coinventor on 13 patents in the area of agent technology.

Parunak has worked as a project designer and associate investigator at Harvard University, as an Assistant Professor and Postdoctoral Scholar at the University of Michigan, and as a computer scientist with Comshare, Inc. His research was done at the Industrial Technology Institute, ERIM, Altarum, NewVectors, TechTeam Government Solutions, Jacobs Technology Group, and Soar Technology. He received an AB in Physics from Princeton University (1969), an MS in Computer and Communication Sciences from the University of Michigan (1982), and a PhD in Near Eastern Languages and Civilizations from Harvard University (1978). He is a member of the American Association for Artificial Intelligence and the Association for Computing Machinery.


Updated March 1, 2016


Trends in social network analysis: information propagation, user behavior modeling, forecasting, and vulnerability assessment
Missaoui R., Abdessalem T., Latapy M.,  Springer International Publishing, New York, NY, 2017. 255 pp. Type: Book (978-3-319534-19-0)

This volume is a selective post-proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining. The ten individual studies have been edited and considerably expanded beyond the original conference versi...


Large-scale graph processing using Apache Giraph
Sakr S., Orakzai F., Abdelaziz I., Khayyat Z.,  Springer International Publishing, New York, NY, 2017. 197 pp. Type: Book (978-3-319474-30-4)

Analysis of graphical data (composed of nodes with edges between them) is a particularly challenging facet of the big data problem. Relational data (tables defining the features of each of a set of entities) enjoy computationally efficient algorit...


 The end of theory: financial crises, the failure of economics, and the sweep of human interaction
Bookstaber R.,  Princeton University Press, Princeton, NJ, 2017.Type: Book (9780691169019)

Richard Bookstaber is a PhD economist experienced in both the financial industry and government policy-making. For such a person to write this book is doubly courageous. First, he is challenging his colleagues, claiming that the orthodoxy of neocl...


Python for scientists (2nd ed.)
Stewart J.,  Cambridge University Press, New York, NY, 2017. 270 pp. Type: Book (978-1-316641-23-1), Reviews: (2 of 2)

This volume provides an important update to the resources available to physicists and other scientists who manipulate quantitative data for one of their most common tasks: computation....


Natural complexity: a modeling handbook
Charbonneau P.,  Princeton University Press, Princeton, NJ, 2017. 376 pp. Type: Book (978-0-691170-35-0)

Author Paul Charbonneau defines science as “a way of knowing.” Since the Renaissance, the natural sciences have had two main ways of knowing: empirical analysis of observational data from the real world, and theoretical arguments (in t...


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