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Qing Tian


Dr. Tian holds a B.S. in Computer Science from Beijing University, an M.S. in Cartography and Remote Sensing from Chinese Academy of Sciences, a second M.S. in Computer Science from George Mason University, and an interdisciplinary Ph.D. from the School of Natural Resources and Environment at the University of Michigan. After completion of her PhD, she studied with Bob Axelrod as a postdoc in the Ford School of Public Policy. Her professional experiences include working as an assistant research professor at the Chinese Academy of Sciences (Beijing, China), research fellow at the International Center for Science and High Technology/United Nations Industrial Organization (Trieste, Italy), and software engineer for VERITAS Software (Reston, VA).

Her doctorate dissertation “From Vulnerability to Sustainability: Rural Development in the Poyang Lake Region of China amid Institutional Changes and Flood Hazards,” supervised by Dan Brown, applies the science of complexity to study the human-environment system around Poyang Lake. The study integrates social, economic, political, and environmental perspectives, and focuses on the interactions between individual households and their social and environmental settings to explain rural development at the aggregate level and variations of well-being between rural households and across places. It includes four major analyses: (i) a regional-scale assessment of well-being, (ii) an in-depth analysis of underlying causes of household well-being, (iii) an analysis of the mechanism underlying spatial patterns and temporal changes in agricultural land use, and (iv) an analysis of land rental markets and rural development policies. Combining agent-based modeling with GIS and empirical analysis of social surveys and interviews, these analyses generated a number of important insights into (i) how polices may effectively promote social and economic development and mitigate flood impacts at the same time, (ii) why polices need to be sensitive to social and environmental heterogeneity, and how policies should vary across places, and (iii) how rural households can increase their overall well-being under environmental and social-economic-political changes. Her dissertation work was supported by several fellowships including a NASA Earth and Space Science Fellowship.

She has broad interests in human cognition, development, land use and land cover change, human-environment systems, and complex adaptive systems in general. Dr. Tian has published frequently in professional journals and books and has recently seen the release of her own text, Rural Sustainability: A Complex Systems Approach to Policy Analysis, available from Springer (2017). This textbook provides a comprehensive and reader-friendly introduction to the field of computational social science (CSS). Presenting a unified treatment, the text examines in detail the four key methodological approaches of automated social information extraction, social network analysis, social complexity theory, and social simulation modeling. This updated new edition has been enhanced with numerous review questions and exercises to test what has been learned, deepen understanding through problem-solving, and to practice writing code to implement ideas. Topics and features: contains more than a thousand questions and exercises, together with a list of acronyms and a glossary; examines the similarities and differences between computers and social systems; presents a focus on automated information extraction; discusses the measurement, scientific laws, and generative theories of social complexity in CSS; reviews the methodology of social simulations, covering both variable- and object-oriented models.

update 9/23/17

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