Dashun Wang
Dashun Wang

Associate Professor of Management & Organizations
Associate Professor of Industrial Engineering & Management Sciences (Courtesy)

Print Overview

Dashun Wang is Associate Professor of Management and Organizations at the Kellogg School of Management, and (by courtesy) Industrial Engineering & Management Sciences at the McCormick School of Engineering. At Northwestern, He is also a core faculty at NICO, the Northwestern Institute on Complex Systems. Prior to joining Kellogg, he was Assistant Professor at the Pennsylvania State University and a Research Staff Member at the IBM T.J. Watson Research Center. Dashun received his PhD in Physics in 2013 from Northeastern University, where he was a member of the Center for Complex Network Research. From 2009 to 2013, he had also held an affiliation with Dana-Farber Cancer Institute, Harvard University as a Research Associate. He is a recipient of the AFOSR Young Investigator Award (2016).

Dashun Wang leads a group of highly interdisciplinary researchers who are extremely passionate about data. His research takes a multidisciplinary approach---combining computational social science, statistical physics, and computer science---to exploit the opportunities and promises offered by Big Data. Through the lens of new and increasingly available large-scale datasets, he hopes to use and develop tools of network science to help improve the way in which we understand the interconnectedness of the social technical and business world around us. His work has been applied to understand and predict social interactions, human mobility, knowledge production and scientific impact. His research has been published in general audience journals such as Science, and PNAS as well as top specialized venues in computer science and physics, and has been featured in The New York Times, Forbes, The Economist, The Guardian, The Washington Post, The Boston Globe, among other major global media outlets. 

Print Vita
Ph.D, 2013, Physics, Northeastern University
M.S., 2009, Physics, Northeastern University
B.S., 2007, Physics, Fudan University

Academic Positions
Associate Professor of Management & Organizations, Management and Organizations, Kellogg School of Management, Northwestern University, 2016-present
Associate Professor (Courtesy), Industrial Engineering & Management Sciences, McCormick School of Engineering, Northwestern University, 2016-present
Assistant Professor, College of Information Sciences and Technology, Pennsylvania State University, 2015-2016
Adjunct Assistant Professor, Physics, Northeastern University, 2014-present
Research Associate, Dana-Farber Cancer Institute, Harvard University, 2009-2013

Other Professional Experience
Research Staff Member, IBM T.J. Watson Research Center, 2013-2014
Research Intern, IBM T.J. Watson Research Center, 2010-2011

Honors and Awards
Young Investigator Award, AFOSR

Editorial Positions
Editorial Board Member, Journal of the Association for Information Science and Technology, 2016

Print Research
Jia, Tao, Dashun Wang and Boleslaw K. Szymanski. 2017. Quantifying patterns of research-interest evolution. Nature Human Behavior. 1(0078)
Sinatra, Roberta, Dashun Wang, Pierre Deville, Chaoming Song and Albert-Laszlo Barabasi. 2016. Quantifying the evolution of individual scientific impact. Science. 354(6312)
Deville, Pierre, Chaoming Song, Nathan Eagle, Vincent Blondel, Albert-Laszlo Barabasi and Dashun Wang. 2016. Scaling identity connects human mobility and social interactions. Proceedings of the National Academy of Sciences (PNAS).
Zhang, Xinyang, Dashun Wang and Ting Wang. 2016. Inspiration or Preparation? Explaining Creativity in Scientific Enterprise. Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM-2016).
Sung, Yi-Shan, Dashun Wang and Soundar Kumara. 2016. Uncovering the effect of dominant attributes on community topology: A case of Facebook networks. Information Systems Frontiers.
Sinatra, Roberta, Pierre Deville, Michael Szell, Dashun Wang and Albert-Laszlo Barabasi. 2015. A Century of Physics. Nature Physics. 11.10: 791-796.
Cao, Nan, Yu-Ru Lin, Fan Du and Dashun Wang. 2015. Episogram: Visual Summarization of Egocentric Social Interactions. IEEE Computer Graphics and Applications.
Song, Chaoming and Dashun Wang. 2015. Impact of Human Mobility on Social Networks. Journal of Communications and Networks.(17.2): 100-109.
Wang, Ting and Dashun Wang. 2014. Why Amazon's Ratings Might Mislead You? The Story of Herding Effects. Big Data Journal.
Wang, Ting, Dashun Wang and Fei Wang. 2014. Quantifying Herding Effects in Crowd Wisdom. Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
Shen, Hua-Wei, Dashun Wang, Chaoming Song and Albert-Laszlo Barabasi. 2014. Modeling and Predicting Popularity Dynamics via Reinforced Poison Processes. The Twenty-Eighth AAAI Conference on Artificial Intelliegence (AAAI 2014).
Jagmohan, A., Y. Li, N. Shao, Anshul Sheopuri, Dashun Wang, L.R. Varshney and P Huang. 2014. Exploring Application Domains for Computational Creativity. The Fifth International Conference on Computational Creativity (ICCC 2014).
Deville, Pierre, Dashun Wang, Chaoming Song, Roberta Sinatra, Vincent Blondel and Albert-Laszlo Barabasi. 2014. Career on the Move: Geography, Stratification, and Scientific Impact. Nature Scientific Reports. 4(4770)
Gao, Liang, Chaoming Song, Ziyou Gao, Albert-Laszlo Barabasi, James P Bagrow and Dashun Wang. 2014. Quantifying Information Flow During Emergencies. Nature Scientific Reports. 4(3997)
Wang, Dashun, Chaoming Song and Albert-Laszlo Barabasi. 2013. Quantifying Long-term Scientific Impact. Science. 342(6154): 127-132.
Barabasi, Albert-Laszlo, Chaoming Song and Dashun Wang. 2012. Handful of papers dominates citation. Nature. 491(7422): 40-40.
Wang, Dashun, Dino Pedreschi, Chaoming Song, Fosca Giannotti and Albert-Laszlo Barabasi. 2011. Human Mobility, Social Ties, and Link Prediction. Proc. 17th ACM SIGKDD Intl. Conf. on Knowledge Discovery and Data Mining.
Bagrow, James, Dashun Wang and Albert-Laszlo Barabasi. 2011. Collective Response of Human Populations to Large-scale Emergencies. PLos ONE. 6(3)(e17680)
Wang, Dashun, Zhen Wen, Hanghang Tong, Ching-Yung Lin, Chaoming Song and Albert-Laszlo Barabasi. 2011. Information Spreading in Context. Proc. 20th International World Wide Web Conference (WWW 2011)..
Working Papers
Song, Chaoming, Dashun Wang and Albert-Laszlo Barabasi. 2015. Connections between Human Dynamics and Network Science.
Book Chapters
Wang, Dashun, Yu-Ru Lin and James P Bagrow. 2014. "Social Networks in Emergency Response." In Encyclopedia of Social Network Analysis and Mining, edited by Reda Alhajj and Jon Rokne, Springer.
Giannotti, Fosca, Luca Pappalardo, Dino Pedreschi and Dashun Wang. 2013. "A complexity science perspective on human mobility." In Mobility Data, edited by Chiara Renso, Stefano Spaccapietra, and Esteban Zimanyi, Cambridge University Press.
Mangioni, Giuseppe, Filippo Simini, Dashun Wang and Stephen Miles Uzzo. 2015. Complex Networks VI. Springer.
Pinel, Florian, Krishna C. Ratakonda, L.R. Varshney and Dashun Wang. 2015. "Group generation using sets of metrics and predicted success values." United States Patent Document Number 2016/0224896, filed 2/13/2015.
Wang, Dashun, Fei Wang and Ting Wang. 2014. "Quantifying and Predicting Herding Effects in Collective Rating Systems." United States Patent 20,160,063,380, filed 9/12/2014, and issued 3/3/2016.
Jagmohan, A., N. Shao, Anshul Sheopuri, L.R. Varshney and Dashun Wang. 2014. "System and Method for Contextual Recipe Recommendation." United States Patent 20,160,140,444, filed 11/17/2014, and issued 5/19/2016.

Print Teaching
Full-Time / Evening & Weekend MBA
Social Dynamics and Network Analytics (MORS-457-0)

**This course was formerly known as MORS-945-0**

Today's business leaders face unparalleled levels of connectivity and complexity. To help students meet these challenges, Social Dynamics and Networks Analytics provides an in-depth introduction to the emerging fields of social dynamics and network science including social networks, social media, tipping points, contagion, the wisdom of crowds, prediction markets, and social capital. Using simple yet powerful hands-on interactive models and exercises, the course covers both theory and applications of social dynamics for organizational growth, leadership, and competitiveness. The course was developed jointly with Professor Uzzi and complements the MORS-430 leadership and organizations course.