Dashun Wang
Alma materNortheastern University
Fudan University
AwardsErdős–Rényi Prize in Network Science[1]
Scientific career
FieldsPhysics, Science of Science, Computational Social Science, Network Science, Big Data, Complex Systems
InstitutionsNorthwestern University
Pennsylvania State University
Northeastern University

Dashun Wang is a Professor of Management and Organizations at the Kellogg School of Management and the McCormick School of Engineering, at Northwestern University since 2016. At Kellogg from 2019, he is the Founding Director of the Center for Science of Science and Innovation (CSSI). He is also a core faculty at the Northwestern Institute on Complex Systems (NICO) and an Adjunct Professor of Department of Physics, at Northeastern University. His current research focus is on Science of Science. Dashun is a recipient of the AFOSR Young Investigator award (2016)[2] and Poets & Quants Best 40 Under 40 Professors (2019).[3]

Career

In 2007, Dashun earned an undergraduate degree in Physics from Fudan University, Shanghai, China. After that, he earned both a M.Sc and a PhD in physics from Northeastern University. From January 2015 to July 2016, he was an Assistant Professor of College of Information Sciences and Technology at Pennsylvania State University, University Park. He is currently a Professor of Management and Organizations at the Kellogg School of Management and the McCormick School of Engineering, at Northwestern University.[4]

Research

Dashun’s current research focus is on Science of Science, a quest to turn the scientific methods and curiosities upon ourselves, hoping to use and develop tools from complexity sciences and artificial intelligence to broadly explore the opportunities and promises offered by the recent data explosion in science.[4] His research in this area has received multiple media coverages and has been featured on sources including The New York Times,[5] The Atlantic,[6] etc.

Dashun's research also span across the fields of Computational Social Science, Network Science, Big Data, and Complex Systems.[4] His most cited work, titled "Human mobility, social ties, and link prediction", investigates the correlation between mobility patterns and social proximity, and illustrates the power of mobility patterns in predicting formation of new social connections.[7][8] Another representative work of Dashun Wang, under the title of "Quantifying long-term scientific impact", centers around citation dynamics of individual papers.[7][9] In collaboration with Chaoming Song and Albert-László Barabási, Dashun Wang detects a universal temporal pattern of papers and this observed pattern facilitates a better understanding on the underlying processes of scientific impact and provides a reliable citation-based measure of influence.[9]

Dashun Wang's most recent work quantitatively analyzes global policy responses towards the COVID-19 pandemic.[10]

Awards and honors

In 2014, Dashun received the Invention Achievement Award from IBM Research. In 2016, Dashun is a recipient of the AFOSR Young Investigator award.[2] In 2019, his paper was elected as Top 100 most-discussed papers across all sciences, and he was elected be Poets & Quants Best 40 Under 40 Professors,[3] received Minerva Award from Department of Defense.[11]

Selected publications

Books

Articles

References

  1. ↑ "Erdős–Rényi prize". Network Science Society. Retrieved 15 September 2021.
  2. 1 2 "AFOSR awards grants to 56 scientists and engineers through Young Investigator Research Pro". Air Force Materiel Command. 14 January 2016. Retrieved 2020-12-18.
  3. 1 2 Allen, Nathan (2019-04-23). "Poets&Quants | P&Q's 2019 Best 40 Under 40 MBA Professors". Poets&Quants. Retrieved 2020-12-18.
  4. 1 2 3 "Dashun Wang". Dashun Wang. Retrieved 2020-12-18.
  5. ↑ Carey, Benedict (Feb 13, 2019). "Can Big Science Be Too Big?". The New York Times. Retrieved 2020-12-18.
  6. ↑ Yong, Ed (Feb 13, 2019). "Small Teams of Scientists Have Fresher Ideas". The Atlantic. Retrieved 2020-12-18.
  7. 1 2 "Google Scholar". Retrieved 2020-12-18.
  8. ↑ Wang, Dashun; Pedreschi, Dino; Song, Chaoming; Giannotti, Fosca; Barabási, Albert-László (August 21, 2011). Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining (PDF). pp. 1100–1108. doi:10.1145/2020408. ISBN 9781450308137. Retrieved 2020-12-18.
  9. 1 2 Wang, Dashun; Song, Chaoming; Barabási, Albert-László (Oct 4, 2013). "Quantifying long-term scientific impact". Science. 342 (6154): 127–132. arXiv:1306.3293. Bibcode:2013Sci...342..127W. doi:10.1126/science.1237825. PMID 24092745. S2CID 803694.
  10. ↑ Gao, Jian; Yin, Yian; Jones, Benjamin F.; Wang, Dashun (June 24, 2020). "Quantifying Policy Responses to a Global Emergency: Insights from the COVID-19 Pandemic". arXiv:2006.13853. {{cite journal}}: Cite journal requires |journal= (help)
  11. ↑ "Dynamics, Predictability, and Uncertainty of Scientific Discovery and Advance > Minerva Research Initiative > Awarded Projects". minerva.defense.gov. Retrieved 2020-12-18.
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