About

Dashun Wang is the Kellogg Chair of Technology and a Professor at the Kellogg School of Management, as well as a Professor of Management & Organizations and of Industrial Engineering & Management Sciences at Northwestern University. He is the Founding Director of the Northwestern Innovation Institute, the Founding Co-Director of the Ryan Institute on Complexity, and the Founding Director of the Center for Science of Science and Innovation (CSSI). Additionally, he is a core faculty member at the Northwestern Institute on Complex Systems (NICO). His research focuses on the Science of Science, aiming to apply scientific methods and curiosity to understand science itself. He develops and utilizes tools from complexity sciences and artificial intelligence to explore the opportunities presented by the recent explosion of data in science. His work has been published in prominent journals such as Nature, Science, PNAS, and others, and has been featured in major media outlets including The New York Times, Wall Street Journal, and Harvard Business Review. Wang has received multiple awards for his research and teaching, including the AFOSR Young Investigator award, Poets & Quants Best 40 Under 40 Professors, and the Erdos-Renyi Prize, among others.

Research topics

• Computer Science
• Political Science
• Sociology
• Social Science
• Data science
• Medicine
• Psychology
• Engineering
• Virology
• Demographic economics
• Economic growth
• Biology
• Geology
• Pedagogy
• Economics
• History
• Social psychology
• Engineering ethics
• Geography
• Public relations
• Mathematics education

Selected publications

• Bipartisan-cited science is rare, unevenly distributed, and disproportionately influential

  Proceedings of the National Academy of Sciences · 2026-04-22

  articleOpen accessSenior authorCorresponding

  This study offers a systematic analysis of scientific papers cited in both Republican and Democratic policy documents. Using data from Overton and Dimensions, we examine congressional reports, hearings, and think tank publications. We find that bipartisan citations, while rare, highlight papers of exceptional scientific influence. Policy documents citing these papers also receive more citations, amplifying their policy impact. Yet, bipartisan-cited science is unevenly distributed-concentrated in monetary policy and healthcare, but notably absent in climate, inequality, and race and gender. These results show that bipartisan engagement, though limited, marks a uniquely influential core of science in both research and policy.

  PublisherDOI

• Interdisciplinary papers supported by disciplinary grants garner deep and broad scientific impact

  PNAS Nexus · 2026-02-27 · 2 citations

  preprintOpen accessSenior author

  Interdisciplinary research has emerged as a hotbed for innovation and a key approach to addressing complex societal challenges. The dominance of grant-supported research in shaping scientific advances, coupled with growing interest in funding interdisciplinary work, raises fundamental questions about the effectiveness of interdisciplinary grants in fostering high-impact interdisciplinary research outcomes. Here, we analyze 350,000 grants from 164 agencies in 26 countries, along with 1.3 million resulting papers published between 1985 and 2009, to examine whether interdisciplinary grants successfully cultivate high-impact interdisciplinary research. Although interdisciplinary grants tend to produce interdisciplinary papers as intended, they yield fewer papers on average. Furthermore, while interdisciplinary papers are generally associated with high impact, those supported by interdisciplinary grants show substantially lower impact compared with those funded by disciplinary grants. In contrast, highly interdisciplinary papers anchored in deeply disciplinary grants garner disproportionately more citations, both within their core disciplines and from broader fields. This impact advantage is not merely a consequence of funding size, reception of ideas within disciplinary boundaries, or collaborative formats. Amid the substantial rise of support for interdisciplinary work across the sciences, these results highlight the underexplored role of disciplinary grants in driving interdisciplinary advances, suggesting that interdisciplinary research may benefit from deep disciplinary expertise and investments.

  PublisherDOI

• Replication Data for: Bipartisan-Cited Science Is Rare, Unevenly Distributed, and Disproportionately Influential

  Harvard Dataverse · 2026-03-13

  datasetOpen accessSenior author

  Replication data for Furnas & Wang "Bipartisan-cited Science"

  PublisherDOI

• Bipartisan-Cited Science

  2025-10-15 · 1 citations

  preprintOpen accessSenior author

  This study offers the first systematic analysis of scientific papers cited in both Republican and Democratic policy documents. Using data from Overton and Dimensions, we examine congressional reports, hearings, and think tank publications. We find that bipartisan citations, while rare, highlight papers of exceptional scientific influence. Policy documents citing these papers also receive more citations, amplifying their policy impact. Yet bipartisan-cited science is unevenly distributed—concentrated in monetary policy and healthcare, but notably absent in climate, inequality, and race and gender. These results show that bipartisan engagement, though limited, marks a uniquely influential core of science in both research and policy.

  PublisherDOI

• Funding the Frontier: Visualizing the Broad Impact of Science and Science Funding

  ArXiv.org · 2025-09-19

  preprintOpen accessSenior author

  Understanding the broad impact of science and science funding is critical to ensuring that science investments and policies align with societal needs. Existing research links science funding to the output of scientific publications but largely leaves out the downstream uses of science and the myriad ways in which investing in science may impact human society. As funders seek to allocate scarce funding resources across a complex research landscape, there is an urgent need for informative and transparent tools that allow for comprehensive assessments and visualization of the impact of funding. Here we present Funding the Frontier (FtF), a visual analysis system for researchers, funders, policymakers, university leaders, and the broad public to analyze multidimensional impacts of funding and make informed decisions regarding research investments and opportunities. The system is built on a massive data collection that connects 7M research grants to 140M scientific publications, 160M patents, 10.9M policy documents, 800K clinical trials, and 5.8M newsfeeds, with 1.8B citation linkages among these entities, systematically linking science funding to its downstream impacts. As such, Funding the Frontier is distinguished by its multifaceted impact analysis framework. The system incorporates diverse impact metrics and predictive models that forecast future investment opportunities into an array of coordinated views, allowing for easy exploration of funding and its outcomes. We evaluate the effectiveness and usability of the system using case studies and expert interviews. Feedback suggests that our system not only fulfills the primary analysis needs of its target users, but the rich datasets of the complex science ecosystem and the proposed analysis framework also open new avenues for both visualization and the science of science research.

  PublisherOA PDFDOI

• Tenure and research trajectories

  Proceedings of the National Academy of Sciences · 2025-07-22 · 8 citations

  articleOpen accessSenior authorCorresponding

  Tenure is a cornerstone of the US academic system, yet its relationship to faculty research trajectories remains poorly understood. Conceptually, tenure systems may act as a selection mechanism, screening in high-output researchers; a dynamic incentive mechanism, encouraging high output prior to tenure but low output after tenure; and a creative search mechanism, encouraging tenured individuals to undertake high-risk work. Here, we integrate data from seven different sources to trace US tenure-line faculty and their research outputs at a remarkable scale and scope, covering over 12,000 researchers across 15 disciplines. Our analysis reveals that faculty publication rates typically increase sharply during the tenure track and peak just before obtaining tenure. Post-tenure trends, however, vary across disciplines: In lab-based fields, such as biology and chemistry, research output typically remains high post-tenure, whereas in non-lab-based fields, such as mathematics and sociology, research output typically declines substantially post-tenure. Turning to creative search, faculty increasingly produce novel, high-risk research after securing tenure. However, this shift toward novelty and risk-taking comes with a decline in impact, with post-tenure research yielding fewer highly cited papers. Comparing outcomes across common career ages but different tenure years or comparing research trajectories in tenure-based and non-tenure-based research settings underscores that breaks in the research trajectories are sharply tied to the individual's tenure year. Overall, these findings provide an empirical basis for understanding the tenure system, individual research trajectories, and the shape of scientific output.

  PublisherOA PDFDOI

• Partisan disparities in the funding of science in the United States

  Science · 2025-09-18 · 3 citations

  articleSenior author

  Republican lawmakers consistently provided robust federal funding, often exceeding Democrats.

  PublisherDOI

• Early career setback and future achievement in professional sports

  Scientific Reports · 2025-09-29

  articleOpen accessSenior authorCorresponding

  A central tenet of human performance posits that past success is a key predictor of future outcomes. This principle underpins selection processes in various human endeavors, shaping opportunity, wage, and winner-take-all inequalities. Here we systematically examine the future performance of previous winners and non-winners across two sports contexts using two different empirical strategies. First, we track young athletes participating in world-class track and field competitions and compare the future performance of bronze medalists to those finishing just shy of the podium. Next, we study a novel natural experiment in tennis, where we compare future performances of 'lucky losers'-players who advanced to the main draw due to last-minute withdrawals from others-to those who just missed advancing. Our findings reveal that although past performance generally correlates with future outcomes, there appear to be notable exceptions at the margins. Interestingly, individuals initially classified as non-winners, despite being objectively outperformed, can surpass the future performance of their winning counterparts. These results not only reinforce the conventional wisdom of basing talent selection on past success but also introduce important nuances. They highlight the importance of recognizing both winning and non-winning experiences in talent scouting and assessment, with implications for nurturing diverse potential within talent pools.

  PublisherOA PDFDOI

• SciSciGPT: advancing human–AI collaboration in the science of science

  Nature Computational Science · 2025-12-09 · 5 citations

  articleOpen accessSenior author

  We introduce SciSciGPT, an open-source, prototype artificial intelligence (AI) collaborator that uses the domain of science of science as a testbed to explore the potential of large language model-powered research tools. SciSciGPT automates complex workflows, supports diverse analytical approaches, accelerates research prototyping and iteration and facilitates reproducibility. Through case studies, we demonstrate its ability to streamline a wide range of empirical and analytical research tasks while highlighting its broader potential to advance research. We further propose a large language model agent capability maturity model for human-AI collaboration, envisioning a roadmap to further improve and expand upon frameworks such as SciSciGPT. As AI capabilities continue to evolve, frameworks such as SciSciGPT may play increasingly pivotal roles in scientific research and discovery. At the same time, these new advances also raise critical challenges, from ensuring transparency and ethical use to balancing human and AI contributions. Addressing these issues may shape the future of scientific inquiry and inform how we train the next generation of scientists to thrive in an increasingly AI-integrated research ecosystem.

  PublisherOA PDFDOI

• Partisan disparities in the use of science in policy

  Science · 2025-04-24 · 10 citations

  articleSenior author

  Documents from Congress and think tanks reflect differences in how science is cited.

  PublisherDOI

Recent grants

• APTO: Measuring, Understanding, Predicting, and Accelerating Technology Outcomes

  NSF · $8.0M · 2024–2029

• Collaborative Research: Understanding Team Success and Failure

  NSF · $250k · 2018–2021

Frequent coauthors

• Albert‐László Barabási

  74 shared

• Yian Yin

  Cornell University

  34 shared

• Benjamin F. Jones

  24 shared

• Chaoming Song

  University of Miami

  24 shared

• Karim R. Lakhani

  16 shared

• Lu Liu

  Northwestern University

  11 shared

• James A. Evans

  University of Chicago

  11 shared

• Brian Uzzi

  McCormick (United States)

  11 shared

Awards & honors

• AFOSR Young Investigator award
• Poets & Quants Best 40 Under 40 Professors
• Junior Scientific Award from the Complex Systems Society
• Erdos-Renyi Prize
• Thinkers50 Radar 2021