Research
My research examines how institutional environments — universities, industrial policy, export controls, AI, and platform design — shape who becomes a founder and what they build. The work is organized below into four themes, each led by a foundational concept I have introduced or helped develop. Recent work centers on cross-border policy interventions, the platform financing of online misinformation, and the methodological infrastructure (alumni entrepreneur surveys, RCTs, AI-enabled methods) that makes large-scale empirical entrepreneurship research possible.
Why this work matters
I got my start as an entrepreneur after staying with a village family in rural India who was down to one meal a day. Back at Duke, I found a biology professor working on a drought- and pest-resistant variety of corn — and the first startup we built around that work was transformational, both for what it could mean in the field and for how I came to think about the institutional environment around founders. Almost everything I research and teach traces back to that arc: the institutional gap between what we know how to do and what actually reaches the people who need it.
Research cited 6,862+ times across management, economics, and information systems ·
Full publications list → ·
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Methodological contribution to engineering-education research: the large-scale alumni-entrepreneur survey approach — first developed with Edward B. Roberts at
MIT (2009), then extended at
Stanford with William F. Miller (2012), at
UVA (2014), and at
Tsinghua (2016, with Delin Yang) — has since been adopted by
Technion (with Shlomo Maital), the
University of Toronto (with Shiri Breznitz), the
University of Alberta, the Chinese University of Hong Kong (CUHK), and others. In the years since, many additional universities have undertaken similar alumni-impact studies inspired by this approach — including
NUS,
UC Berkeley, and
IIT Delhi (January 2026). The survey instrument and its methodological companion paper are openly available through Stanford Epicenter as the
Alumni Innovation Survey — designed to be adopted and adapted by any research university.
Lasting contributions
What this work has changed.
The thematic structure below organizes the work by topic. This section organizes it by consequence — the four places where I think the research program has moved the field, the evidence it landed, and the direction the work is heading next.
An empirical foundation for measuring the entrepreneurial impact of universities
Working with William F. Miller across more than a decade, I built the longest-running large-scale alumni-entrepreneurship dataset in the field — tracing Stanford alumni-founded companies and their economic footprint over a 40-year window. The methodology and dataset became the template subsequent studies at MIT, UVA Darden, and other research universities adapted to measure their own alumni-founder economies. The work moved the conversation about university entrepreneurship from anecdote ("Stanford produces a lot of founders") to a measurable, replicable empirical claim.
Evidence: cited in Stanford institutional planning, replicated in MIT and UVA alumni-impact studies, basis for the ongoing Stanford GSB founder-impact reporting (~350 new companies / year from GSB alumni alone). Current direction: extending the comparative framework to MIT, UVA, and international peers to isolate which institutional features actually predict founder outcomes.
A causal account of industrial policy as an engine of — and a constraint on — innovation
A sustained research program established three empirical findings that are now central to the contemporary industrial-policy debate. First, U.S. semiconductor export controls did not slow Chinese venture capital allocation to the targeted sector — controls paradoxically attracted ~6 percentage points more financing and ~12% more capital to Chinese semiconductor startups (Strategic Management Journal). Second, the Inflation Reduction Act redirected venture capital toward climate-aligned technologies, but the strength of redirection depended on the credibility of program design more than the dollar magnitude of incentives (introducing the Policy Credibility Index as a measurement framework). Third, China's massive battery subsidies attract more entrants — but the marginal entrants are short-lived, low-commitment participants who never build productive capacity, undermining the policy's stated goal.
Evidence: published and forthcoming work informing how Treasury, DOE, and policy researchers think about subsidy design and capability screening. Presented at the National Academies GUIPRR workshop (April 2026); congressional briefing to the Joint Economic Committee on industrial policy and U.S.–China technology competition. Current direction: extending the Policy Credibility Index across additional industrial-policy regimes (EU CHIPS Act, Korea, Taiwan, Japan).
Naming and quantifying the algorithmic financing of online misinformation
Published in Nature with Wajeeha Ahmad, Ananya Sen, and Erik Brynjolfsson, this work traced how programmatic advertising routes mainstream-advertiser dollars to misinformation publishers, and identified the specific intermediary infrastructure responsible. The paper shifted the conversation about online misinformation from a content-moderation problem to a market-design problem — and showed advertisers what they could actually do about it.
Evidence: Nature publication (2024); coverage in Bloomberg and Stanford Report; documented adoption by ad-tech firms revising brand-safety practices in response to the findings. Current direction: extending the methodology to additional platform contexts and intermediary types, and continuing the policy-research collaboration on what governance structures would change publisher incentives.
A multi-level engineering-entrepreneurship education program and a doctoral pipeline that carries the work forward
Three parallel contributions to how engineering entrepreneurship education actually reaches people. First, a three-level course program at Stanford MS&E: undergraduate E145 Technology Entrepreneurship (recently re-anchored on the NAE Grand Challenges), the graduate MS&E 272 Entrepreneurship Without Borders (co-taught with Vimbayi Kajese; recently revised to treat agentic AI as a first-class object of study), and the PhD-level MS&E 379 Causal Inference for Entrepreneurship Research — together covering entry-level founder fluency, graduate cross-border institutional depth, and doctoral methodological training. Second, the E145 / NovoEd MOOC pipeline reached more than 200,000 learners globally and validated the cohort-based online-learning model that is now standard across the EdTech industry — the company itself was acquired by Devonshire Investors / Fidelity. Third, the lab has produced a doctoral pipeline whose impact extends well beyond my own publication record: 9 of 11 former doctoral students hold tenure-track faculty positions at institutions including Columbia, Oxford Saïd, Carnegie Mellon Tepper, Johns Hopkins Carey, NUS, CUHK Business School, the University of Oregon Lundquist, and Pontificia Universidad Católica de Chile — with their own research programs now extending the work.
Evidence: three-level MS&E course program with curriculum and syllabi on the
Teaching page; documented MOOC reach (200,000+ learners); NovoEd acquisition; doctoral placement record on the
Advising page. Current direction: continuing to evolve the three-level course program as AI changes what engineering founders need to learn, and continuing to advise PhD students working at the intersection of institutional design and entrepreneurship.
A two-decade research program on engineering schools as ecosystems for technology entrepreneurship
A through-line that runs from the MIT alumni dataset (assembled with Edward B. Roberts starting in the mid-2000s) to current work on AI-mediated founder cognition: the systematic study of how engineering schools and the institutions around them actually produce technology founders — and what specifically can be designed to make that pipeline broader, fairer, and more productive. The work spans the canonical paper on technology-based-university entrepreneurs (Hsu, Roberts & Eesley, Research Policy 2007), the founding-team-composition paper using MIT alumni data (Eesley, Hsu & Roberts, SMJ 2014), a randomized field experiment showing that structured peer mentorship measurably increases entrepreneurial activity among engineering students (Eesley & Wang, Research Policy 2017), the cross-national MIT–Tsinghua comparison (Eesley, Yang, Roberts & Li 2016), and the recent Eesley & Gerber 2025 Organization Science paper — Designing Institutions for Applied Impact: Lessons from Engineering for Organizational Research, which makes the engineering-to-organizational-research argument explicit. The Stanford E145 course (taught since 2009; Teaching page) has now been re-anchored on the NAE Grand Challenges for Engineering, making the most consequential open problems in engineering the explicit subject matter of the course's project track.
Evidence: continuous publication record in Research Policy, Strategic Management Journal, MIS Quarterly, and Organization Science on engineering-driven entrepreneurship; the Hsu/Roberts/Eesley 2007 paper is among the most-cited in the field; NSF I-Corps trainer role (2023–present); E145 reanchored on NAE Grand Challenges (Fall 2026). Current direction: extending the engineering-entrepreneurship work to cover AI's effects on founder cognition and on the institutional environment around technical founders.
Theme 1
Institutional Change and Entrepreneurship Quality
Foundational concept: institutional barriers to entrepreneurship quality — institutions shape not only how many firms get founded but the durability, innovativeness, and growth trajectories of those firms. Subsidies and market catalysts that boost entry volume can quietly hollow out quality.
Where this work has landed: presented at the National Academies GUIPRR workshop (April 2026); congressional briefing to the Joint Economic Committee on industrial policy and U.S.–China technology competition; the export-controls paper informs current Treasury and DOE discussions of CHIPS Act and IRA program design; doctoral students extending this program now hold faculty positions at Oxford Saïd, CMU Tepper, the University of San Diego, and PUC Chile.
Working paper, with Yikai Cao, Wanru Deng, and Guankai Zhai · In preparation for Management Science
U.S. export controls were meant to slow China's semiconductor sector. We find they increased VC funding to Chinese semiconductor startups by 6 percentage points and 12% in capital — driven by institutional reclassification, with state-backed investors acting as opportunity coordinators.
Working paper, with Yikai Cao, Rishee Jain, and Dinesh Moorjani · In preparation for PNAS
The Inflation Reduction Act selectively redirected venture capital toward climate-aligned technologies. Our Policy Credibility Index — scoring statutory specificity, durability, and enforceability — shows that institutional design quality, not just incentive size, determines whether private capital follows industrial policy.
Working paper, with Guankai Zhai (Stanford MS&E) · In preparation for Research Policy
Local government supply-side subsidies across 300 Chinese prefectures do attract more battery-sector entrants — but the marginal entrants are non-corporate, short-lived, generate no patents, and exit at elevated rates even in cities where the underlying battery cluster is thriving. Subsidies without capability screening attract participation without productive commitment.
In Institutions We Trust? Trust in Government and the Allocation of Entrepreneurial Intentions
With Yong Suk Lee · Organization Science, 34(2), 532–556 (2023)
Trust in government predicts which Stanford alumni become entrepreneurs and which sectors they enter — with implications for South Korea's policy reforms and other contexts where institutional trust varies sharply across demographic groups.
The Dark Side of Junior Stock Exchanges
With Robert Eberhart · Strategic Management Journal (2018)
Market catalysts — incubators, science parks, junior stock exchanges — are designed to stimulate venture creation. Analysis of 19,000 firms in Japan shows they produce unintended negative consequences: more competition and information asymmetry, ultimately fewer quality IPOs and less economic growth. The clearest single illustration of the institutional-quality concept above.
Read the paper ↗ Entrepreneurial Strategies During Institutional Changes: Evidence from China's Economic Transition
With You (Willow) Wu and Delin Yang · Strategic Entrepreneurship Journal (2022)
What China's regional economic transition tells us about which entrepreneurial strategies pay off when institutions shift.
Read the paper ↗ How Entrepreneurs Leverage Institutional Intermediaries in Emerging Economies
With Daniel Armanios, Jamber Li, and Kathleen Eisenhardt · Strategic Management Journal (2017)
How founders in emerging economies use incubators, accelerators, and business associations to acquire public resources they couldn't otherwise reach.
Read the paper ↗
Related ongoing work: China's national laboratory system, CHIPS Act effects on U.S. semiconductor entrepreneurship, and South Korean institutional reforms (with current and former PhD students).
Theme 2
Platforms, Information Ecosystems & Stakeholder Influence
Foundational concept: platforms as quasi-regulators — algorithmic monetization and matching decisions act as de facto regulatory infrastructure for the information environment, for the digital divide, and for whose voice shifts firm behavior. Firms inadvertently fund systems they would never knowingly underwrite; founders' access to mentor networks and learning platforms compounds prior advantage.
Where this work has landed: the Nature paper on programmatic advertising and online misinformation has been adopted by ad-tech firms revising brand-safety practices and is now cited across the AI-governance literature; the activist-targeting work (Eesley, DeCelles & Lenox, SMJ 2016) shaped how strategy scholars think about secondary-stakeholder influence; doctoral students extending this program now hold positions at Columbia Business School, Yale SOM, and beyond.
Companies Inadvertently Fund Online Misinformation Despite Consumer Backlash
With Wajeeha Ahmad, Ananya Sen, and Erik Brynjolfsson · Nature, 630(8015), 123–131 (2024)
Programmatic ad-tech systematically directs major-brand advertising dollars to misinformation publishers, even when those brands explicitly want to avoid them. The paper traces the algorithmic pipeline and the consumer-backlash evidence that follows when brand placements become visible.
Platform Governance and the Rural–Urban Divide: Sellers' Responses to Design Change
With Wesley Koo · Strategic Management Journal (2021)
A major design change on a leading Chinese e-commerce platform — the introduction of ML-based personalized search ranking — left rural sellers roughly 24% worse off than urban peers because they lacked the offline informational infrastructure to interpret the new algorithmic signals. Documents how platform search-ranking algorithms function as private governance with unintended distributional consequences across geography. The first half of a two-paper line of work with Wesley Koo on platform algorithms and the rural-urban divide.
Read the paper ↗ Take Me Home, Country Roads: Return Migration and Platform-Enabled Entrepreneurship
With Wesley Koo · Organization Science, 36(3), 1202–1220 (2025) · Special issue on Migration and Organizations
Companion paper to Koo & Eesley (2021). Uses a natural experiment from a Chinese provincial policy change that reduced barriers for rural migrants to return home, showing that rural e-commerce businesses in the affected province enjoyed a 19% performance gain relative to peers elsewhere. Together with the 2021 SMJ paper, the two papers establish how ML-driven platform design choices systematically reshape the geography of digital entrepreneurship.
Read the paper ↗ For Startups, Adaptability and Mentor Network Diversity Can Be Pivotal
With Lynn Wu · MIS Quarterly (2020)
Evidence from a randomized field experiment on the NovoEd MOOC platform — what kinds of mentor connections, and what kinds of adaptability, actually predict whether early-stage ventures succeed. Among the earliest large-scale platform-RCTs in entrepreneurship research.
Read the paper ↗ Through the Mud or in the Boardroom
With Katherine DeCelles and Michael Lenox · Strategic Management Journal (2016)
Activist tactics and how firms get targeted for social change — when secondary stakeholder pressure tactics succeed in shifting firm behavior, and when they don't.
Read the paper ↗ AI, Agentic Tools, and the Future of Engineering Entrepreneurship Education
Working papers in preparation, with current PhD students and collaborators
A line of work examining how generative and agentic AI are reshaping engineering entrepreneurship — what changes about founder cognition when the work shifts from doing the analysis to directing it, which parts of the entrepreneurial workflow get automated, which become newly important, and how engineering schools should redesign their pedagogy in response. Treats AI tools as the next platform layer mediating opportunity recognition, customer discovery, and team formation, with the same distributional and institutional-design concerns that ML platforms raised at smaller scale in the rural-urban work above. Recent outputs include the Yale FDS Workshop lightning talk on Four Paradigms for AI-Enabled Social Science Research (with Guankai Zhai), the agentic-AI revision of MS&E 272, and the June 2026 World Economic Forum essay on the institutional layer required for AI innovation to translate into durable value creation.
Theme 3 · pioneered methodology
Alumni Entrepreneur Surveys
Foundational contribution: large-scale alumni entrepreneur surveys as a research instrument. Pioneered first with Ed Roberts at MIT (2009), then extended at Stanford (2012) with William F. Miller, the University of Virginia (2014), and Tsinghua University. The surveys created the empirical infrastructure for an entire downstream literature on university entrepreneurship, founder ethnicity, founding-team composition, mentor networks, and the institutional environment around technology entrepreneurship.
Where this work has landed: the MIT/Stanford/UVA alumni-impact studies have collectively documented $6T+ in alumni-founded company revenue and are cited in Stanford institutional planning, the Kauffman Foundation's annual reports on university entrepreneurship, and across federal policy on research investment; the methodology has now been adopted by Tsinghua and is in adoption discussions at additional research universities; the Stanford Report and Stanford Engineering have covered the work as the canonical evidence on how universities produce founders.
In memory of
Edward B. Roberts (1935–2024), doctoral advisor at MIT Sloan, founder of the MIT Entrepreneurship Center, and the person who handed me the alumni-survey methodology between 2005 and 2007. A personal reflection on Ed, his lineage through Forrester and Fisher, and what it means to inherit a research tradition:
Ed Roberts — what an advisor is actually for, and what compounds across generations → Stanford Innovation Survey (2011–present)
With William F. Miller · Foundational publication: Foundations and Trends in Entrepreneurship, 14(2) (2018)
Survey of more than 140,000 Stanford alumni. Showed that companies founded by Stanford alumni generate trillions of dollars in revenue and millions of jobs globally — the empirical backbone of the "Stanford economic impact" finding now widely cited in policy and university-impact discourse.
Entrepreneurial Impact: The Role of MIT
With Edward B. Roberts · Kauffman Foundation report (2009)
The MIT alumni-impact study — and the methodological forerunner of the Stanford Innovation Survey. Found that companies founded by MIT alumni would, if grouped as an independent nation, generate roughly $2 trillion in annual worldwide sales — the 11th largest economy in the world at the time.
Read the report on Kauffman.org ↗ The Economic Impact of Entrepreneurial Alumni: University of Virginia
With Michael Lenox, Andrew King, and Asif Mehedi · UVA Darden Batten Institute (2014)
The third in the alumni-impact trilogy (after MIT 2009 and Stanford 2012), applying the same methodology to UVA. Survey of more than 135,000 UVA alumni (22,757 valid responses) found 65,000 alumni-founded companies, 2.3 million employees worldwide, and an estimated $1.6 trillion in annual global revenues.
Read the full report (PDF) ↗ Tsinghua University Alumni Survey
With Tsinghua School of Economics and Management collaborators
Extended the alumni-survey methodology to one of China's leading research universities. Provides the empirical base for comparative work on how university entrepreneurship education differs across institutional contexts.
Papers built on the alumni-survey infrastructure
Do University Entrepreneurship Programs Promote Entrepreneurship?
With Yong Suk Lee · Strategic Management Journal, 42(4), 833–861 (2021)
Survey of 27,783 Stanford alumni asking what CES at the GSB and STVP at the Engineering School actually did to entrepreneurship rates. CES participation had a negative-to-zero effect on rates and STVP had no effect — but CES participants saw lower startup failure and higher long-term firm revenue.
Read the paper ↗ The Persistence of Entrepreneurship and Innovative Immigrants
With Yong Suk Lee · Research Policy (2018)
Stanford alumni survey work showing that Asian American alumni are more entrepreneurial than white American alumni, but non-American Asian alumni are substantially less so — with parental entrepreneurship a strong predictor regardless of group, and intergenerational persistence highest among non-American Asians.
Read the paper ↗ Founding Team Composition and Venture Performance
With David Hsu and Edward B. Roberts · Strategic Management Journal (2014)
Survey of 2,067 MIT alumni-founded ventures showing that all-technical founding teams have a 12.8% greater likelihood of favorable exit in cooperative business environments — challenging the conventional wisdom that diverse business skills always matter most.
Read the paper ↗ Born into Chaos
With Carrington Motley and Wesley Koo · Strategic Entrepreneurship Journal (2023)
How founding conditions shape whether ventures survive or thrive through environmental change — based on the longitudinal data of the alumni cohort.
Read the paper ↗ Public-facing artifacts of the alumni-survey work
Founder interviews recorded as part of the Stanford alumni cohort and the technology entrepreneurship course built around it.
Andy Bechtolsheim — Sun Microsystems co-founder, first check to Google
Recorded with former Stanford Provost William Miller in 2012. On founding Sun, how to decide when to pursue a startup opportunity, the discipline of risk, and the story behind writing the first check to Google.
David Cheriton — Stanford CS, serial founder, co-author of the original Google check
Recorded in 2012. Cheriton on serial founding, the practice of writing the original angel check to Google with Andy Bechtolsheim, and the academic-founder pathway.
Theme 4
Methodological Contributions
Two distinct methodological contributions: large-scale alumni entrepreneur surveys (Theme 3 above), and early adoption of randomized controlled trials, difference-in-differences, and regression discontinuity designs in entrepreneurship research — including the first wave of platform-RCTs in MOOC and accelerator settings, and more recently AI-enabled methods for analyzing regulatory and policy corpora.
Where this work has landed: the MOOC-platform RCTs (Eesley & Wu, MIS Quarterly 2020; Eesley & Wang, Research Policy 2017) opened a now-standard methodological vein in entrepreneurship research; the Kauffman-Nesta Research Grant (2014) and the IACMR–RRBM Responsible Research in Management Award (2020) recognized the broader methodological program; NSF I-Corps trainer service (2023–2026) and reviewer/advisor work on NSF's STEM Translation and Commercialization study (Award #2337688) extend the methodological infrastructure into federal innovation policy.
Learning-by-Advising? Startup Learning as an Advice-Giver in Accelerators
Working paper, with Zhuoxuan (Fanny) Li and Jungyun Han (December 2024)
Randomized field experiment in a Thai online accelerator (AIS and KBank, 2021–2023, n=166 startups across multiple cohorts). Tests whether structured peer evaluations benefit the advice-giver, not just the receiver. Treatment teams gained +0.217 on independent pitch-quality scores (~⅓ of a SD, p=0.004) and +0.108 on idea usefulness (p=0.042); no significant novelty effect. Mechanisms: rubric-applying memory reinforcement, and metacognitive self-reflection.
Uganda Refugee Entrepreneurship RCT
With Zahra Hejrati, the AMENA Center, and local Ugandan partners · Stanford Social Impact Labs Design Fellowship (2024)
Field-experimental study of entrepreneurship training in refugee camps and settlements across Uganda. Foundation-supported program operations and rigorous evaluation, designed in partnership with the practitioners running the program.
Platform-RCT on the NovoEd MOOC
With Lynn Wu · MIS Quarterly (2020)
Among the earliest large-scale randomized experiments embedded in an online entrepreneurship platform — testing what kinds of mentor connections and what kinds of adaptability actually predict whether early-stage ventures succeed.
Read the paper ↗ Difference-in-Differences and Regression Discontinuity in Industrial Policy Evaluation
Working papers, with Yikai Cao, Guankai Zhai, Wanru Deng, Rishee Jain, and Dinesh Moorjani
The export-controls, IRA cleantech, and China battery-subsidies papers (Theme 1) each rely on quasi-experimental designs to identify the causal effect of large-scale policy shocks on venture capital allocation and firm entry composition.
Four Paradigms for AI-Enabled Social Science Research
Lightning talk, with Guankai Zhai · FDS Workshop on AI for Social Science Research Methods, Yale University (May 22, 2026)
How generative AI is reshaping social-science research design — from automated coding and synthetic experimentation to LLM-based content analysis of regulatory and policy corpora. Reflects the methodological direction of the current research program.