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OVERVIEW
OVERVIEW
I study how emerging technologies move from technical possibility to real-world adoption. Across work on drones, robotics, automation, and state technology policy, I examine how firms, workers, governments, and ecosystems respond to uncertainty. I am especially interested in why promising technologies succeed in some organizational and institutional settings while stalling in others.
My work is mixed-methods, combining user and stakeholder interviews with archival data, web scraping, market analysis, and policy datasets. Across projects, I turn messy evidence into frameworks, case studies, and practical insights that help people understand where adoption stalls, what conditions enable scale, and how organizations can make better decisions about emerging technologies.
Together, these projects ask the same question at three altitudes: inside organizations, where adoption succeeds or stalls; across products and policies, where regulation shapes what gets built; and at the scale of an entire industry, where bottlenecks shift as a market matures.
Smart Machines in a Messy World
Smart Machines in a Messy World
Why do robots that work in controlled settings struggle on real job sites? Drawing on 30+ interviews, field engagement, and a mapped landscape of 300+ construction robotics companies, this project examines how workflow fit, trust, liability, and buyer readiness shape adoption. The research shows that technical capability is rarely enough: successful firms begin with narrow use cases, build credibility, and redesign the surrounding system as they scale.
Methods: Interviews, ecosystem mapping, field research, and facilitated discovery.
How One Regulation Standardized Drone Innovation
How One Regulation Standardized Drone Innovation
I expected clearer rules to set drone design free. Instead, tracking 335 agricultural drone models launched between 2000 and 2021, I found that new designs converged around the FAA's 55-pound standard: the rule itself became a design magnet. The exceptions were local. Firms near industry consortia followed the standard even more closely, while firms near farmer-facing knowledge networks kept experimenting. Regulation sets the standard. Unconventional designs survive in the places where builders and users learn together.
Methods: Longitudinal product data, regulatory filings, archival research, web archives, and quantitative analysis.
Building an Industry Before the Market Exists
Building an Industry Before the Market Exists
How does a new technology become a functioning market? Mapping 2,130 drone companies across Chinese cities, this project follows the emergence of China’s civilian drone industry from early technical experimentation through commercialization and regulation. It shows how the central bottleneck shifted over time, requiring different forms of ecosystem and institutional support at each stage.
Methods: Ecosystem mapping, firm and city-level data, value-chain analysis, policy analysis, and industry interviews.
How States Place Their Technology Bets
How States Place Their Technology Bets
How do governments invest in emerging technologies when no one knows which industries or interventions will succeed? This project transforms 6,800 policy reports into a dataset of 1,659 state-led experiments, revealing four distinct approaches to innovation policy. The findings show that how states distribute their bets across technologies and partners matters more than how much they experiment, and that cross-sector partnerships can make experimentation more resilient during economic shocks.
Methods: Web scraping, natural-language processing, policy coding, portfolio analysis, economic indicators, and interviews with state officials.
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