I am an economist of innovation and intellectual property, studying how how legal and policy frameworks shape the creation and commercialization of new technologies. My expertise spans innovation and technology policy, IP strategy and regulation, the measurement of R&D and intangible assets, technology transfer, and competition issues around standard-setting and licensing. Methodologically, I work with large-scale administrative and digital data—especially on patents and scientific publications—using applied econometrics, causal inference, and machine learning to produce evidence that is useful to policymakers, firms, and courts.

Our lab studies how innovation systems work, with a focus on the economics and policy of intellectual property and technology commercialization. We combine large-scale patent and publication data with advanced econometrics and machine learning to measure innovation, assess the value and quality of patents, and understand how ideas diffuse through markets and technologies. Working at the intersection of academia, policy, and practice, we aim to generate rigorous, data-driven evidence that helps governments design better innovation policies and helps firms and other stakeholders make more informed decisions about protecting and deploying new technologies.