about

My research studies the commercialization of scientific innovations and the diffusion of technologies into markets. Along with my research, I develop novel datasets and tools. Check out scientifiq.ai, our platform to help advance research on innovation.

Prior to academia, I founded a startup providing software and machine learning translation solutions for large firms. I also spent years in M&A, where I led numerous projects in technological sectors such as advanced water treatment technologies, biotech, energy generation, and materials science.

I will be on the job market during the 2025-2026 academic year.

published articles

• Measuring the Commercial Potential of Science with S. Hasan and W. Cohen paper | data | code

  Conditional Accept, Strategic Management Journal (March 2025); NBER Working Paper 32262

  Abstract: We develop an ex-ante measure of commercial potential of science, an otherwise unobservable variable driving the performance of innovation-intensive firms. To do so, we rely on LLMs and neural networks to predict whether scientific articles will influence firms' use of science. Incorporating time-varying models and the quantification of uncertainty, the measure is validated through both traditional methods and out-of-sample exercises, leveraging a major university’s technology transfer data. To illustrate the methodological contributions of our measure, we apply it to examining the impact of university reputation and university privatization of science, finding that firms’ reliance on reputation may lead to foregone opportunities, and privatization (i.e., patenting) appears to increase firms’ use of the science of one university. We make our measure and method available to researchers.

working papers

• Scientific Innovation, Outside Options, and Hold Up: Evidence from Startup Acquisitions

  Abstract: Scientific innovations increasingly rely on startups to reach the market. Yet, in critical areas like energy, industrials, and materials—crucial for addressing social challenges—startup activity remains limited. This issue is often associated with high risks and low economic value. I propose a complementary explanation: a hold-up problem that constrains value capture. Startups commercializing scientific innovations often cannot scale independently and depend on a few incumbents, reducing outside options and weakening bargaining power. Empirically, I estimate value creation and capture by examining stock market reactions to startup acquisitions, filtering out unrelated noise, and assess outside options using fine-tuned Large Language Models. The study reveals three main findings. First, estimates show that in industries where hold-up is more severe, science startups capture 46 cents per dollar of surplus generated, compared to 70 cents for non-science ones—a 34% penalty. Second, these effects are mitigated when I control for outside options. Third, startups with lower capture create more value, offsetting the penalty and explaining entry. The findings suggest that hold-up is pervasive, reducing upstream incentives for investment and potentially leaving valuable innovations underfunded. Policy and management should focus on fostering competitive markets for technology and enhancing commercialization pathways.

• Taste Before Production: The Role of Judgment in Entrepreneurial Idea Generation with A. Chatterji, S. Hasan, and R. Larrick paper

  Abstract: Crafting high-quality ideas is crucial for entrepreneurs to succeed, yet evidence about the factors that shape the idea-generation process is scarce. A long-standing question is whether differences across entrepreneurs in market judgment—the ability to evaluate business ideas—explain differences in ideas’ quality and composition. We conduct an experiment with an intervention that improves subjects’ ability to evaluate an idea’s market potential, finding that improved judgment leads subjects to generate ideas 15% higher in quality and more complete, with stronger effects among initially poorly-calibrated subjects. Our results support a potential mechanism: individuals with developed judgment mentally test more ideas and better filter them before committing to one. Simple training can improve judgment and idea quality, complementing ex-post, experimental methods by reducing the costs of testing ideas.