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Dec 3, 2024
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Neil Thompson
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Neil Thompson is an Innovation Scholar at MIT’s Computer Science and Artificial Intelligence Lab and the Initiative on the Digital Economy. He is also an Associate Member of the Broad Institute.
Previously, he was an Assistant Professor of Innovation and Strategy at the MIT Sloan School of Management, where he codirected the Experimental Innovation Lab (X-Lab), and a Visiting Professor at the Laboratory for Innovation Science at Harvard University. He has advised businesses and government on the future of Moore’s Law and Machine Learning, and has been on National Academies panels on transformational technologies and scientific reliability.
He did his PhD in business and public policy at UC Berkeley, where he also did Master's degrees in computer science and statistics. He has a Master's in economics from the London School of Economics, and undergraduate degrees in physics and international development. Prior to academia, he worked at organizations including Lawrence Livermore National Laboratories, Bain and Company, The United Nations, the World Bank, and the Canadian Parliament.
Publications
"How to Measure and Draw Causal Inferences with Patent Scope."
Kuhn, Jeffrey M., and Neil Thompson. International Journal of the Economics of Business. Forthcoming.
"Science is Shaped by Wikipedia: Evidence From a Randomized Control Trial."
Thompson, Neil C., and Douglas Hanley, MIT Sloan Working Paper 5238-17. Cambridge, MA: MIT Sloan School of Management, September 2017.
"Firm Software Parallelism: Building a Measure of how Firms will be Impacted by the Changeover to Multicore Chips."
Thompson, Neil. 2012.
"Intellectual Property and Academic Science."
Thompson, Neil. 2012.
"The Statistics of a Fundamental Change in how Computers Work and its Impact on Firm Productivity."
Thompson, Neil. 2012.
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