Email: nurahmed(AT)
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I am a Postdoctoral associate at MIT Sloan & MIT CSAIL. I completed my PhD in Strategy from Ivey Business School, Canada, and have an engineering degree in Computer Science majoring in AI. My research focus is broadly on Innovation, Entrepreneurship and Technology Strategy.

The ability to benefit from investment in basic scientific research concerns both large firms and startups. Drawing on the burgeoning literature of "science of science," I examine the factors that motivate firms to pursue basic scientific research and voluntarily disclose them in the public domain (e.g., publications, patents). To this end, I build a research program for corporate R&D using Artificial Intelligence as an empirical context. In particular, I propose the Iceberg Model of R&D Disclosure Strategy, which details the notion that firms tend to minimize outgoing knowledge (e.g., “secrecy” is the preferred channel) and selectively reveal internal knowledge strategically (e.g., timing, topics, content). Further, I examine the role of specialized assets like human capital (scientists), computing power, and data in innovation processes. Drawing on strategic management literature, and using Big Data, Machine learning (NLP methods like word embedding), and interviews, I build testable models of the world that can help managers and policymakers to make decisions.

Previously, I worked as a Software Engineer for Samsung R&D Lab in Bangladesh, India, and South Korea. My research is partly informed by experiences at such corporate labs.

My working papers have been recognized at multiple conferences such as Best PhD Paper Prize (nominated, SMS), Max Boisot Award (finalist, EGOS), Best Paper in Strategy (won, AMCIS), Honorable Mention (won, ASAC), Best Paper Award (nominated, Israel Strategy Conference) among others. Finally, my research has also received media coverage from outlets like VentureBeat, Scientific American, Axios, Marginal Revolution, State of the AI. Three prestigious AI reports cited my work: The National Security Commission on Artificial Intelligence and Stanford AI Index (2021), National Artificial Intelligence Research Resource (2022).

Latest News:

I am co-organizing two symposia at AOM 2022,

  • Corporate R&D Disclosure (panelists: David Hsu, Hong Luo, Sharon Belenzon, Deepak Hegde, Raffaele Conti)

  • Scientists within Corporate Environment (panelists: Matt Marx, Waverly Ding, Anita McGahan, Keyvan Vakili, Denisa Mindruta).

I recently presented at the NBER Productivity Seminar (May 2022).

Organized a special SMS panel titled "The Promise and Potential Perils of Using Machine Learning Techniques in Management Research." (2021)

Panelists: Riitta Katila, Jorge Guzman, Florenta Teodoridis

I have received an R&R from SMJ.

I recently chaired the organizing committee of the 3rd Toronto Fintech Conference.