Douglas Hamilton works across business units at Nasdaq to deploy artificial intelligence anywhere the technology can expedite or improve processes related to global trading. In this episode of Me, Myself, and AI, he joins hosts Sam Ransbotham and Shervin Khodabandeh to explain how the global financial services and technology company uses AI to predict high-volatility indexes specifically and to offer more general advice for those working with high-risk scenarios. Read the episode transcript here.

Me, Myself, and AI is a collaborative podcast from MIT Sloan Management Review and Boston Consulting Group and is hosted by Sam Ransbotham and Shervin Khodabandeh. Our engineer is David Lishansky, and the coordinating producers are Allison Ryder and Sophie Rüdinger.

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Guest bio:

A data scientist by trade, Douglas Hamilton is the head of AI research at Nasdaq’s Machine Intelligence Lab, which is dedicated to clarifying and improving financial markets with machine learning. He joined Nasdaq in 2017 as a data scientist and developed AI solutions focusing on rapid adaptation, reinforcement learning, and efficient market principles as solutions to predictive control problems. Before joining the financial technology industry and spearheading Nasdaq’s machine intelligence initiatives, Hamilton led an advanced manufacturing analytics group at Boeing Commercial Airplanes and built customer relationship management systems at Fast Enterprises. He is a veteran of the U.S. Air Force and a member of the advisory board of The Data Science Conference. Hamilton holds a master of science degree in systems engineering from MIT and a bachelor’s degree in mathematics from the University of Illinois Springfield.

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