As Boeing China’s regional director of airspace and airport programs, Helen Lee is helping the aerospace giant work toward improving airport and airspace operational efficiency and enhancing flight safety for its aviation customers. In this episode, Helen discusses ongoing research that involves using AI to analyze the wake turbulence of aircraft with computer vision systems, using speech recognition to analyze interactions between pilots and air controllers to minimize the potential for human error, and using image recognition to scan planes for needed repairs. Helen also talks about the challenges of implementing such technology across a complex industry in which there’s no tolerance for error and systems must be impenetrable to hackers. 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:

Helen H. Lee is responsible for managing and coordinating Boeing’s airport, airspace, and air traffic management programs in the Greater China region. She also initiates and provides technical guidance and insight to related programs in the region. She is the first China-based employee to be selected as a Boeing Technical Fellow, the company’s most elite team of technical experts.

Previously, Lee served as air traffic management (ATM) research lead for Boeing Research & Technology-China, where she planned and managed all ATM-related research projects involving Chinese domestic research partners. Before joining Boeing, she was a senior consultant at Boeing Jeppesen Airspace and Airport Services Group, where she led a project team that provided simulation and consulting services in support of major airport and airspace modernization efforts worldwide. Lee earned a doctoral degree in aerospace engineering from the University of Minnesota.

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