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Muyinatu Bell Shares Top Recommendations for Implementing Artificial Intelligence & Machine Learning Solutions

Muyinatu Bell Shares Top Recommendations for Implementing Artificial Intelligence & Machine Learning Solutions

In this keynote speaker spotlight, Muyinatu Bell shares her top recommendations for healthcare innovators implementing artificial intelligence and machine learning solutions. She also shares her thoughts on being selected by MIT Technology Review as one of 35 Innovators Under 35 in 2016, her thoughts on the next generation of healthcare, how intelligent automation technologies helped inspire her to develop innovative biomedical solutions, and what she hopes attendees will learn from her keynote session.

Dr. Bell is an Assistant Professor of Electrical & Computer Engineering with a joint appointment in the Department of Biomedical Engineering at Johns Hopkins University. She directs the Photoacoustic and Ultrasonic Systems Engineering (PULSE) Lab, a highly interdisciplinary research lab that integrates optics, acoustics, robotics, signal processing, and medical-device design to engineer and deploy innovative biomedical imaging systems that simultaneously address unmet clinical needs and significantly improve the standard of patient care. Dr. Bell completed a postdoctoral fellowship with the Engineering Research Center for Computer-Integrated Surgical Systems and Technology at Johns Hopkins University, obtained a PhD in biomedical engineering from Duke University, earned a BS in mechanical engineering (biomedical engineering minor) from the Massachusetts Institute of Technology, and spent a year abroad as a Whitaker International Fellow at the Institute of Cancer Research and Royal Marsden Hospital in the United Kingdom. She was honored by MIT Technology Review as one of 35 Innovators Under 35 in 2016.


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