Interview with Muyinatu Bell, Johns Hopkins University

This interview took place at the Deep Learning in Healthcare Summit, Boston 2017.

Monique sat down with Muyinatu to find out more about her and her thoughts on the following questions:
- What motivated you to start your work in machine learning?
- What inspired you to use machine learning to improve Photoacoustic-Guided Surgery?
- Tell us a bit more about your current work with the PULSE lab?
- Looking into the future, what developments of deep learning applications excited you the most?
- What advice do you have for new entrants into the field?
- Collaborations of different fields is sometimes essential for the development of another field, which fields do you think would complement machine learning & healthcare?

Muyinatu Bell, Assistant Professor at Johns Hopkins University

Muyinatu A. Lediju 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. 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 recently honored by MIT Technology Review as one of 35 Innovators Under 35 in 2016.

Monique Brouillette, Science Reporter at Freelance

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