Neal Bangerter is an Associate Professor of Bioengineering at Imperial College London.
His current research interests include the application of artificial intelligence and machine learning to a variety of problems in medical imaging and healthcare, and the development of novel medical imaging technologies.
In addition to his research and teaching interests, Neal is passionate about innovation/entrepreneurship and intellectual property strategy. He regularly consults and advises in these areas. He has deep technical expertise in healthcare, medical imaging, machine learning, big data, signal processing, and software development, and significant management and strategy experience from his work in industry.
Neal holds a BA with honors in Physics from UC-Berkeley and a Master’s and PhD in Electrical Engineering from Stanford University. He has held permanent and visiting positions at Oxford University, INSEAD, Brigham Young University, University of Utah, Microsoft, and management consulting firm McKinsey & Company.
Humans are good at processing messy data. Computers, not so much.
Some believe the singularity is near, others are sceptical.
Although Neal thinks we are still “a long way from artificial general intelligence, where a machine could successfully perform any intellectual task that a human being can,” AI does have a significant role to play in certain areas.
The limitations of messy data
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