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What can AI learn from our own brains? Bridging the gap between biology and code
AI grows ever more powerful and ubiquitous, powered by vast sources of data and inexpensive cloud processing power. Yet the human brain, using just 25W of power and 6 kHz neuron speed, remains many orders more efficient than current AI processing approaches. Leveraging insights from new optical and physiological recording techniques, Prof. Bart M. ter Haar Romeny will help bridge the gap between AI and how the human brain processes sight, giving practical applications with respect to computer vision and machine learning, especially in medical image analysis such as neuroimaging that can help accelerate neurology research, clinical trials and care delivery.
A 30 minute lecture by Em.Prof. Romeny will be followed by a chat with his former students, Vesna Prčkovska, CEO, and Paulo Rodriguez, CTO of QMENTA. Please bring your questions for our closing Q&A. Zoom space is limited, so reserve your place today.
– How we can bridge the gap between biological and AI communities
– New optical and physiological recording techniques in imaging analysis
– Practical applications with respect to computer vision and machine learning
Prof. Bart M. ter Haar Romeny is emeritus professor in Biomedical Image Analysis at Eindhoven University of Technology in the Netherlands. He obtained his MSc in Applied Physics from Delft University of Technology and PhD from Utrecht University.
He worked his whole career on biologically inspired medical image analysis algorithms, especially for computer-aided diagnosis (cancer, heart, brain, diabetes), image guided neurosurgery and visualization of brain connectivity from MRI diffusion tensor imaging. He initiated and led the RetinaCheck project, a large international AI-based retinal image screening program for diabetes. He published over 250 papers, 12 books and book chapters, and 3 patents. He teaches a national PhD course on the neuro-mathematics of deep learning and human visual perception.