THE CORTEX - What's so Deep about Deep Learning?"

ML Show & Tell

What's so Deep about Deep Learning?"

Hello fellow data scientists, mathematicians, neuroscientists, biologists, engineers and curious humans,

Thanks to the incredibly positive feedback we received from our last panel night, we are now ready to launch our second panel discussion at the beautiful GoPro offices in Carlsbad.

The panelists will cover some of the principles, tools, and applications of Neural Networks / Deep Learning in their research and business

Speakers

Ping Wang

Director of Qualcomm Robotics Accelerator powered by Techstars. Founder & Partner at the Ansir Innovation Center. Mr. Wang holds a Ph.D in Neuroscience from UCSD and has researched natural and artificial neural networks. His professional experience includes cutting-edge research into enhancing artificial intelligence, finding cures to neurological disorders, neuro-prosthetics & augmentation, and brain inspired neuro-computing.

Henrik Christensen

Director of the Contextual Robotics Institute at UCSD. Prior to UC San Diego, he was a Distinguished Professor of Computer Science in the School of Interactive Computing at the Georgia Institute of Technology. He also serves as the director of the Center for Robotics and Intelligent Machines. Dr. Christensen has published more than 250 contributions across robotics, vision and artificial intelligence.

Desmond Chik

Senior Engineer for Computer Vision at GoPro / Chief Scientist, Co-Founder @ Lumific. Mr. Chik is an entrepreneur with a strong interest in deep learning. He applies machine learning and computer vision tech to improve the editing and storytelling experience of GoPro videos. At Lumific, Desmond leads the development of core computer vision and machine learning algorithms for assisted photo management, which automatically sorts and edits photos stored in the cloud and on the mobile device.

Tristan Webb

Tristan Webb received his Ph.D. in Complexity Science from the University of Warwick in 2013. His contributions include neural network simulations of brain decision making invoking biologically derived parameters. Machine learning was an important part of his scientific workflow, providing analysis for the computational neuroscience simulations. After moving to San Diego he worked as a postdoc at USCD and later two years in the software industry specializing in Functional Programming. Tristan is a strong believer that Deep Learning is a major growth field, and he works as an independent contractor currently. His next plans include work in cloud-based financial analysis and Deep Learning graphical models.