Deep Learning Summer School

Aug 01 2016

I participated in the Deep Learning Summer School organized by the CIFAR Institute and the CRM Center of Canada. This event took place at the University of Montreal, and it consisted of a series of lectures covering a broad range of topics about deep learning from a machine learning perspective touching multiple applications like computer vision, natural language processing, and robotics. The talks were given by top researchers in each area working in academia (NYU, MIT, Stanford) and industry (Google, Facebook, Twitter, etc.) such as Rob Fergus, Jeff Dean, Yousha Bengio among others.

It was the second edition of this summer school, which it is pretty selective, with an acceptance rate around 25%. In that sense, it was a pleasant experience for me to talk with highly competitive people from academia and industry working at the heart of deep learning models. It was a really insightful experience to hear about the way other researchers are tackling their specific problems as well as their perception of the field and the relevant challenges in the next couple of years. Another essential part of the summer school was the opportunity to present recent and ongoing research work, I took advantage of it to talk and discuss my latest work accepted for ECCV-2016. Our work was received well from practitioners and researchers, a group of people is eager to try it out for specific applications such as sports analytics and pedestrian analysis, and others are interested in built on top of our observations.

In summary, it was a splendid time to learn, network with people and spread the presence of KAUST through the work of a member of the Visual Computing Center.