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.
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.
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.