Currently Faculty of Technologies is hosting Dr. Georgios Ouzounis. Georgios is a computer vision/machine learning engineer specializing in advanced, high performance image/video/data analytics, processing and feature extraction algorithms, cloud processing and distributed systems. Fields of his expertise include artificial, convolutional and recurrent neural networks for 2D/3D deep learning, self-organizing maps and auto-encoders. He has doctorate degree in mathematics and natural sciences. Georgios works as senior computer vision engineer at Arlo Technologies, Inc., in New York (USA).
Georgios Ouzounis was invited to deliver the 5-day intensive course Crash Course in Deep Learning in the period from September 26 to October 2, 2018. The aim of this course is to familiarize students with notions and concepts from the fields of data science and machine- & deep-learning, and to showcase how to build, train and deploy artificial neural networks and other advanced derivative architectures for solving a wide range of real-world challenges. The skill-sets developed upon completion of the course would allow attendants to engage directly in data-analytics problem solving and enrich their curriculum with a ‘must-have’ for the global job market.
The course attendees are the students who study Infotronics, Information Finance Systems, Automatic Control and Administration of Computer Networks.
Deep-Learning is a thriving, state-of-the-art field of data analytics that shapes developments in almost every field of the modern global economy. It is the driving technology in data science and artificial intelligence and has a very broad field of applications. Indicatively, the Deep-Learning market was worth USD 2.28 Billion in 2017 and is expected to reach USD 18.16 Billion by 2023, at a CAGR of 41.7% from 2018 to 2023.
