Hesham Eraqi is currently a Senior Principal Research Engineer and Artificial Intelligence Pre-Expert at Valeo, in addition he is an Adjunct Faculty at the Computer Science and Engineering department at the American University in Cairo (AUC). He received his Bachelor degree in Electronics Engineering in 2010, and the Master of Science degree in Computer Engineering in 2014 from Cairo University. He has been a PhD fellow candidate with Highest Honors and highest GPA in class, and was a Teaching and Research Assistant at AUC for 5 years. With 7+ years of experience in the Automotive software industry besides working in academia, Hesham’s experience mix between conducting pure academic research and developing high technology commercial products that are now available in the market. They Autonomous Driving and Active Safety-related products using Artificial Intelligence technologies. His research team at Valeo conducts industrial research focused in these two areas. In addition to his filled patents worldwide, Hesham’s publications, including book chapters and international conference papers, are mainly in Artificial Intelligence and Deep/Machine Learning. He also has a variety of own-developed awards-winning projects and he is an active technical web blogger. In addition to university-level teaching, Hesham Eraqi has conducted thousands of industrial training and workshops hours. He is a speaker in several top international conferences and serves as reviewer in top academic journals and international conferences in his area of research.
About the Tutorial
Smart Cities & Object Detection with Modern Artificial Intelligence
Goals and objectives
What is Modern AI? Why is it very successful in detecting objects and understanding scenes from cameras automatically? How can this help in achieving real smart cities and save tremendous cost? How to enable such technology and what is needed? There will be a coding technical tutorial at the last hour of the tutorial to see how modern AI software libraries make it an easy task to achieve.
Pre-requisites for the tutorial
1- Basic statistics knowledge (mean, variance, standard deviation, etc.).
2- Linear algebra (vectors, matrices, etc.).
3- Calculus (differentiation, integration, partial derivatives, etc.).
4- Experience with programming.