The 2018 IEEE Data Science Seminar is a new workshop that aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science theory and applications.
In particular, the event will gather researchers and practitioners in various academic disciplines of data science, including signal processing, statistics, machine learning, data mining and computer science, along with experts in academic and industrial domains, such as personalized health and medicine, earth and environmental science, applied physics, finance and economics, intelligent manufacturing.
2018 IEEE UAE Section Data Science Seminar
The 2018 IEEE Data Science Seminar was hold on Saturday, November 24, 2018 from 10:00 AM to 11:45 AM.
The first topic has been delivered by Dr. Giulia De Masi in the title of “Complex Networks in Data Science: from Visualization to Analysis”.
Dr. Giulia De Masi obtained her PhD at the Physics Department of L’Aquila in 2007. She was Post-Doctoral Researcher in the Polytechnic University of Marche and visiting researcher at Hitachi Research Laboratory, in Nara, Japan.
Then she got a position in the
Research and Development field at the Advanced Engineering Department in a leading Italian company in the Energy sector. She had Faculty positions in American University, Canadian University and Zayed University in Dubai.
She has 15+ years of experience in Data Science. Her R&D activities consist in Data Mining, Complex Networks, Machine Learning, Computational Modeling and Decision Making, having more than 30 publications in these fields and more than 40 reports for Industry.
Dr. Giulia has presented the Complex Networks theory that has been developed in last decades in parallel to Data Mining techniques with the common goal to detect patterns in huge amount of available data.
Based on Graph Theory, this approach can be applied to systems where it is possible to identify basic units and relationships between them. Besides systems where there is a clear connection between two nodes (Internet, WWW, transportation networks), network representation can be used also when a functional relationship can be defined or a correlation between single units.
The interest to Complex Network theory is growing in many different fields, namely engineering, finance, economics, biology and ecology, addressing complex networks as an important tool of Data Science. In this talk we focus on benefits of Complex Network approach and its synergies with other Data Mining techniques.
The second topic has be delivered by Dr. Sherief Selim in the title of “Data Science: Not Just For Big Data”.
Dr. Sherief is a passionate technology enthusiast with both field and research experience over 10 years. He currently works for Microsoft as Cloud Solutions Architect helping customers to build application, infrastructure, data and AI solutions on top of cloud.
He is also a PhD Researcher focusing on BlockChain Engineering and Data Science in couple of well know institutes. He has contributed in many standards development for the past 13 years with IEEE, IETF and ITU in networks communities.
Dr. Sherief has presented the data science concept in the every day life examples; the audience has enjoyed his presentation as he has focused on showing how the data science is connected to the IoT and the huge use of this concept using their every day uses.