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Dr.  EL-FAKDI SENCIANES, ANDRES

Plana personal

Categoria
INVESTIGADOR ORDINARI
Departament
ENGINYERIA ELÈCTRICA, ELECTRÒNICA I AUTOMÀTICA
Àrea de coneixement
ENGINYERIA DE SISTEMES I AUTOMÀTICA
Institut
INSTITUT DE RECERCA EN VISIÓ PER COMPUTADOR I ROBÒTICA (VICOROB)
Grup de recerca
Agents Research Lab.
ORCID PRC:
0000-0002-9865-3039

Currículum abreujat

My name is Andres El-Fakdi, Smart Cities Master co-coordinator and researcher in the Department of Electrical Engineering, Electronics and Automation at the University of Girona. I'm a member of the Tecnio Centre EASY in the Agents Research Laboratory. My research interests are focused in contributing to the development of modern societies in urban environments. For this purpose, my studies are related with the application of machine learning techniques for Big Data Analytics and the use and development of blockchain technologies for distributed security and IP assurement. My field of work are smart cities.

Along the PhD my research has been focused on the study and development of machine learning techniques and its application to autonomous mobile robots and autonomous underwater vehicles in real robotics tasks. The purpose of my PhD research has been to demonstrate the feasibility of artificial intelligence for learning in open scenarios. Therefore, my PhD succesfully concluded with the utilization of learning algorithms to overcome not programmed changes in the environment conditions which lead robots to fulfill particular tasks. Nowadays, my post doctoral research is centered in the study, design and development of machine learning solutions for knowledge extraction in high complex processes, usually related with smart cities.

Improving cities is a pressing global need as the world’s population grows and our species becomes rapidly more urbanized. Thanks to the relative ease with which local governments can now gather real time data, combined with the capabilities of artificial Intelligence, cities are realizing interesting new ways to run more efficiently and effectively. Therefore, current research carried out at our research group and with our smart city master students is aligned with the application of machine learning techniques and blockchain technologies for big data analytics, smart traffic and parking management, energy efficiency in buildings, citizen participation and e-government.

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