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Luís Paulo Reis

HomeKeynote SpeakersLuís Paulo Reis
KEYNOTE SPEAKER
Luís Paulo Reis

Luís Paulo Reis holds BSc, MSc, and PhD degrees in Electrical and Computer Engineering from the University of Porto. He’s an Associate Professor at DEI/FEUP and Director of LIACC/UP.

AFFILIATION:
University of Porto
Scopus

KEYNOTE TITLE

Artificial Intelligence as a Catalyst for Next-Gen Marketing: From Data to Dynamic Customer Engagement

PERSONAL INFO

Luis Paulo Reis is an Associate Professor with Habilitation at the University of Porto in Portugal and Director of LIACC – Artificial Intelligence and Computer Science Laboratory. He is an IEEE Senior Member and he was president of the Portuguese Society for Robotics and is now president of the Portuguese Association for Artificial Intelligence.

During the last 30 years, he has lectured courses and performed research, at the University, on Artificial Intelligence, Intelligent Robotics, Multi-Agent Systems, Intelligent Simulation, Machine Learning, Games and Interaction, Cognitive and Physical Rehabilitation, Educational/Serious Games and Computer Programming. He was the principal investigator of more than 30 research projects in those areas.

He won more than 50 scientific awards including wining more than 15 RoboCup international competitions and best papers at conferences such as ICEIS, Robotica, IEEE ICARSC and ICAART. He supervised 22 PhD and 150 MSc theses to completion and is supervising 12 PhD theses. He evaluated more than 50 projects and proposals for FP6, FP7, Horizon2020, FCT and ANI. He was a plenary speaker at several international conferences such as ICAART, ICINCO, LARS/SBR, WAF, IcSports, SYROCO, CLAWAR, WCQR and ECIAIR. He organized more than 60 international scientific events and belonged to the Program Committee of more than 300 scientific events. He is the author of more than 400 publications in international conferences and journals (indexed at SCOPUS or ISI Web of Knowledge).

RESEARCH AREAS

  • Artificial Intelligence
  • Intelligent Robotics
  • Multi-Agent Systems
  • Machine Learning

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