Em parceria com Seção Centro-Norte Brasil do IEEE e com apoio do Departamento de Engenharia Elétrica da Faculdade de Tecnologia da Universidade de Brasília, o Capítulo Profissional da IEEE Communications Society da Seção Centro-Norte Brasil (www.facebook.com/IEEEComSocCNBr) tem o prazer de anunciar a Palestra: “IT research at Halmstad University and self monitoring systems“.
Palestrante: Prof. Thorsteinn Rögnvaldsson, (Professor of Computer Science – Halmstad University, Sweden)
Horário: 16h00 – 18h00
Local: Auditório da Faculdade de Tecnologia da Universidade de Brasília.
Coffee-Break de Recepção antes da palestra.
Abordará aspectos gerais da pesquisa na área de IT da Universidade de Halmstad, realizando uma breve apresentação sobre Sistema de Automonitoramento, Sistemas conscientes, Sistemas Embarcados e Sistemas Inteligentes.
Por fim, discorrerá também sobre as oportunidades de estudo para alunos de engenharia.
Biografia do Palestrante
Thorsteinn Rögnvaldsson was born in 1963 in Reykjavik, Iceland but grew up in Lund. He studies theoretical physics at Lund University and completed his PhD at the same university in 1994, after which he spent a few years as researcher at the Oregon Graduate Institute in Portland, Oregon. In 2003 he was appointed as associate professor with a specialism in learning systems at Halmstad University and from 2007 to date he has worked as chairman of the Research Committee for Engineering and Natural Sciences.
Thorsteinn Rögnvaldsson’s interest for the subject area of artificial intelligence and machine learning began with a fascination for physics-based models relating to how the brain works. Although interest for the functions of the brain remains, his principal areas of research are now directed towards applications of intelligent systems such as in for example the car and vehicle industry.
Increased use for machine learning systems is a central driving force for Thorsteinn Rögnvaldsson’s research. He is particularly interested in finding better algorithms, improved in the sense that they make fewer mistakes and can solve a task more quickly and with higher precision.