Personlig profil

Forskning

Mikael Nilsson receicved a M.Sc.E.E with emphasis on Signal Processing in 2002 and a Ph.D. degree in applied Signal Processing in 2007 from Blekinge Institute of Technology, Sweden. He worked as an Asst. Prof. and also during 2010 been acting head of department at department of electitral engineering at Blekinge Institute of Technology between 2007 and 2010. During 2011 and 2013 he was Post. doc. in Mathematics (Faculty of Technology) at the Centre for Mathematical Sciences at Lund University, Sweden.  From 2013 until 2019 he was Adjunct Senior Lecturer in Mathematics (Faculty of Technology) at the Centre for Mathematical Sciences in Lund University (50%) and Developer in industry (50%) at Cognimatics AB and later Axis Communications AB after acquiring Cognimatics 2016.  In 2017 he was appointed to Associate Professor/Reader (swe: Docent) in Mathematics at Lund University, Sweden. Since 2019 he is Senior Lecturer (100%) in Mathematics (Faculty of Technology) at the Centre for Mathematical Sciences at Lund University, Sweden.

 

His current research interest lies in creating new and novel Machine Learning (ML) models and techniques.  The focus is on modern machine learning, i.e. deep neural network designs, in various forms. Often related to problems in Computer Vision (CV), i.e. 3D  estimation of objects or various estimations from images/video. Many times, with an applied flavour in various contexts.

Undervisning

Mikael Nilsson is since 2019 Programme Director for the international masters programme in Machine learning, Systems and control (www.lunduniversity.lu.se/lubas/i-uoh-lu-TAMSR).
Since 2021 he is teaching the Machine Learning course (FMAN45) at LTH (www.kurser.lth.se/lot/course-syllabus-sv/22_23/FMAN45)
He frequently supervises master's thesis projects within ML and CV. (www.kurser.lth.se/lot/course/FMAM05 and www.kurser.lth.se/lot/course/FMAM02).

Expertis relaterad till FN:s globala mål

2015 godkände FN:s medlemsstater 17 Globala mål för en hållbar utveckling, för att utrota fattigdomen, skydda planeten och garantera välstånd för alla. Den här personens arbete relaterar till följande Globala mål:

  • SDG 3 – God hälsa och välbefinnande
  • SDG 11 – Hållbara städer och samhällen
  • SDG 13 – Bekämpa klimatförändringarna
  • SDG 16 – Fredliga och inkluderande samhällen

Ämnesklassifikation (UKÄ)

  • Signalbehandling
  • Datorseende och robotik (autonoma system)

Fingeravtryck

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