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Personal profile

Research

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.

Teaching

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).

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 11 - Sustainable Cities and Communities
  • SDG 13 - Climate Action
  • SDG 16 - Peace, Justice and Strong Institutions

UKÄ subject classification

  • Signal Processing
  • Computer Vision and Robotics (Autonomous Systems)

Free keywords

  • Machine Learning, Computer Vision, Optimization, Pattern Recognition, Mathematics, Signal Processing

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