Dr Traian Emanuel Abrudan
Main research: practical localization algorithms and systems for humans and robots using low-frequency magnetic fields, as well as other sensing modalities
Related research topics:
- sensor array signal processing,
- applied parameter estimation,
- numerical optimization
- wireless transceiver algorithms
- localization and navigation
Traian is a postdoctoral researcher at the Department of Computer Science, University of Oxford. Since October 2013, he has been working as a Research Assistant in Being There project (HARPS - Humans and Robots in Public Spaces). His primary research focuses on practical localization algorithms and systems for humans and robots using low-frequency magnetic fields, as well as other sensing modalities. His fundamental research topics include sensor array signal processing, applied parameter estimation, numerical optimization, and wireless transceiver algorithms.
Traian received the M.Sc. degree from the Technical University of Cluj-Napoca, Romania in 2000, and the D.Sc. degree (with honors) from Aalto University, Finland (formerly known as Helsinki University of Technology) in 2008. During 2001-2010, he was a member of SMARAD (Finnish Centre of Excellence in SMArt RADios and Wireless Research) which has been selected as Center of Excellence in research by The Academy of Finland. During September 2010-2013, he was a postdoctoral researcher at Faculty of Engineering, University of Porto (FEUP), Portugal, and a member of Instituto de Telecomunicações (IT) Porto.
Magneto−Inductive Underground Tracking: Principles and Systems
T. Abrudan A. Markham N. Trigoni and O. Kypris
In Elsevier, editor, Underground Sensing: Monitoring and hazard detection for environment and infrastructure − 1st edition. Chapter 8.2. 2016.
Distortion Rejecting Magneto−Inductive 3−D Localization (MagLoc)
T. E. Abrudan‚ Zhuoling Xiao‚ A. Markham and N. Trigoni
In IEEE Journal on Selected Areas in Communications. Vol. PP. No. 99. Pages 1–14. May, 2015.
Advances in Independent Component Analysis and Learning Machines
V. Koivunen and T. Abrudan
Chapter 4: Riemannian optimization in complex−valued ICA. Pages 83–94. Academic Press. Edition 1. April, 2015.
(Eds: Ella Bingham and Samuel Kaski and Jorma Laaksonen and Jouko Lampinen – In honour of Professor Erkki Oja)