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Aku Seppänen


Academy Research Fellow
Ph.D, Docent
Phone: +358 40 7405624
Room: Me-228 (Melania)
Fax: +358 17 16 2585
Skype: aku.seppanen
Email: Aku.Seppanen(at)uef.fi

List of Publications (pdf)

M.Sc -thesis: Correction of Collimator Blurring
and Attenuation in Single Photon Emission
Computed Tomography (pdf), 2000
Ph.D -thesis: State Estimation in Process
Tomography (pdf), 2005
Docentship: Applied Inverse Problems, 2011

Research Areas
Inverse problems & uncertainty quantification
• Electrical Impedance Tomography
Non-destructive testing of concrete
Industrial process tomography
Remote sensing of forest

Teaching: Lectures
• Statistical Inverse Problems (Autumn 2017)
• Transport Phenomena (Spring 2017)
Video of the lecture in science week 2012
(In Finnish)
Jyväskylä Summer School 2014:Course on
Statistical and Computational Inverse
Problems with Applications (August 2014)

My Research Team
Christina Brandt (postdoc)
Teemu Luostari (postdoc)
Petri Varvia (PhD student)
Antti Voss (PhD student)
Danny Smyl (visiting PhD student, NCSU, Sept'16-May'17)
Niko Hänninen (MSc student)
Tuukka Heiskanen (BSc student)

Supervision: Completed thesis works
PhD theses: 3 as primary supervisor
(Kimmo Karhunen, Antti Lipponen, Dong Liu),
1 as secondary supervisor (Anna Kaasinen)
MSc theses: 5
BSc theses: 4
BEng theses: 1

Research highlights:


The UEF Inverse problems group and the group of Prof. Mohammad Pour-Ghaz from North Carolina State University have recently developed a new 'sensing skin' technology for detecting cracks in concrete structures. The research has drawn a wide interest in public mediait has been reported e.g. by phys.org, NASA Tech Briefs, wn.com, Science Newsline, ScienceDaily, Durability+Design, materialstoday, theEngineer, World Industrial Reporter and Capitalista. In Finnish press, the research was noted e.g. by Aamulehti, Turun Sanomat, Maaseudun tulevaisuus and Yle.

► M. Hallaji, A. Seppänen, M. Pour-Ghaz: Electrical impedance tomography-based sensing skin for quantitative imaging of damage in concrete, Smart Materials and Structures, 23: 085001, 2014.