Janne Toivola
I'm a postgraduate student at Aalto University and recently started as a software engineer at Eigenor. During the years 2003-2013, I was working as a research assistant and later as a researcher in the Parsimonious Modelling group in HIIT and Algodan. I have participated in ISMO, a multidisciplinary research project dealing with structural health monitoring and wireless sensor networks. I also collaborated in the Wireless Sensor Systems group.
See ISMO demonstrator in action.
Research and other interests
I'm interested in pattern recognition, machine learning, probabilistic graphical models, digital signal processing, embedded and distributed systems, and computer graphics. In addition to computer and information science as my major, I have studied software systems and interactive digital media as minors. Hobbies include amateur radio (OH2GXN) and electronics.
Recently, I compiled a list of interesting references. BibTeX.
Contact information
E-mail: janne.toivola
aalto.fi
(NOTE: There is also another Janne
Toivola, if the above portrait does not look familiar.)
Postal address:
Department of Information and Computer Science
Aalto University School of Science and Technology
P.O. Box 15400
FI-00076 Aalto, Finland
Publications
Automatically generated lists of my publications can be found at ICS Publications and Google Scholar.
M. Á. Prada, J. Toivola, J. Kullaa, J. Hollmén.
Three-way analysis of structural health monitoring data.
Neurocomputing 80, pages 119-128. Elsevier, March 2012.
DOI.
J. Toivola and J. Hollmén.
Collaborative filtering for coordinated monitoring in sensor networks.
In Proceedings of the ICDMW 2011 11th IEEE International Conference on
Data Mining Workshops, pages 987-994.
IEEE Computer Society, December 2011.
DOI.
Presentation slides.
M. Bocca, J. Toivola, L. M. Eriksson,
J. Hollmén, and H. Koivo.
Structural health monitoring in wireless sensor networks by the
embedded Goertzel algorithm
In Proc. of the 2nd ACM/IEEE International Conference on Cyber-Physical
Systems (ICCPS 2011), pages 206-214.
IEEE, April 2011.
DOI.
M. A. Prada, J. Hollmén, J. Toivola, and
J. Kullaa.
Three-way
Analysis of Structural Health Monitoring Data
In Proc. of
the 2010 IEEE International Workshop on Machine Learning for Signal
Processing (MLSP 2010), pages 256-261.
IEEE, August 2010.
DOI.
J. Toivola, M. A. Prada, J. Hollmén.
Novelty
Detection in Projected Spaces for Structural Health Monitoring
In Advances in Intelligent Data Analysis IX, Proceedings of the
9th International Symposium on Intelligent Data Analysis (IDA 2010),
volume 6065 of LNCS, pages 208-219.
Springer, Berlin/Heidelberg, May 2010.
DOI.
Presentation slides.
J. Toivola, J. Hollmén.
Feature
Extraction and Selection from Vibration Measurements for Structural Health
Monitoring
In Advances in Intelligent Data Analysis VIII, Proceedings of the
8th International Symposium on Intelligent Data Analysis (IDA 2009),
volume 5772 of LNCS, pages 213-224.
Springer, Berlin/Heidelberg, August 2009.
DOI.
Presentation slides.
R. Gwadera, J. Toivola, J. Hollmén.
Segmenting multi-attribute sequences using dynamic Bayesian networks
In Proceedings of The 1st Workshop on Data Mining of Uncertain Data
(DUNE 2007),
in conjunction with the 7th IEEE International Conference on Data Mining
(ICDM 2007).
IEEE Computer Society Press, Washington DC, USA, October 2007.
Also available at portal.acm.org
and DOI.
Presentation slides.
Master's Thesis
J. Toivola.
Modular specification of dynamic Bayesian networks for time series
analysis.
Master's thesis, Helsinki University of Technology, Finland, Jan. 2007.
PDF
(one-sided layout, 564kB)
PDF
(two-sided layout, 569kB)
Presentation slides
(in Finnish, 951kB)
Software
NIP - Dynamic Bayesian Network library
The stuff written for my MSc thesis is available via
GitHub:
git://github.com/oh2gxn/nip.git
Other
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