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university of tampere: sis/luo-coms: research: cis - the tampere research center for information and systems: research groups: darg:
Faculties of Natural and Communication SciencesUniversity of TampereFaculties of Natural and Communication Sciences
CIS - The Tampere Research Center for Information and Systems

We study data analysis methods as such and to apply them in various types of data, medical especially. One of our long-run themes is the classification of otoneurological patient data according to diseases, Meniere disease as an example. Here the objective is to develop computer-aided decision making for physicians. However, actual complicated data sets are only an interesting application area, and our main target to develop data analysis methods, particularly for preprocessing. We have studied feature selection and evaluation methods of variables to determine the importance of variables for a user or data analysis purposes. Recently we began to study image data analysis with benthic macroinvertebrates, which are small bugs living in river bottoms. These images used for the control of water quality were scanned in the Finnish Environment Institute in Jyväskylä. Not only the data itself is interesting, but our main objective is to study support vector machines in multiclass (c>2) classification.

We have studied medical signal analysis for long. Particularly we study eye movements associated with otoneurological patients. At the moment nystagmus eye movements are analysed particularly. Connected to these the function of semicircular canals (in inner ears) sensing one's balance is modelled computationally. Nowadays we also study biometric verification of individuals by means of saccade eye movements. The target is to verify  computer users or other subjects on the basis of saccades recorded with an eye movement (gaze tracker) videocamera. For long we have studied human balance signals (stabilograms) recorded with a force platform, on which a subject is standing. We have developed virtual reality stimulations for this purpose. These signals are used to aid in medical balance investigations and investigations of occupational health.

Document classification is a topic in which we develop computational methods to effectively classify cases of interesting topics from extensive collections of electronic documents by using machine learning methods, for example, self-organising maps.

A topic is probabilistic roadmap algorithms for robotics. We also study steganography, hiding security information (electronic labels or signatures) in images and data mining for demographic, economic and social data for exploring correlations and causes of crime at the (macroscopic) country level based on national and UN databases.

Ph.D. theses completed

Yrjö Auramo: Construction of an expert system to support otoneurological vertigo diagnosis, 1999 (Report A-1999-2, Department of Computer Science, University of Tampere)

Jorma Laurikkala: Knowledge discovery for female urinary incontinence expert system, 2001

Markku Siermala: Local prediction of secondary structures of proteins from viewpoints of rare structure, 2002

Kati Iltanen (née Viikki): Machine learning on otoneurological data: decision trees for vertigo diseases, 2002

Jouni Mykkänen: Delineation of brain structures from functional positron emission tomography images, 2003

Heikki Hyyrö: Practical methods for approximate string matching, 2003

Timo Tossavainen: Virtual reality and posturography applied to postural control research, 2006

Antti Järvelin: Applying machine learning methods to aphasic data, 2008

Tuomas Talvensaari: Comparable Corpora in Cross-Language Information Retrieval, 2008

Pekka-Henrik Niemenlehto: Detection of physiological events from biomedical signals originating from facial landmarks, 2009

Jyrki Rasku: Classification of the human swaying processes: A machine learning approach, 2009

Henry Joutsijoki: Variations on a theme: The classification of benthic macroinvertebrates, 2012

Youming Zhang: Biometric verification of a subject based on data mining of saccade eye movement signals, 2014.

Xingan Li: Application of data mining methods in the study of crime based on international data sources, 2014.

Mika Rantanen: Improving probabilistic roadmap methods for fast motion planning, 2014.

Jyri Saarikoski: On text document classification and retrieval using self-organising maps, 2014.

Yevhen Zolotavkin: New methods for digital image watermarking, 2015.

Awards and Recognitions

Timo Tossavainen: Master Thesis Award of the Pirkanmaa Computing Society (Pirkanmaan tietojenkäsittely-yhdistys), 2000

Heikki Hyyrö: Master Thesis Award of the Finnish Mathematician, Physicist and Computing Union (Suomen Matemaatikko-, Fyysikko- ja Tietojenkäsittelytieteilijäliitto SMF), 2001

Antti Järvelin: Master Thesis Award of the Pirkanmaa Computing Society (Pirkanmaan tietojenkäsittely-yhdistys), 2003

Antti Järvelin: The Nokia Research Center Award for the best paper by a young scientist, The 11th Finnish Artificial Intelligence Conference, The Finnish Science Center Heureka, Vantaa, September 1-3, 2004

Janne Lumijärvi: Master Thesis Award of the Finnish Mathematician, Physicist and Computing Union (Suomen Matemaatikko-, Fyysikko- ja Tietojenkäsittelytieteilijäliitto SMF), Finlandia Hall, Helsinki, November 25, 2004

Kati Iltanen: Award of the best teacher of 2005 in the Department of Computer Sciences, University of Tampere.

Martti Juhola, Heikki Aalto and Timo Hirvonen: On signal analysis of three-dimensional nystagmus, Proc. Medical Informatics in Europe 2009 (MIE2009), Sarajevo, Bosnia and Herzegovina, p. 846-850; The article was singled out for the best 10 % of over 300 articles of MIE2009.

In MLDM 2012 Henry Joutsijoki received a recognition for his active participation and innovative publications in International Conferences on Machine Learning and Data Mining (MLDM).

In IMMM 2012, the paper of Youming Zhang (speaker) and Martti Juhola was awarded as one of the best papers.

In MDA 2013, the paper of Youming Zhang (speaker) and Martti Juhola was the next best paper in the best paper competition.

Henry Joutsijoki was appointed  for the Finnish nominee for Cor Baayen Award 2015 by the Finnisch Society of Computer Science on the 30th April 2015.

The paper 'Signal analysis and classification methods for the calcium transient data of stem cell-derived cardiomyocytes, Comp. Biol. Med, 2015' of our research group (DARG) and that of Prof. Katriina Aalto-Setälä from BioMeditech (Univ. Tampere) was selected and featured by Global Medical Discovery as a brief presentation on the 5th October 2015. "Global Medical Discovery is highly selective, the invited articles are less than 0.1% of the whole published literature (that is 20 per week chosen by a team of advisers and experts)".


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