Research output per year
Research output per year
Personal profile
Artistic and research interests
Wilhelmiina Hämäläinen (PhD) is a senior university lecturer at the Department of Computer Science, Aalto University. In the past, she has worked in various research and teaching positions in the areas of computer science, biology, biomedicine and environmental science in Finnish universities. Her main research area is data mining and machine learning, including both basic research, especially on pattern discovery algorithms and statistical significance testing methods in computational data analysis, and applied research on solving challenging real world data analysis problems on biological, medical, bionformatics and educational data.
Education/Academic qualification
Doctoral degree, Natural Sciences, University of Helsinki
Award Date: 19 Oct 2010
External positions
Research manager of Bioinformatics center, University of Eastern Finland
1 Aug 2018 → 30 Nov 2019
Keywords
- data mining, machine learning, algorithms, data science
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Metabolomics of Synovial Fluid and Infrapatellar Fat Pad in Patients with Osteoarthritis or Rheumatoid Arthritis
Nieminen, P., Hämäläinen, W., Savinainen, J., Lehtonen, M., Lehtiniemi, S., Rinta-Paavola, J., Lehenkari, P., Kääriäinen, T., Joukainen, A., Kröger, H., Paakkonen, T. & Mustonen, A. M., Jun 2022, In: Inflammation. 45, 3, p. 1101-1117 17 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile6 Citations (Scopus)11 Downloads (Pure) -
A tutorial on statistically sound pattern discovery
Hämäläinen, W. & Webb, G. I., 2019, In: Data Mining and Knowledge Discovery. 33, 2, p. 325–377 53 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile24 Citations (Scopus)79 Downloads (Pure) -
Clustering students' open-ended questionnaire answers
Hämäläinen, W., Joy, M., Berger, F. & Huttunen, S., 2018, arXiv.org, 13 p.Research output: Working paper › Scientific
Open AccessFile10 Downloads (Pure) -
Evaluation of the confusion matrix method in the validation of an automated system for measuring feeding behaviour of cattle
Ruuska, S., Hämäläinen, W., Kajava, S., Mughal, M., Matilainen, P. & Mononen, J., 1 Mar 2018, In: BEHAVIOURAL PROCESSES. 148, p. 56-62 7 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access87 Citations (Scopus) -
Specious rules: An efficient and effective unifying method for removing misleading and uninformative patterns in association rule mining
Hämäläinen, W. & Webb, G. I., 2017, Proceedings of the 17th SIAM International Conference on Data Mining, SDM 2017. p. 309-317 9 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
File5 Citations (Scopus)28 Downloads (Pure)
Projects
- 1 Finished
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Efficient search algorithms for genuine dependency rules in large-dimensional data
01/05/2016 → 28/02/2018
Project: Academy of Finland: Other research funding
Activities
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Tutorial on Yule-Simpson's paradox and other specious associations
Wilhelmiina Hämäläinen (Speaker)
8 Mar 2018Activity: Talk or presentation types › Academic keynote or plenary lecture
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Monash University
Wilhelmiina Hämäläinen (Visiting researcher)
17 Nov 2017 → 3 Dec 2017Activity: Visiting an external institution types › Visiting an external academic institution
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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases
Wilhelmiina Hämäläinen (Member)
19 Sep 2016 → 23 Sep 2016Activity: Participating in or organising an event types › Membership of a scientific or program committee of a conference or seminar
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Workshop on Statistically Sound Data Mining
Wilhelmiina Hämäläinen (Member)
19 Sep 2016Activity: Participating in or organising an event types › Organization of a workshop, panel, session, tutorial or event
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Inria Lille Nord Europe
Wilhelmiina Hämäläinen (Visiting researcher)
7 Nov 2016 → 18 Nov 2016Activity: Visiting an external institution types › Visiting an external academic institution