Tapio Pahikkala
Professor
aatapa@utu.fi +358 29 450 4323 +358 50 345 5824 Office: 456D ORCID identifier: https://orcid.org/0000-0003-4183-2455 |
Machine learning, Data science, Artificial intelligence
Machine learning, Data science, Artificial intelligence
Tapio Pahikkala is a professor of computer science in the University of Turku, Finland, from which he also received his doctoral degree in 2008. He has authored more than 150 peer-reviewed scientific articles and participated in the winning teams of several international scientific competitions/challenges. He has led many research projects, supervised more than ten doctoral theses, held several positions of trust in academia and served in the program committees of numerous international conferences. His current research interests include theory and algorithmics of machine learning, data analysis, and artificial intelligence, as well as their applications on various different fields.
Theory and algorithmics of machine learning, data science and artificial intelligence as well as their practical applications in various different fields. Estimation of prediction performance with resampling methods, theory of resampling and cross-validation.
TKO_7092 Evaluation of Machine Learning Methods
- Bayesian Inference for Predicting the Monetization Percentage in Free-to-Play Games (2022)
- IEEE Transactions on Games
(A1 Refereed original research article in a scientific journal) - Detection of Prostate Cancer Using Biparametric Prostate MRI, Radiomics, and Kallikreins: A Retrospective Multicenter Study of Men With a Clinical Suspicion of Prostate Cancer (2022)
- Journal of Magnetic Resonance Imaging
(A1 Refereed original research article in a scientific journal) - Generalized vec trick for fast learning of pairwise kernel models (2022)
- Machine Learning
(A1 Refereed original research article in a scientific journal) - Quicksort leave-pair-out cross-validation for ROC curve analysis (2022)
- Computational Statistics
(A1 Refereed original research article in a scientific journal) - Adaptive risk prediction system with incremental and transfer learning (2021)
- Computers in Biology and Medicine
(A1 Refereed original research article in a scientific journal) - A Resource Management Model for Distributed Multi-Task Applications in Fog Computing Networks (2021)
- IEEE Access
(A1 Refereed original research article in a scientific journal) - Effect of oat β-glucan of different molecular weights on fecal bile acids, urine metabolites and pressure in the digestive tract – A human cross over trial (2021)
- Food Chemistry
(A1 Refereed original research article in a scientific journal) - Modeling drug combination effects via latent tensor reconstruction (2021)
- Bioinformatics
(A1 Refereed original research article in a scientific journal) - Negative Predictive Value of Biparametric Prostate Magnetic Resonance Imaging in Excluding Significant Prostate Cancer: A Pooled Data Analysis Based on Clinical Data from Four Prospective, Registered Studies (2021)
- European Urology Focus
(A1 Refereed original research article in a scientific journal) - A general-purpose toolbox for efficient Kronecker-based learning (2020) JuliaCon Proceedings Michiel Stock, Tapio Pahikkala, Antti Airola, Bernard De Baets
(Other publication)



