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
- Algebraic shortcuts for leave-one-out cross-validation in supervised network inference (2020)
- Briefings in Bioinformatics
(A1 Refereed original research article in a scientific journal) - Cost-effective survival prediction for patients with advanced prostate cancer using clinical trial and real-world hospital registry datasets (2020)
- International Journal of Medical Informatics
(A1 Refereed original research article in a scientific journal) - Developing a pain intensity prediction model using facial expression: A feasibility study with electromyography (2020)
- PLoS ONE
(A1 Refereed original research article in a scientific journal) - (2020)
- Computers in Biology and Medicine
- Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects2020
- Nature Communications
(A1 Refereed original research article in a scientific journal) - Measuring Player Retention and Monetization Using the Mean Cumulative Function (2020)
- IEEE Transactions on Games
(A1 Refereed original research article in a scientific journal) - (2020)
- Journal of the Acoustical Society of America
(A1 Refereed original research article in a scientific journal) - Predicting profitability of peer-to-peer loans with recovery models for censored data (2020)
- International Conference on Intelligent Decision Technologies
(A4 Refereed article in a conference publication ) - (2020)
- Lecture Notes in Business Information ProcessingScientific Reports
(A4 Refereed article in a conference publication ) - Prediction of prostate cancer aggressiveness using 18 F-Fluciclovine (FACBC) PET and multisequence multiparametric MRI (2020)
(A1 Refereed original research article in a scientific journal)



