Tapio Pahikkala
Professor
aatapa@utu.fi +358 29 450 4323 +358 50 345 5824 Työhuone: 456D ORCID-tunniste: 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
- Towards practical federated learning and evaluation for medical prediction models (2025)
- International Journal of Medical Informatics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - A comparison of embedding aggregation strategies in drug-target interaction prediction (2024)
- BMC Bioinformatics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Benchmarking Evaluation Protocols for Classifiers Trained on Differentially Private Synthetic Data (2024)
- IEEE Access
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Does Differentially Private Synthetic Data Lead to Synthetic Discoveries? (2024)
- Methods of Information in Medicine
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Finnish perspective on using synthetic health data to protect privacy: the PRIVASA project (2024)
- Applied Computing and Intelligence
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Predicting pairwise interaction affinities with ℓ0-penalized least squares-a nonsmooth bi-objective optimization based approach∗ (2024)
- Optimization Methods and Software
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Targeted and Untargeted Amine Metabolite Quantitation in Single Cells with Isobaric Multiplexing (2024)
- Chemistry - A European Journal
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Budget-based classification of Parkinson's disease from resting state EEG (2023)
- IEEE Journal of Biomedical and Health Informatics
(A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä ) - Empirical evaluation of amplifying privacy by subsampling for GANs to create differentially private synthetic tabular data (2023)
- CEUR Workshop Proceedings
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa) - Evaluating Classifiers Trained on Differentially Private Synthetic Health Data (2023)
- Proceedings (IEEE International Symposium on Computer-Based Medical Systems)
(A4 Vertaisarvioitu artikkeli konferenssijulkaisussa)
