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.
Current research projects:Academy of Finland: "AI technologies for interaction prediction in biomedicine", Academy of Finland: "Machine Learning for Systems Pharmacology", Business Finland: "Privasa".
The course I am currently responsible of: ``Evaluation of Machine Learning Methods'', consists of a series of practical cases studies that are each presented by different assistant teachers that act as clients of data scientists. The clients then introduce the problem the the data scientist should solve for them and the details of the data. The students' job is then implement the data analysis pipeline, train a predictive model, do a proper experimental design and carry out carry out statistical estimation of the prediction performance for each client. To achieve this, they study the accompanying course material that is currently in the form of both video lectures and reading material. All the clients' cases correspond to real cases from which our team has written research articles in the past. For example, the case concerning metal ion concentration prediction from drinking water is based on our research cooperation with the chemistry deparment of the University of Turku (Pihlasalo et al. 2016), the case on water permeability prediction in forestry for route planning of forest harvesters and the use of newly developed spatial cross-validation for estimating the prediction performance in that context is based on our cooperation with the Natural Resources Center of Finland (Pohjankukka et al. 2017), and the case concerning drug-target interaction prediction is based on our research cooperation with Institute for Molecular Medicine Finland (Pahikkala et al. 2015), to highlight a few. We have also had plans to involve cases from private companies in the future, such that would correspond to real commercial cases.
- Regularized Machine Learning in the Genetic Prediction of Complex Traits (2014)
- PLoS Genetics
(A2 Refereed review article in a scientific journal ) - A Machine Learning Approach Towards Early Detection of Frequent Health Care Users (2013) Proceedings of the 4th International Louhi Workshop on Health Document Text Mining and Information Analysis (Louhi 2013) Antti Airola, Tapio Pahikkala, Heljä Lundgrén-Laine, Anne Santalahti, Päivi Rautava, Sanna Salanterä, Tapio Salakoski
(A4 Refereed article in a conference publication ) - Analyzing the Japanese Toxicogenomics Project Dataset with SVM and RLS Classifiers (2013) 13th Annual International Conference on Critical Assessment of Massive Data Analysis (CAMDA 2013) Björne J, Airola A, Pahikkala T, Salakoski T
(Other publication) - Comparison of chlorophyll fluorescence curves and texture analysis for automatic plant identification (2013)
- Precision Agriculture
(A1 Refereed original research article in a scientific journal) - Efficient regularized least-squares algorithms for conditional ranking on relational data (2013)
- Machine Learning
(A1 Refereed original research article in a scientific journal) - Energy Aware Consolidation Algorithm based on K-nearest Neighbor Regression for Cloud Data Centers (2013) 6th IEEE/ACM International Conference on Utility and Cloud Computing Fahimeh Farahnakian, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila
(A4 Refereed article in a conference publication ) - Genetic variants and their interactions in disease risk prediction - machine learning and network perspectives (2013)
- BioData Mining
(A2 Refereed review article in a scientific journal ) - Kernel-Based Learning of Conditional Utility Functions (2013) European Conference on Operational Research (EURO 2013) Pahikkala T
(Other publication) - Optimized Multicore Architectures for Data Parallel Fast Fourier Transform (2013) Proceedings of the 14th International Conference on Computer Systems and Technologies (CompSysTech '13) Thomas Canhao Xu, Tapio Pahikkala, Pasi Liljeberg, Juha Plosila, Hannu Tenhunen
(A4 Refereed article in a conference publication ) - Pairwise kernel methods for predicting molecular interactions (2013) BeNeLux Bioinformatics Conference Stock M, Pahikkala T, Airola A, De Baets B, Waegeman W
(Other publication) - Parallel Feature Selection for Regularized Least-Squares (2013)
- Lecture Notes in Computer Science
(A4 Refereed article in a conference publication ) - Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification (2013)
- JMLR workshop and conference proceedings
(A4 Refereed article in a conference publication ) - A Kernel-Based Framework for Learning Graded Relations From Data (2012)
- IEEE Transactions on Fuzzy Systems
(A1 Refereed original research article in a scientific journal) - Conditional Ranking Algorithms for Efficient Object Retrieval and Object Querying on Relational Data (2012) Proceedings of the 12th Dutch-Belgian Information Retrieval Workshop (DIR 2012) Waegeman W, Stock M, De Baets B, Pahikkala T, Airola A, Salakoski T
(A4 Refereed article in a conference publication ) - Efficient cross-validation for kernelized least-squares regression with sparse basis expansions (2012)
- Machine Learning
(A1 Refereed original research article in a scientific journal) - Efficient recurrent local search strategies for semi- and unsupervised regularized least-squares classification (2012)
- Evolutionary Intelligence
(A1 Refereed original research article in a scientific journal) - Implementation and Analysis of Block Dense Matrix Decomposition on Network-on-Chips (2012) 2012 IEEE 14th International Conference on High Performance Computing and Communication & 2012 IEEE 9th International Conference on Embedded Software and Systems Xu TC, Pahikkala T, Airola A, Liljeberg P, Plosila J, Salakoski T, Tenhunen H
(A4 Refereed article in a conference publication ) - Learning Monadic and Dyadic Relations: Three Case Studies in Systems Biology (2012) ECML/PKDD 2012 Workshop on Learning and Discovery in Symbolic Systems Biology Stock M, Pahikkala T, Airola A, Salakoski T, De Baets B, Waegeman W
(A4 Refereed article in a conference publication ) - Learning Preference Relations with Kronecker Kernels: Some Theoretical and Algorithmic results (2012) Pahikkala T
(Other publication) - Learning Valued Relations from Data (2012)
- Advances in intelligent and soft computing
(A4 Refereed article in a conference publication )
