Antti Airola
D.Sc. (Tech.)
ajairo@utu.fi +358 29 450 4193 +358 50 517 8711 Vesilinnantie 5 Turku : 456H |
artificial intelligence; data analytics; machine learning; health technology
Antti Airola, is an Associate Professor (tenure track) of data science in the area of Health Technology at the University of Turku. He has co-authored over 100 peer-reviewed articles, won multiple international data science competitions, and received several research excellence awards such as the the HATUTUS award for the best PhD thesis in the area of pattern recognition in Finland (2010 - 2011) and IEEE Computational Intelligence Society Outstanding Transactions on Fuzzy Systems Paper award (2015). He is currently working as responsible leader in several EU and Research Council of Finland funded research projects.
As of 2025, he is acting as a deputy head of the department of computing.
Airola's main research areas are in the area of machine learning and data science, especially their applications in the health domain.
Airola is currently responsible for teaching the course Data Analysis and Knowledge Discovery, as well as thesis supervision work (BSc, MSc, PhD). He has developed materials for and taught in many courses in the area of data and computer science, is responsible for developing the curriculum for both national BSc and MSc Medical and health technology programmes, as well as the international MSc programme in Health technology, and directs the AI Academy that coordinates AI related teaching between the faculties.
- Learning Valued Relations from DataAll-paths graph kernel for protein-protein interaction extraction with evaluation of cross-corpus learning (2011)
- Advances in intelligent and soft computing
- On Learning and Cross-Validation with Decomposed Nystrom Approximation of Kernel Matrix (2011)
- Neural Processing Letters
- Speedy Local Search for Semi-Supervised Regularized Least-Squares (2011)
- Lecture Notes in Computer ScienceFrontiers in Artificial Intelligence and Applications
- Training linear ranking SVMs in linearithmic time using red-black trees (2011)
- Pattern Recognition Letters
- A comparison of {AUC} estimators in small-sample studies (2010)
- Journal of Machine Learning Research
- A comparison of AUC estimators in small-sample studies (2010)
- JMLR workshop and conference proceedingsFrontiers in Artificial Intelligence and Applications
- Applying permutation tests for assessing the statistical significance of wrapper based feature selection (2010) Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA 2010) Airola A, Pahikkala T, Boberg J, Salakoski T
- Conditional Ranking on Relational Data (2010)
- Lecture Notes in Computer Science
- Feature Selection for Regularized Least-Squares: New Computational Short-Cuts and Fast Algorithmic Implementations (2010) Proceedings of the Twentieth IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010) Pahikkala T, Airola A, Salakoski T
- Greedy {RankRLS}: a Linear Time Algorithm for Learning Sparse Ranking Models (2010) SIGIR 2010 Workshop on Feature Generation and Selection for Information Retrieval Pahikkala T, Airola A, Naula P, Salakoski T
- Large scale training methods for linear {RankRLS} (2010) Proceedings of the {ECML/PKDD} 2010 Workshop on Preference Learning {(PL-10)} Airola A, Pahikkala T, Salakoski T
- Proceedings of the 14th Finnish Artificial Intelligence Conference, STeP 2010 (2010) Pahikkala T, Väyrynen J, Kortela J, Airola A (eds. )
- Speeding up Greedy Forward Selection for Regularized Least-Squares (2010) Proceedings of The Ninth International Conference on Machine Learning and Applications (ICMLA 2010) Pahikkala T, Airola A, Salakoski T
- An efficient algorithm for learning to rank from preference graphs (2009)
- Machine Learning
- Extracting Complex Biological Events with Rich Graph-Based Feature Sets (2009) Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task Björne J, Heimonen J, Ginter F, Airola A, Pahikkala T, Salakoski T
- A Graph Kernel for Protein-Protein Interaction Extraction (2008) Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing (BioNLP 2008) Airola A, Pyysalo S, Björne J, Pahikkala T, Ginter F, Salakoski T
- 2008
- BMC Bioinformatics
- A Sparse Regularized Least-Squares Preference Learning Algorithm (2008)
- Comparative analysis of five protein-protein interaction corpora (2008)
- BMC Bioinformatics
- Efficient AUC Maximization with Regularized Least-Squares (2008)
