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 80 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.
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 TKO_3103 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 Data (2012)
- Advances in intelligent and soft computing
- Machine Learning and Performance Estimation Methods for Ranking Problems (2012) Proceedings of the Federated Computer Science Event 2012 Airola A
- Parallelized Online Regularized Least-Squares for Adaptive Embedded Systems (2012)
- International Journal of Embedded and Real-Time Communication Systems
- Sparse Quasi-{Newton} Optimization for Semi-Supervised Support Vector Machines (2012) Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods (ICPRAM) Gieseke F, Airola A, Pahikkala T, Kramer O
- Unsupervised Multi-Class Regularized Least-Squares Classification (2012)
- IEEE International Conference on Data Mining
- Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations (2012)
- Algorithms for Molecular Biology
- An experimental comparison of cross-validation techniques for estimating the area under the ROC curve (2011)
- Computational Statistics and Data Analysis
- An Improved Training Algorithm for the Linear Ranking Support Vector Machine (2011)
- Lecture Notes in Computer Science
- A parallel online regularized least-squares machine learning algorithm for future multi-core processors (2011) Proceedings of the 1st International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS 2011) Pahikkala T, Airola A, Xu TC, Liljeberg P, Tenhunen H, Salakoski T
- Drug-drug Interaction Extraction from Biomedical Texts with {SVM} and {RLS} Classifiers (2011) Proceedings of the SEPLN 2011 Workshop on First Challenge Task on Drug-Drug Interaction Extraction (DDIExtraction 2011) Björne J, Airola A, Pahikkala T, Salakoski T
- Drug-Drug Interaction Extraction with RLS and SVM Classifiers (2011)
- CEUR Workshop Proceedings
- EXTRACTING CONTEXTUALIZED COMPLEX BIOLOGICAL EVENTS WITH RICH GRAPH-BASED FEATURE SETS (2011)
- Computational Intelligence
- Fast and Parallelized Greedy Forward Selection of Genetic Variants in Genome-Wide Association Studies (2011) IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS 2011) Okser S, Pahikkala T, Airola A, Aittokallio T, Salakoski T
- Greedy Regularized Least-Squares for Multi-Task Learning (2011) 11th IEEE International Conference on Data Mining Workshops (ICDMW'11) Naula P, Pahikkala T, Airola A, Salakoski T
- Learning Multi-Label Predictors under Sparsity Budget (2011)
- Frontiers in Artificial Intelligence and Applications
- Learning Valued Relations from Data (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 Science
- 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
