Antti Airola profile picture
Assistant Professor, Health Technology
D.Sc. (Tech.)


+358 29 450 4193
+358 50 517 8711
Vesilinnantie 5

Areas of expertise

artificial intelligence
data analytics
machine learning
health technology


Antti Airola, is an Assistant 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 Academy of Finland and Business 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. He currently leads two Academy of Finland funded projects related to the area of biomedical interaction prediction, and the Business Finland PRIVASA project on privacy-preserving AI for health data.


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.


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O-CDIO: Emphasizing Design Thinking in CDIO Engineering Cycle (2016)

International Journal of Engineering Education
Ville Taajamaa, Mona Eskandari, Barbara Karanian, Antti Airola, Tapio Pahikkala, Tapio Salakoski
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

RLScore: Regularized Least-Squares Learners (2016)

Journal of Machine Learning Research
Tapio Pahikkala, Antti Airola
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Toward more realistic drug-target interaction predictions (2015)

Briefings in Bioinformatics
Tapio Pahikkala, Antti Airola, Sami Pietilä, Sushil Shakyawar, Agnieszka Szwajda, Jing Tang, Tero Aittokallio
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Predicting patient acuity from electronic patient records (2014)

Journal of Biomedical Informatics
Elina Kontio, Antti Airola, Tapio Pahikkala, Heljä Lundgren-Laine, Kristiina Junttila, Heikki Korvenranta, Tapio Salakoski, Sanna Salanterä
(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))