Juho Heimonen profile picture
University Teacher, Health Technology
Research on applications of text mining, machine learning and knowledge representation in various domains (such as biomedicine and healthcare). A member of the IKITIK consortium.


Vesilinnantie 5

Areas of expertise

text mining
machine learning
knowledge representation


Juho Heimonen received his PhD degree in Bioinformatics from the University of Turku in 2019 and is currently working as a university teacher at the Department of Computing. His main research interest is the use of text mining and machine learning to solve domain-specific problems. Heimonen has studied university pedagogy and has acquired over 10 years of teaching experience. He has also worked in several research projects in connection to the themes of his PhD dissertation (Knowledge Representation and Text Mining in Biomedical, Healthcare, and Political Domains).


Heimonen is interested in teaching data analytics, programming and bioinformatics to both major and minor subject students. He is excited about MOOCs and other possibilities to organise teaching online in a time and location independent manner.

Heimonen is currently responsible for Bioinformatics Programming Course (5 ECTS) and Introduction to Statistical Analysis (5 ECTS) at the Department of Computing. He also lectures in Applications of Data Analysis (5 ECTS) and Digitalisaatio sosiaali- ja terveydenhuollon palveluissa (3 ECTS), supervises bachelor's thesis students and organises thesis seminars. His previous teaching responsibilities include Supplementary mathematics (5 ECTS), Introduction to Statistics (4 ECTS), Bioinformatiikan perusteet (5 ECTS), and Mathematics for Bioinformatics (4 ECTS). He has also been a guest lecturer in courses at other departments.


Heimonen's current research interests include the use of text mining, machine learning and knowledge representation in various domains. He is particularly interested in how text mining and knowledge representations can be used to improve healthcare services and how machine learning methods can be adapted to domain-specific problems.

Heimonen is a member of the IKITIK research consortium.


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