Areas of expertise
I am a researcher at the Department of Computing, University of Turku. My research is in the area of natural language processing. I belong to the TurkuNLP (turkunlp.org) research group. In addition to my primary role at the University of Turku, I am also a part-time AI Scientist with Silo.ai and a technical architect with Lingsoft Oy
I was born in 1978 in Ostrava, Czech Republic (Czechoslovakia back then). In 2001, I got a M.Sc. (tech) in computer science at the computer science department of VSB - Technical University Ostrava. My major subject was artificial intelligence. I gained a PhD in computer science in 2007. The title of my thesis is Towards Information Extraction in the Biomedical Domain: Methods and Resources.
As of 2018, I am an associate professor of language technology and as of 2021 the deputy director of the Department of Computing.
I have been actively teaching since early on during my PhD studies. I independently prepared my first advanced level NLP course in 2004, and since ca. 2008 I have been teaching at least one course every year, substantially more during my bioinformatics lecturer appointment. While a lecturer in the bioinformatics MSc degree programme, I was lecturing international students in two cities. In 2016, I was tasked with developing and coordinating the introduction of a new 20 ECTS study module on natural language processing. This module is, with modifications, still in use and shared between the departments of Languages and Computing, both in terms of teaching and in terms of students. In 2019-2020 and 2020-2021 I was also co-lecturing, upon invitation, two courses in natural language processing in the Arcada University of Applied Sciences in Helsinki.
My primary field of research is language technology / natural language processing. In my post-PhD career, I have focused on the development of NLP tools and resources primarily for Finnish, but later also numerous other languages via the Universal Dependencies project. My work is heavy on resource development, both in terms of data and machine learning pipelines. Open science and resources play an important role in my research, much of which is carried out in the open on GitHub and as a rule, all resources are openly available for unrestricted use. I work collaboratively, especially with my younger colleagues, rather than striving for deeper, primary author inquiries.