PhD Student. Giacomo supports proof-of-concept studies with Italian. His research is on deep learning language models for morphological disambiguation in multiple languages.
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PhD student. Jue works on scalability of the back end and the front end, and educational data science — to analyze and model data collected from proof-of-concept studies with real learners. His research focuses on modeling learner proficiency and novel approaches to language modeling deep-learning neural nets.
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PhD Student. Anisia works on all aspects of user studies involving Russian. Her research is on building deep-learning language models for detection of grammatical errors. Revita needs such models to identify "alternative-correct" answers — important situations in learning, where more than one answer is possible for an exercise.
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MS student. Ilmari works with the TOSKA Group, under the direction of Dr Matti Luukkainen, to bring the latest developments in front-end technologies into Revita — to assure the best possible User Experience for the learners and teachers. He is working on his MS degree in Language Technology.
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PhD Student. Duc works on Bayesian networks and deep learning modeling of the learners' proficiency and progress, which is essential for personalization in the Revita Project — learner competency must be modeled accurately to provide the most suitable exercises and feedback.
Duc's MS Thesis (2020) was on "Modeling knowledge states in language learning."
Project lead. Roman Yangarber is Associate Professor at the Department of Digital Humanities, University of Helsinki (UH). He holds the Chair in Linguistic Inequalities and Translation Technologies at INEQ: The Helsinki Inequality Initiative. The Research Group he is leading — the Language Learning Lab — works on a variety of topics: studying how language works, and how computers can better understand language. His recent focus is on AI support for language learning. His earlier research themes include analysis of news media, and modeling language evolution and relationships among languages.
Work on language learning has resulted in a system currently in use by learners and teachers at several universities. The research focuses on support for learning of smaller, endangered languages, as well as for "majority" languages.
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Publications (Google Scholar)
Prior members of the Research Group: