Giacomo Furlan — PhD Student. Giacomo supports proof-of-concept studies with Italian. His research is on deep learning language models for morphological disambiguation in multiple languages.Giacomo Furlan's People finder profile Giacomo Furlan's Research Portal profile
Jue Hou — PhD student. Jue's research focuses on modeling learner proficiency and novel approaches to language modeling with deep-learning neural nets. He also works on scalability of Revita's back end, and on educational data science — to analyze and model the data collected from proof-of-concept studies with real learners. Jue Hou's People finder profileJue Hou's Research portal profile
Silja Huttunen — PhD (University of Helsinki). Organizing user studies and experiments with teachers and learners.
Anisia Katinskaia — PhD Student. Anisia works on all aspects of user studies involving Russian and Finnish. Her research is on deep-learning language models for detection of grammatical errors. Revita needs to identify "alternative-correct" answers — important settings in learning, where there is more than one correct answer.Anisia Katinskaia's People finder profileAnisia Katinskaia's Research Portal profile
Ilmari Kylliäinen — MS student. Ilmari works with the TOSKA Group, under the lead of Dr Matti Luukkainen. Ilmari and TOSKA bring the latest in front-end technologies and software engineering into Revita — to create a friendly user experience (UX) for learners and teachers. He has a MS degree in Language Technology.
Ilmari Kylliäinen's People finder profile
Ilmari Kylliäinen's Research portal profile
Anh-Duc Vu — PhD Student. Duc works on Bayesian networks and deep learning modeling of the learner proficiency and progress, which is essential for the personalization aspect in the Revita Project — learner competency must be modeled as accurately as possible to provide suitable exercises and feedback.
Duc's MS Thesis (2020) on "Modeling knowledge states in language learning."
Project lead. 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. His research group — the Language Learning Lab — works on a variety of topics: studying how language works, and how computers can better understand language. His earlier research themes include analysis of news media, and modeling language evolution. Recent focus is on AI support for language learning. This has resulted in Revita, 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.Roman Yangarber's People finder profilePublications (Google Scholar)
Some of our main collaborators: local, at the University of Helsinki (UH), and international.
Remote Studies — current work with groups of learners at other universities, collecting feedback from them and researching their progress.
All of our colleagues and collaborators typically work on multiple problems and aspects of the Project at the same time, and contribute to many areas. We list here some of them here: