CLAIRE | UiT

Olov Engwall is a Professor in Speech Communication at KTH Royal Institute of Technology, specializing in the intersection of speech technology, artificial intelligence, and educational science. His research focuses on developing interactive digital agents and social robots to support learning, particularly second language (L2) acquisition, pronunciation training, and literacy. His early projects utilised 3D animated virtual tutors to visualise articulatory movements — such as tongue and lip positioning — to give learners direct feedback on internal vocal mechanics. He has further applied natural language processing and speech recognition to automated Swedish L2 instruction. Building on virtual agents, Engwall’s work expanded into Robot-Assisted Language Learning (RALL), using embodied the social robot Furhat to facilitate collaborative and task-based learning for students from diverse backgrounds. His recent projects apply interactive AI and social robots to the study of how learners interact with LLM-driven anthropomorphic robots, specifically examining student trust, critical thinking, and responses to model hallucinations. In CLAIRE, Engwall will explore both social robots and animated agents acting as virtual patients to practice L2 Swedish in the medical setting for newly-arrived doctors, nurses and dentists.

Julia Prentice

Professor of Multilingualism

Julia Prentice

Professor of Multilingualism

julia.prentice@svenska.gu.se

University of Gothenburg, Department of Swedish, Multilingualism, Language Technology

https://www.gu.se/en/about/find-staff/juliagrosse

Julia Prentice is professor of multilingualism and has worked on conventionalized language in Swedish as a second language since her doctoral project. She also was a member of the research team that developed the Swedish Constructicon (SweCcn). She has more than ten years of experience with usage-based, constructionist research regarding the acquisition of Swedish lexico-grammar and has been actively involved in both theory development and applied research within the international research community of usage-based construction grammar.

Hanne Løje

Associate Professor

Hanne Løje

Associate Professor

halo@dtu.dk

Technical University of Denmark (DTU)

https://www.dtu.dk/person/hanne-loeje?id=19873&entity=profile

Hanne Løje is an Associated Professor and Head of Section for the Section Engineering Education Research at DTU Engineering Technology and Didactics. Furthermore, she is also Head of Studies for the Bachelor of Engineering program in Global Business Engineering at Technical University of Denmark (DTU). Her current research focus is on interdisciplinary, feedback, challenge-based learning and pedagogical development. She is a chair of the management group for the Danish Network for Engineering Education (IUPN). Hanne Løje has for several years worked with didactics and pedagogy and has presented results at national and international conferences within Engineering Education Research and been project leader for several projects within this field. Hanne Løje has been teaching university students for more than 18 years and is responsible for development and running a number of new courses at DTU. Through her academic career, she has worked systematically with development of teaching, teaching materials and teaching environment to improve the students learning and she has published several papers in this context and presented at several international conferences. She is also an experienced project leader and is present project leader for two projects with focus on improvement of quality in higher education. Since 2021, she has been project manager for a Scholarship of Teaching & Learning program at DTU Engineering Technology, where university teachers work systematically with development of their teaching as well as ensure the quality of the teaching.

Björn Lundquist

Professor

Lundquist, Björn

Professor

+4777646571

bjorn.lundquist@uit.no

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Taras Andrushko

IT engineer

Taras Andrushko

IT engineer

taand8919@uit.no

UiT The Arctic University of Norway

https://www.linkedin.com/in/taras-andrushko-105872228/

Taras Andrushko is an accomplished AI Engineer with expertise in Norwegian Large Language Models (LLMs) and automatic speech recognition (ASR). Holding a Master’s degree in Language Technology from the University of Oslo, he played a key role in developing the preliminary interface for the Norwegian Constructicon. With extensive hands-on experience in speech processing, text-to-speech (TTS), and ASR research, Taras excels in designing and implementing end-to-end machine learning pipelines — from data preprocessing and model training to evaluation and deployment. His technical proficiency spans cutting-edge tools and frameworks, including PyTorch, Hugging Face, LoRA fine-tuning, transformers, GANs, diffusion models, and speech tokenizers. In addition, he is adept at deploying models in production environments, leveraging technologies such as Docker, Kubernetes, and ONNX/TorchScript. Driven by a passion for innovation, Taras is dedicated to creating natural, expressive speech synthesis and advancing voice AI to power global applications.

Lei You

Assistant Professor in Applied Mathematics

Lei You

Assistant Professor in Applied Mathematics

leiyo@dtu.dk

Technical University of Denmark (DTU), Department of Engineering Technology and Didactics

https://www.dtu.dk/english/person/lei-you?id=197929&entity=profile

Lei You received my Ph.D. in Computer Science (specialized in Mathematical Optimization) from the Department of Information Technology at Uppsala University in 2019. He is the winner of the Doctoral Dissertation Award for Operations Research in Telecommunications and Network Analytics awarded by INFORMS in 2020. He had been a visiting data scientist in The Boston Consulting Group (BCG) Gamma in 2019. He had been working as a data scientist in Bolt and Wolt (Doordash) in the domain of on-demand logistics optimization. His research develops mathematical optimization frameworks for trustworthy AI, treating AI as a coupled system and producing metrics, algorithms, and deployable systems for reliable evaluation and transparent governance. His work focuses on three thrusts in AI ecosystem auditing, epistemic communication theory, and faithful AI explanations.