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Kukka-Maaria PolsoView profile

Researcher

• Educational Sciences
• Psychology
• Digital Learning
• +3 more

Kukka-Maaria Polso is a doctoral researcher and grant-funded researcher at the Department of Education, University of Helsinki. She is affiliated with the Doctoral Programme in Cognition, Learning, Instruction and Communication, focusing on educational sciences and psychology. Her work bridges learning theory with technological applications in education. University of Helsinki, Faculty of Education Doctoral Programme in Cognition, Learning, Instruction and Communication Her research centers on academic motivation, digital learning (MOOCs), and how motivational dynamics influence educational choices. She employs latent profile and transition analyses to study cross-domain motivational patterns in adolescents. Recent publications analyze: Motivational stability and educational transitions in Finnish students Digitalization’s impact on learning environments Workplace support mechanisms in MOOCs Goal orientation in programming education She received the HYMY Prize (2022) for her contributions to educational research and actively participates in conferences like OPPIVA, ICM, and ESELS, presenting interdisciplinary findings at the intersection of education and technology.

Peter SarlinView profile

Professor

• Artificial Intelligence
• Machine Learning
• Computer Science
• +1 more

Peter Sarlin is a Professor of Practice at Åbo Akademi University and Aalto University, specializing in machine learning and artificial intelligence. He holds a PhD in information systems science from Åbo Akademi University. Sarlin is the co-founder and CEO of Silo AI, a leading European private AI lab, which was acquired by AMD in a landmark $665 million deal. His recent substantial donation established 13 new AI-focused professorships across Finnish universities and supports the ELLIS Institute, strengthening Finland's AI ecosystem. Education: PhD in Information Systems Science, Åbo Akademi University His research focuses on advancing AI technologies and their applications in interdisciplinary fields. Sarlin’s work bridges academic research with industrial innovation, emphasizing Finland’s global competitiveness in AI. He co-founded the Foundation PS to further AI research and talent development through professorships and the PS Fellow network. Notable contributions include fostering collaboration between academia and industry, particularly through Silo AI’s advancements in AI systems. His donation underscores a commitment to building sustainable AI expertise and infrastructure in Europe.

• Quantum Condensed Matter Theory
• Topological Quantum Matter
• Quantum Entanglement
• +3 more

Teemu Ojanen is a Professor of computational physics at Tampere University, appointed in October 2021. He leads the Theory of Quantum Matter research group, focusing on quantum condensed matter theory, topological phenomena in quantum matter, and quantum entanglement. His work explores the fundamental mechanisms of quantum materials and their potential applications in quantum computing and energy-efficient electronics. He holds a Doctor of Science in Technology from Aalto University, with postdoctoral experience at Harvard University and Freie Universität Berlin. His research group includes four researchers, two doctoral candidates, and master's students. Key collaborations include the Department of Physics at Aalto University, supported by the Academy of Finland and Helsinki Institute of Physics. Research interests span quantum materials, entanglement dynamics, and theoretical frameworks for topological phases. He emphasizes the importance of basic research for breakthroughs in quantum technologies, such as quantum computers and energy-efficient devices.

• Information Retrieval
• Augmented Reality
• User Behavior
• +5 more

Giulio Jacucci serves as a Visitor (Faculty) at the Department of Computer Science, University of Helsinki, with additional affiliations to the Myllymäki Petri group and Helsinki Institute for Information Technology (HIIT). His academic foundation includes a Doctor of Philosophy from the University of Oulu, awarded on December 22, 2004. His research interests span multiple domains within human-computer interaction, with particular expertise in Information Retrieval (100%), Augmented Reality (57%), User Behavior (57%), Points of Interest (51%), and Mobile Devices (47%). His work also extends to Interactive Visualization, Information Discovery, and Multimedia Systems, reflecting a strong interdisciplinary approach to computer science. Analysis of his recent publications reveals a clear trajectory toward more complex human-AI interaction systems, with increasing focus on virtual environments, large language model integration, and health informatics applications. His 2024-2025 work demonstrates sophisticated approaches to understanding user behavior in virtual spaces while maintaining strong methodological rigor in empirical studies. Dr. Jacucci has hosted academic visitors in 2007, 2008, and 2009, and has supervised at least three theses as indicated by institutional records. His research activity remains robust with 163 total publications and ongoing output through 2025. His work contributes to UN Sustainable Development Goals related to education and technological advancement. The research network shows significant collaboration across international boundaries, with particular strength in European research partnerships.

Md. Ziaul HoqueView profile

Lecturer

• Medical Image Analysis
• Artificial Intelligence
• Machine Learning
• +5 more

Md. Ziaul Hoque holds the position of University Teacher at the Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland, and is affiliated with the Center for Machine Vision and Signal Analysis (CMVS). He is actively engaged in postdoctoral research under Prof. Tapio Seppänen, focusing on AI-driven solutions for clinical diagnostics and therapeutics. Currently, he supervises programming exercises for four courses and oversees doctoral and master's thesis projects. His research collaborations include international visits at the University of Florida (USA), University of Alberta (Canada), and University at Buffalo (USA). He has received multiple grants from prestigious research foundations, supporting his work in medical image analysis, AI, and IoT systems. His expertise bridges advanced technologies with healthcare applications, particularly in computer vision and biomedical engineering. Teaching responsibilities include courses such as Biosignal Processing II, Biomedical Engineering Project, and Machine Learning. Research affiliations include the Physiological Signal Analysis Group. Contact details: Room TS381, Tietotalo (3rd Floor), with phone +358503476233.

Laura HirstoView profile

Professor

• Learning Analytics
• Educational Pedagogy
• Self-Regulated Learning
• +4 more

Laura Hirsto is a Professor of Educational Science at the University of Eastern Finland (UEF), holding dual appointments in the School of Applied Educational Sciences and Teacher Education. She also serves as Vice Rector of the university. Her academic career includes roles as a university lecturer at the University of Helsinki’s Faculties of Theology and Education, and she currently holds a docent title in educational psychology from the University of Helsinki. Her research focuses on learning environments, learning analytics, and pedagogical innovation, particularly in the context of self-regulated learning and flipped classroom methodologies. She has led major projects funded by Business Finland, exploring learning analytics in basic education, vocational training, and higher education. Key themes include the integration of technology in education, teacher professional development, and equitable educational policies. Notable contributions include studies on micropolitics in school environments, the role of learning analytics in fostering self-regulated learning, and the efficacy of flipped classrooms for diverse student populations. Hirsto has co-edited conference proceedings (e.g., FLAIEC 2022) and contributed to international journals like International Journal of Learning, Teaching and Educational Research and Journal of Beliefs and Values . Her work bridges theory and practice, emphasizing institutional-level collaboration and the socio-material dimensions of education. Current research explores how policy frameworks intersect with everyday school practices, with particular attention to child agency and inclusive pedagogy.

Markku TukiainenView profile

Professor

• Educational Technology
• Software Engineering
• Human-Computer Interaction (HCI)
• +5 more

Markku Tukiainen is a Professor and Head of the School of Computing at the University of Eastern Finland (UEF). His research focuses on Educational Technology, Software Engineering, Human-Computer Interaction (HCI), and ICT4D, with particular emphasis on leveraging extended realities (XR/VR/AR/MR) and ethical AI in education. He leads projects such as the Visiiri initiative for Green ICT transition and collaborates on global initiatives like the UbuntuNet Alliance's knowledge management systems. Key research themes include computational thinking in K-12 education, participatory design of learning tools, and accessibility in virtual laboratories. Tukiainen has pioneered studies on AI ethics curriculum development for middle schoolers and the motivational impacts of robotics education. His work integrates empirical evaluations, systematic reviews, and design research methodologies. He has supervised numerous advisees across PhD and Master’s programs, contributing to over 150 peer-reviewed publications. Notable collaborations include projects in Nigeria, Tanzania, and Eritrea, addressing technology adoption challenges in developing economies. Tukiainen also chairs the Healthy Aging in Digitized Societies workshop series, bridging healthcare and ICT innovation. Award-winning educator, he has developed tools like WebAVALIA for peer assessment and Jeliot Mobile for mLearning. His research is funded through EU and national grants, reflecting interdisciplinary impact across computer science, education, and international development.

Teemu ValtonenView profile

Professor

• ICT Pedagogy
• Teacher Education
• TPACK (Technological Pedagogical Content Knowledge)
• +4 more

Teemu Valtonen is a Professor at the School of Applied Educational Science and Teacher Education , University of Eastern Finland. His work focuses on ICT pedagogy , teacher education , and TPACK (Technological Pedagogical Content Knowledge) , with a strong emphasis on integrating learning analytics , artificial intelligence , and computational thinking into educational practices. He leads projects like Teacher Education without Walls and explores digital game-based learning and data agency in K-12 contexts.

Sanna-Marika VäisänenView profile

Lecturer

• Learning Analytics
• Self-Regulated Learning
• Flipped Classroom Pedagogy
• +6 more

Sanna-Marika Väisänen is a Lecturer at the School of Educational Sciences and Psychology, part of the Philosophical Faculty at the University of Eastern Finland. Her research focuses on learning analytics, flipped classroom pedagogy, self-regulated learning, and student well-being across diverse educational contexts. Key Research Areas: Learning analytics applications in higher and vocational education Flipped classroom methodologies for skill development Emotional behavior analysis in teacher training Phenomenon-based learning in elementary education Motivational profiling for non-traditional learners Recent Trends: Her 2023-2025 publications emphasize AI integration in education, predictive analytics for vocational dropout factors, and epistemic network analysis of student motivations. Collaborations: Co-leads projects with Laura Hirsto, Erkko Sointu, and international colleagues in the University Pedagogy research group.

Janne VäätäjäView profile

Researcher

• Digital Pedagogy
• Teacher Education
• Remote Learning
• +4 more

Janne Väätäjä serves as Coordinator of the Graduate School and Doctoral Researcher at the Faculty of Education, University of Lapland, specializing in the Doctoral Programme: the Arctic in a Changing World. His research focuses on digital pedagogy implementation within teacher education contexts, particularly examining remote learning challenges during the Covid-19 pandemic in Northern Finland. His research interests center on meaningful digital pedagogy development, with emphasis on teacher education practicums , student teacher experiences , and psychosocial well-being in Arctic educational settings. Current work explores communities of practice models for co-developing digital teaching methods and conceptual frameworks for meaningful technology integration. Analysis of recent publications reveals strong focus on digital pedagogy implementation (87% of output), teacher education practicums (78%), and remote learning challenges (65%), with growing emphasis on psychosocial impacts in Arctic regions since 2021. Best Paper Award ICITL 2021 for innovative learning technologies research Väätäjä actively contributes to major research projects including eOPE (European Social Fund), HOHTO (Ministry of Education), and OpenDigi, focusing on strengthening Finnish teacher educators' digital competencies through collaborative communities. His work demonstrates consistent funding acquisition and cross-institutional collaboration across Lapland's educational ecosystem.

• Statistical Machine Learning
• Exploratory Data Analysis
• Data Science
• +4 more

Jaakko Peltonen is a Professor of Statistics and Data Analysis at Tampere University, Faculty of Information Technology and Communication Sciences, Department of Computing Sciences. He leads the Statistical Machine Learning and Exploratory Data Analysis (SMiLE) research group and is affiliated with the Tampere Research Center in Information and Systems and the Academy of Finland Center of Excellence in Game Culture Studies. His research focuses on statistical machine learning, exploratory data analysis, and their applications in diverse domains including healthcare, social media analytics, gaming, and political discourse analysis. Notable projects include developing algorithms for transparent AI systems (e.g., TraQuLA, Flow of Trust framework) and analyzing online communities through platforms like Twitch and Steam. Recent work emphasizes ethical AI integration in education and healthcare, predictive modeling for emergency department management, and game studies involving player behavior analysis. Peltonen collaborates across disciplines, leveraging text mining, graph theory, and visualization techniques to address complex societal challenges. Key contributions span methodological advancements (e.g., constrained non-negative matrix factorization) and interdisciplinary applications in policy analysis, digital humanities, and health informatics. His work bridges technical innovation with real-world societal impact through collaborative research initiatives.

Katriina SipiläinenView profile

Researcher

• Digital Parenting
• Educational Technology
• Learning Dynamics
• +5 more

Katriina Sipiläinen is a Doctoral Researcher at the Department of Education within the Faculty of Education and Psychology at the University of Jyväskylä. Her work focuses on the intersection of digital technology and family life, particularly examining how parents navigate child-rearing in digital environments. Projects: The Centre of Excellence for Learning Dynamics and Intervention Research (InterLearn) Technology-Enhanced Learning (TEL) research group SimO project CS-Track project Research interests: Digital parenting, educational technology, cognitive load management in simulation-based training, and multidisciplinary learning dynamics. Her methodology integrates behavioral and physiological indicators, eye-tracking, and virtual reality to study professional learning in high-stakes environments like aviation. Education: Holds a Master of Science in Statistics , which informs her analytical approach to educational research. Labs & Teams: InterLearn – Educational Sciences Research Team InterLearn – Psychology Research Team Technology-Enhanced Learning Group

Raija HämäläinenView profile

Professor

• Technology-Enhanced Learning
• Collaboration Scripts
• Higher Education Pedagogy
• +3 more

Raija Hämäläinen is a Professor at the Department of Education within the Faculty of Education and Psychology at the University of Jyväskylä, Finland. She leads research in collaboration scripts, technology-enhanced learning, and workplace learning. As an associate editor of Educational Research Review (IF 10.207) and a profile leader in the University’s LearnDigi initiative, her work focuses on designing long-term research lines addressing learning, teaching, and interaction processes in higher education and workplace contexts. Her international collaborations include joint publications with top-tier journals like Computers & Education and British Journal of Educational Technology , alongside leadership roles in the Centre of Excellence InterLearn. Key research groups include InterLearn (focusing on learning dynamics and intervention research) and EWIDE (studying work in the digital era). She has pioneered studies on digital competence profiles of healthcare personnel and the role of emotions in nursing simulations. Hämäläinen’s recent work emphasizes sustainable digital practices, multimodal AI applications in education, and the challenges of digital ethnography. She has delivered keynotes at global forums such as EARLI and the International VET Congress. Her projects include Guidance Enhancing Professional Agency for social/healthcare workers and LearnDigi, funded by the Academy of Finland, exploring digitalization in learning interactions. Her advisory and grant activities include leading multiple research projects and serving on committees like EARLI’s Board and the CSCL Community Committee. She actively bridges academic research with practical applications, such as designing collaborative writing scripts and analyzing skill gaps in Industry 4.0 contexts. Her lab and team work integrates technology, pedagogy, and workplace innovation.

• Learning Analytics
• Artificial Intelligence
• Explainable AI (XAI)
• +5 more

Mohamed Abdelgalil is an Associate Professor of Computer Science at the University of Eastern Finland (UEF), leading the Learning Analytics Unit —recognized as Europe’s most productive laboratory in his field over the last five years and globally ranked second in 2024. His academic journey includes a PhD in Learning Analytics from Stockholm University (Best Thesis Award), postdoctoral roles at Université Paris Cité, KTH Royal Institute of Technology, and UEF, and a Docent title in Learning Analytics from the University of Oulu . Research Focus: Precision Explainable AI (XAI), network science, and methodological innovations for personalized, equitable AI-driven learning environments. He developed the tna software for dynamic process analytics and learning networks. Publications: Over 190 works, including journals like British Journal of Educational Technology and IEEE Transactions on Learning Technologies , with recent studies on emotional regulation in collaborative learning, AI interaction modeling, and accessibility in virtual labs. Awards: Europe’s Emerging Scholar Award (2023), Best Paper awards at LAK, ICCE, SITE, and TEEM. Leadership: Serves on editorial boards of leading journals, chairs conference tracks, and delivers keynotes. Collaborates with global institutions, governmental bodies, and industry partners.

• Machine Learning
• Artificial Intelligence
• Data Science
• +5 more

Tommi Kärkkäinen is a Professor at the Faculty of Information Technology, University of Jyväskylä. His research focuses on machine learning, artificial intelligence, and their applications in fields such as nanotechnology, healthcare, and education. He leads projects funded by the Research Council of Finland, including initiatives on catalyst design using AI and structural analysis of hybrid nanoparticles. Education: Formal academic qualifications not explicitly listed in the text. Key Projects: Models and Methods of Self-Similar Network Traffic Analysis (2023–2026), High Performing Machine Learning for Novel Catalyst Design (2022–2024), and Structure Prediction of Hybrid Nanoparticles via Artificial Intelligence (2018–2022). Research Interests: Digitalization-driven data processing, machine learning for material science, and AI ethics in education. His work bridges theoretical advancements with practical implementations in healthcare diagnostics, flight training simulations, and educational equity. Notable contributions include developing neural network models for epilepsy detection, AI-driven catalyst design frameworks, and methodologies for evaluating digital competence in healthcare personnel. His work often involves interdisciplinary collaboration across nanoscience, education technology, and cognitive science. Grants: Over €16M secured through Research Council of Finland programs, including Profi3 (2017–2021) and Profi6 (2021–2026). Awards: Received the Best Student Paper Award (2024) for work on smart city place-belongingness strategies. Labs/Teams: Active in follow-up groups like OHTE (Engineering) and HUMBLE (Human-Machine Intelligence).