جست‌وجوی استاد و پژوهشگر

Miika Marttunenمشاهده پروفایل

استاد

• Computer-Supported Collaborative Learning
• Argumentation Skills
• Digital Literacy
• +۳ مورد دیگر

Miika Marttunen is a Professor at the University of Jyväskylä's Faculty of Education and Psychology, Department of Education. His research focuses on computer-supported collaborative learning, argumentation, and digital literacy, with notable contributions to projects like ARONI and DETECT. He supervises M.A. and PhD students and holds administrative roles including membership in the University Collegium and the Faculty Council. His research interests emphasize online inquiry skills, collaborative writing, and interventions to enhance source evaluation. Recent projects include developing assessment tools for argumentative inquiry and testing pedagogical methods for detecting disinformation. He has extensive experience with quasi-experimental designs in educational technology contexts. Publications highlight advancements in collaborative learning dynamics, source credibility evaluation, and multimodal argumentation. Key contributions include analyzing online inquiry phases, interventions for adolescents, and role-play simulations in social work education. His work bridges theoretical research with practical educational tools and interventions. Marttunen leads the InterLearn research team within the Centre of Excellence for Learning Dynamics, focusing on individual responses to educational support. He also contributes to LearnDigi, examining digitalization's impact on learning and interaction.

Mikko Aroمشاهده پروفایل

استاد

• Special Education
• Educational Psychology
• Learning Disabilities
• +۵ مورد دیگر

Mikko Aro is a Professor of Special Education at the University of Jyväskylä, affiliated with the Department of Education within the Faculty of Education and Psychology. He co-directs the Center of Excellence in Learning Dynamics and Intervention Research (InterLearn), funded by the Academy of Finland (2022–2029). His research focuses on learning disabilities, particularly in literacy and mathematics, and the development of effective interventions. Aro holds a PhD in Psychology from the University of Jyväskylä and has extensive international training in child neuropsychology and neuropsychology. His research interests span typical and atypical learning processes, including the role of cognitive, motivational, and emotional factors in skill acquisition. He has led projects on learning difficulties, intervention efficacy, and assessment practices. Key contributions include studies on reading fluency, math anxiety, and the integration of self-efficacy interventions into educational strategies. Aro’s extensive publications reflect his commitment to advancing understanding of learning disabilities and improving educational support systems. He collaborates with institutions like the Finnish National Agency for Education and the European Commission on projects addressing teacher training, assessment methodologies, and multisite cohort studies. His work emphasizes evidence-based interventions, such as computer-assisted training for struggling readers and strategies to enhance self-efficacy. He advocates for clearer frameworks in educational support, particularly through the Response-to-Intervention (RTI) model. Aro’s research bridges cognitive science, educational policy, and practical classroom applications, aiming to create inclusive and effective learning environments.

• Conversation Analysis
• Interactional Linguistics
• Peer Support
• +۷ مورد دیگر

Saija Merke is a University Lecturer in the Faculty of Arts, Psychology and Theology at Åbo Akademi University, specializing in the Department of Languages. Her academic work bridges linguistics, education, and health sciences, with a strong focus on interactional dynamics in learning and professional contexts. Her research interests lie at the intersection of conversation analysis, peer support mechanisms, and educational discourse. She investigates how knowledge is co-constructed in practical nursing study circles, classroom interactions, and storytelling events. Key themes include epistemic authority, peer advice, and the role of digital platforms in shaping interaction. Her work employs ethnomethodological conversation analysis to uncover the micro-structures of communication that facilitate learning. The trends in her recent publications reflect a sustained engagement with peer interaction in educational settings, particularly in nursing and language learning. Her work spans both empirical studies and critical reviews, with increasing attention to digital interaction and its methodological implications. She frequently publishes in interdisciplinary venues that connect linguistics, education, and health sciences. Saija Merke has contributed to key journals such as Linguistics and Education , Puhe ja Kieli , and Virittäjä , as well as book chapters with Åbo Akademi University Press. Her research is openly accessible and has been downloaded internationally, indicating a growing scholarly impact. She is actively involved in mentoring and academic discourse, though no formal advisees are listed. Her collaborations include researchers in Finland and potentially beyond, as indicated by her network in nursing and linguistic studies. While no specific grants or awards are mentioned, her consistent publication record suggests sustained research activity. She contributes to academic discourse through book reviews and theoretical reflections, particularly on the state of digital interaction research. Her work helps map emerging fields and identify future directions for interdisciplinary scholarship.

• Boolean Optimization
• Constraint Reasoning
• Satisfiability (SAT) Solving
• +۳ مورد دیگر

Matti Järvisalo is a Professor in the Department of Computer Science at the University of Helsinki, Finland, holding the title of Docent and serving as Supervisor for the Doctoral Programme in Computer Science. He is affiliated with the Helsinki Institute for Information Technology (HIIT), a leading collaborative research institute between the University of Helsinki and Aalto University. His research centers on computational logic and constraint-based reasoning, with core expertise in Boolean optimization, SAT/MaxSAT solving, and argumentation frameworks. He develops declarative approaches for combinatorial problems in computational social choice, judgment aggregation, and fair division, emphasizing certified algorithms and preprocessing techniques. His work bridges theoretical computer science with practical implementations in optimization and AI. Recent publications (2024-2025) reveal a strong focus on multi-objective optimization, certified reasoning, and argumentation under incomplete information. Key trends include symmetry-aware core learning for Pseudo-Boolean optimization, Pareto-optimality certification in MaxSAT, and novel algorithms for manipulation analysis in judgment aggregation, demonstrating his leadership in advancing SAT-based AI methods. Professor Järvisalo's significant contributions have been recognized by prestigious awards: IJCAI-JAIR Best Paper Prize (2019) Best Researcher Award from University of Helsinki Department of Computer Science (2011) CP 2017 Distinguished Paper Award ECAI 2016 Runner-Up Best Student Paper Award Honorary Mention at ICCMA 2015 He actively mentors the next generation of researchers and secures major research funding: Supervision: 6 doctoral theses and 6 Master's/Licentiate theses Active Grant: Academy of Finland project 'Next-generation Unsatisfiability-based Declarative Optimization' (2023-2027) Past Projects: 'Symbolic Techniques for Formally Verified and Explainable AI' (2020-2022), 'Declarative Boolean Optimization: Pushing the Envelope' (2019-2023) As a core member of HIIT, he collaborates within Finland's premier information technology research ecosystem, contributing to the institute's mission of advancing fundamental and applied IT research through interdisciplinary teamwork and international partnerships.

Mika Ruokonenمشاهده پروفایل

استاد مدعو

• Artificial Intelligence
• Business Strategy
• Digital Transformation
• +۳ مورد دیگر

Mika Ruokonen serves as an Industry Professor at LUT University's Business School, with a new AI-focused industry professorship commencing in August 2025 on the Lahti campus. His role is funded by the PHP Foundation, Padasjoki Savings Bank Foundation, Lahti Industrial Association Foundation, and City of Lahti with a total of 310,000 euros for a three-year part-time position. As the largest donor, the PHP Foundation contributed 150,000 euros to this initiative. Ruokonen specializes in artificial intelligence research, particularly in business applications, collaborating with Professor Paavo Ritala. His doctoral work was completed at LUT in 2008, and he brings extensive business management experience to his academic role. He has gained recognition as an AI expert in Finnish media and internationally through numerous studies and public statements on AI strategies. His research interests center on practical AI implementation in business contexts, with focus areas including generative AI for strategic advantage, industrial AI capabilities development, AI-first business strategies, and the application of AI in European industries. His work bridges academic research with practical business applications, emphasizing how organizations can leverage AI for competitive advantage and operational transformation. Ruokonen's publication record shows a strong focus on the intersection of AI technologies and business strategy, with recent work examining generative AI, metaverse strategies, conversational AI in knowledge industries, and data-driven competitiveness. His research demonstrates a clear trajectory from foundational digital transformation concepts to cutting-edge AI applications across various business functions. His new role involves speaking at AI-related events in Lahti, with the first engagements planned for late 2025. The position aims to build 'broader shoulders for AI research' that is more extensive, faster, and less dependent on individual researchers. Ruokonen emphasizes that his contribution combines academic expertise with practical business skills and contacts, particularly supporting AI development from a management perspective. He has authored significant reports including 'Applying AI in Key European Industries' for the Finnish Innovation Fund Sitra, where he advocates for European investment in AI infrastructure, expertise, models, and data availability. His recommendations include European single market harmonization, affordable computing resources, multilingual large language models, reliable European data spaces, AI workforce training, and talent retention strategies.

Heikki Ailistoمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Software Engineering
• Smart Buildings
• +۴ مورد دیگر

Heikki Ailisto serves as a Research Professor at VTT Technical Research Centre of Finland within the BA5A Management and Support department. With a research career spanning from 1985 to present, he maintains active involvement in cutting-edge technology research and development projects. His research interests focus on Artificial Intelligence applications , Software Engineering methodologies , Smart Building technologies , and Digital Governance frameworks . A significant portion of his work addresses the practical implementation of AI systems in public sector contexts and industrial applications, with particular attention to Finnish societal needs and environmental considerations. Analysis of his recent publications reveals a strong trend toward interdisciplinary research connecting technology development with policy implications and sustainability goals. His work consistently bridges theoretical concepts with practical implementations, particularly in energy management systems and manufacturing data integration. Dr. Ailisto actively contributes to major research initiatives including: Future of Software Engineering (2025-2027) GOWELL: Governance of new technologies towards sustainability and well-being (2024-2026) His media presence includes contributions to discussions about AI development in Finland, such as the 2021 media appearance "Kohti tekoälyn kesää?" (Toward the Summer of AI).

• Data Mining
• Graph Theory
• Computational Biology
• +۲ مورد دیگر

Laura Langohr is a Postdoctoral Researcher at the Finnish Institute of Molecular Medicine (FIMM), University of Helsinki, specializing in computational approaches to biomedical research. Her work bridges computer science and molecular medicine through advanced data analysis techniques. Her core research domains include: Data Mining for pattern extraction in complex datasets Graph Theory applied to biological networks Computational Biology for genetic and physiological modeling Network Analysis of weighted and probabilistic systems Genetics-focused algorithm development Langohr's publication history reveals consistent innovation in subgroup discovery and network algorithms, with emphasis on identifying non-redundant information and representative nodes in biological contexts. Her methodologies directly support molecular medicine applications through computational rigor. Current research funding includes: MetaStem: Academy of Finland Center of Excellence in Stem Cell Metabolism (2023-2025) New insights into leukemia development (Academy of Finland, 2022-2026) iCAN: Digital personalized cancer medicine flagship (Academy of Finland, 2022-2026) Organ transport mechanisms in stem cells (Academy of Finland, 2024-2028) No scientific awards or fellowships are documented in available sources. As a research-focused academic, her contributions center on collaborative project execution rather than formal student supervision. She operates within FIMM's interdisciplinary ecosystem, connecting computational theory with experimental biomedical research.

Victor Bolbotمشاهده پروفایل

پژوهشگر

• Autonomous ships
• Marine systems safety
• Ship propulsion systems
• +۳ مورد دیگر

Victor Bolbot serves as a Postdoctoral Researcher in the Department of Energy and Mechanical Engineering at Aalto University, Finland, affiliated with the Marine and Arctic Technology research group. His work focuses on advancing safety, reliability, and cybersecurity frameworks for autonomous maritime systems through rigorous systems engineering approaches and data-driven methodologies. He maintains active collaborations with international researchers and institutions, evidenced by extensive co-authorship across high-impact publications. Dr. Bolbot's research centers on autonomous ships, marine systems safety, ship propulsion cybersecurity, and risk modeling. He employs systems-theoretic process analysis (STPA), Bayesian networks, and association rule mining to address critical challenges including maritime accident causation, cybersecurity vulnerabilities in dual-fuel engines, safety acceptance criteria for autonomous vessels, and socio-technical implications of maritime automation. His methodological innovations bridge theoretical safety engineering with practical applications in Arctic navigation, inland waterways, and regulatory compliance, emphasizing the integration of cyber-physical risk assessment. Analysis of his 2023-2025 publications reveals three dominant research trajectories: (1) Development of cyber-physical risk frameworks like STPA-Cyber for maritime cybersecurity; (2) Real-time Bayesian modeling for dynamic operations including remote pilotage and ice navigation; and (3) Socio-technical investigations into regulatory frameworks, educational needs, and workforce skill transformations for autonomous shipping. His work consistently addresses the interplay between technological innovation and safety assurance, with growing emphasis on cybersecurity as a critical maritime safety component. As an active member of Aalto University's Marine and Arctic Technology research group, Dr. Bolbot contributes to interdisciplinary projects tackling complex challenges in marine safety engineering, Arctic operations, and sustainable maritime technologies. The group's collaborative environment supports the development of safer, more efficient, and environmentally conscious maritime systems through experimental validation, computational modeling, and industry partnerships.

• Clinical Neuropsychology
• Attention Deficit Hyperactivity Disorder
• Pediatric Neurology
• +۳ مورد دیگر

Kati Rantanen is a researcher at the School of Health Sciences, University of Eastern Finland, focusing on clinical neuropsychology and rehabilitation for children with attention deficit hyperactivity disorder (ADHD) and early-onset epilepsy. Her work bridges neuropsychological training with human-computer interaction, particularly gestural interfaces for children with attention deficits. University of Eastern Finland, School of Health Sciences Researcher in Clinical Neuropsychology and Rehabilitation Her research explores mid-air gestural interactions for ADHD children, embodied video games for impulse control, and academic outcomes in pediatric epilepsy. She has published extensively on these topics, often collaborating with multidisciplinary teams in Finland. Recent publications include studies on fogscreens for ADHD interventions, embodied games like PigScape, and cognitive peer-training frameworks. She has also contributed to neuropsychological rehabilitation literature and reviewed for journals like Epilepsy & Behavior.

Christopher Görschمشاهده پروفایل

استاد مهمان

• Construction Management
• Worker Productivity
• Situational Awareness in Construction
• +۳ مورد دیگر

Christopher Görsch is a Visiting Professor at Aalto University’s Department of Civil Engineering, focusing on construction workflows, productivity, and situational awareness. He holds a PhD in Construction Engineering (2024) and a Master’s in Engineering from Bauhaus-Universität Weimar (2016). His research emphasizes reducing waste in construction, improving worker efficiency, and integrating digital tools like digital twins and AI into workflows. Key projects include the ACTOR initiative for automated coordination of construction actors and studies on self-managed teams. Görsch has received the Greg Howell Best Paper Award (2022) and a Research Visit Grant to Swinburne University (2020). His work spans academic qualifications, including a doctoral thesis on task planning in construction. Research interests highlight interdisciplinary approaches combining technology (e.g., IoT, AI) with human factors, such as worker demands and situational awareness. Collaborations include teams analyzing workflow interruptions and sustainability in BIM systems. Press coverage highlights his findings on productivity losses in construction work. Education: PhD in Construction Engineering (Aalto U., 2024), M.Sc. Engineering (Bauhaus U., 2016) Key Projects: ACTOR Project, Building 2030 Digital Twin Initiative Grants/Awards: Greg Howell Award, Australia Research Visit Grant Press Highlights: Revealed up to 80% of construction work as non-productive (2024) Recent articles emphasize automation (e.g., Choosing by Advantages algorithms) and digital tools to enhance decision-making. His datasets, such as Time-Motion Data of Construction Work, support quantitative analyses of workflow interruptions. Görsch’s lab activities include cross-disciplinary teams addressing managerial adoption of digital systems and worker empowerment strategies.

Maria Ballestar de las Herasمشاهده پروفایل

دانشیار مهمان

• Statistics
• Probability
• Artificial Intelligence
• +۱۲ مورد دیگر

Maria Ballestar de las Heras is a Visiting Associate Professor at LUT University, School of Engineering Sciences, where her work intersects Social Sciences, Statistics, and Artificial Intelligence. She is concurrently an Associate Professor in Applied Economics at Universidad Rey Juan Carlos (URJC), Madrid, Spain, and serves as Head of Analytical Consultants at Google in Spain, demonstrating a strong bridge between academia and industry. Universidad Rey Juan Carlos – Associate Professor, Applied Economics LUT University – Visiting Associate Professor, School of Engineering Sciences Google Spain – Head of Analytical Consultants She earned her B.A. in Statistics from Universidad de Zaragoza, M.Sc. in Marketing and Market Research, and M.A. in Information and Knowledge Society from Universitat Oberta de Catalunya, and her Ph.D. in Applied Economics from Universidad Rey Juan Carlos. Her research focuses on applying data science, Big Data, and AI to real-world problems in customer behavior, digital transformation, public policy evaluation, and sustainability. She investigates how AI can enhance marketing strategies, evaluate educational reforms, predict stock markets, and analyze social media discourse on climate change. Her interdisciplinary approach integrates economics, marketing, and machine learning to generate actionable insights for businesses and policymakers. Her recent publications (2021–2025) reveal a consistent trend in leveraging machine learning and AI for business and social impact, particularly in e-commerce, robotics adoption, and educational policy. She frequently collaborates with researchers such as Jorge Sainz, Ismael Sanz, and Taraneh Shahin. Scientific Contributions: Published over 20 articles in leading journals including Technological Forecasting and Social Change , Journal of Business Research , and IEEE Transactions on Engineering Management . Active peer reviewer for journals like Arabian Journal for Science and Engineering and Journal of Business Research . She advises on data-driven decision-making and digital innovation, though no formal students are listed. She leads research at the intersection of technology and society, contributing to both academic knowledge and industrial practice. Her work is supported by her extensive industry experience across banking, IT, and pharmaceuticals.

• Neuroscience
• Biomedical Engineering
• Machine Learning
• +۴ مورد دیگر

Koen Van Leemput is a Professor at the Department of Neuroscience and Biomedical Engineering at Aalto University, Finland. His work bridges neuroscience and computer science , focusing on generative models , magnetic resonance imaging (MRI) , and machine learning applications in neurodegenerative diseases like Alzheimer's Disease and Multiple Sclerosis (MS) . Research Highlights: Development of interpretable AI models for subject-level prediction in neuroimaging. Advancements in uncertainty quantification for neuroimage registration. Leadership in the CLAIMS project , creating AI-driven prognostic models for MS progression. Pioneering MRI intensity scaling techniques to improve quantitative imaging reliability. Scientific Contributions: Editorial Roles: Served on the board of IEEE Transactions on Medical Imaging and Medical Image Analysis (2014). Collaborations: Includes affiliations with Harvard Medical School and Technical University of Denmark (DTU).

Johan Liliusمشاهده پروفایل

استاد

• Embedded Systems
• energy-efficient software
• safety in autonomous systems
• +۵ مورد دیگر

Professor Johan Lilius is a Full Professor of Embedded Systems at Åbo Akademi University's Faculty of Science and Engineering, Department of Information Technology. He has held this position since 2001 and currently serves as Head of Research. Prof. Lilius has demonstrated extensive leadership throughout his career, having served as director of the Turku Center for Computer Science (TUCS) and multiple terms as Head of the Department of Information Technology, where he led significant departmental restructuring and educational reform efforts through two major university reorganizations. He is currently a member of the steering group for Digivisio2030, a national initiative involving all Finnish higher education institutions aimed at building a new educational ecosystem. Prof. Lilius's research focuses on energy-efficient software, safety in autonomous systems, and neuro-symbolic computing. His work contributes to the UN Sustainable Development Goals, particularly in technology and environmental sustainability. His research interests span autonomous navigation, data-parallel computing, energy-aware systems, and maritime technology. His work bridges theoretical computer science with practical applications in embedded systems, particularly in maritime contexts. Analysis of his recent publications shows a strong trend toward autonomous systems, particularly in maritime applications, with significant work on energy efficiency in embedded architectures. His research increasingly integrates AI and machine learning approaches with traditional software engineering, focusing on safety-critical systems where reliability is paramount. The fingerprint analysis of his work reveals strong connections to convolutional neural networks, autonomous navigation algorithms, and scenario-based testing for complex systems. Ten-Year Most Influential Paper Award at the ACM/IEEE Conference on Model Driven Engineering Languages and Systems Several Best Paper Awards 2015 Gadd Prize for Research Excellence at Åbo Akademi Prof. Lilius has demonstrated exceptional commitment to doctoral education, having supervised over 10 completed doctoral theses and currently mentoring several PhD students. He leads the TUCS Graduate program and has co-organized numerous academic workshops, summer schools, and conferences. His research is supported by significant projects including EDISS (Engineering of Data-intensive Intelligent Software Systems), IoT Reboot Factory, DECATRIP (Decarbonizing Transport Corridors), SMARTER (Sea4Value Smart Terminals), and AutoMare EduNet (Autonomous Maritime Education Network), funded by the European Commission, Business Finland, and other organizations. Prof. Lilius collaborates extensively through the Turku Center for Computer Science (TUCS) and participates in national initiatives like Digivisio2030. His work often involves interdisciplinary teams focusing on the intersection of software engineering, AI, and practical maritime applications, with strong industry partnerships that ensure real-world impact of his research.

• Materials Science
• Computational Chemistry
• Machine Learning
• +۴ مورد دیگر

Miguel Caro serves as an Assistant Professor in the Department of Chemistry and Materials at Aalto University, where his research integrates computational methods with materials science to address complex challenges in atomic-scale modeling and catalytic processes. His primary research domains encompass: Materials Science Computational Chemistry Machine Learning Catalysis Nanomaterials Electrochemistry Amorphous Materials Specializing in the development of machine learning interatomic potentials, Caro focuses on modeling hydrocarbon systems, carbon-based nanomaterials, and electrocatalytic phenomena. His work bridges theoretical simulations with experimental validation, particularly in hydrogen evolution reactions, CO 2 reduction, and thermal transport properties of disordered materials. Recent publications (2023–2025) reveal a cohesive research trajectory centered on machine learning-driven materials discovery. Key contributions include unifying frameworks for carbon material descriptions, anomalous catalytic effects in bimetallic nanoclusters, and advanced methodologies for modeling amorphous systems. His approach consistently combines computational innovation with practical applications in energy conversion and sustainable chemistry. Caro actively contributes to the DAS Group at Aalto University, which pioneers data-driven strategies for materials characterization and design. This collaborative environment supports his interdisciplinary investigations spanning quantum mechanics, machine learning, and experimental materials science. No information regarding student supervision, grant funding, or scientific awards is available in the source material.

Lassi Roininenمشاهده پروفایل

استاد

• Statistics and Probability
• Geophysics
• Applied Mathematics
• +۵ مورد دیگر

Lassi Roininen is a tenured Professor of Applied Mathematics at LUT University's School of Engineering Sciences, holding this position since September 2022 after serving as Assistant Professor there from 2018 to 2022. He maintains significant adjunct appointments as Associate Professor at University of Oulu, Assistant Professor at Bahir Dar University (Ethiopia), and faculty member at AIMS Rwanda, demonstrating strong international academic engagement. Education: Master of Science (Engineering), Tampere University of Technology Doctorate in Applied Mathematics, University of Oulu (2015) - conducted at Sodankylä Geophysical Observatory His research integrates Statistics, Geophysics, and Applied Mathematics with core expertise in Bayesian inference, uncertainty quantification, and inversion problems. He develops computational frameworks for geophysical imaging, climate modeling, and industrial applications, emphasizing robust statistical methodologies for real-world data challenges. Recent work shows increasing focus on African climate adaptation and medical/industrial tomography. Analysis of his 15 most recent publications reveals dominant trends in Bayesian approaches to climate science (particularly East African adaptation studies), medical/industrial imaging (tomography and fault detection), and geophysical modeling. His work consistently bridges mathematical innovation with practical applications across environmental science, healthcare, and manufacturing sectors. Research support includes Academy of Finland postdoctoral funding. Through AIMS Rwanda, he actively mentors African mathematicians and contributes to capacity building in computational sciences across the continent. His collaborative projects demonstrate commitment to solving region-specific challenges through advanced statistical methods. His work is closely tied to geophysical research networks including Sodankylä Geophysical Observatory, with recent expansions into East African climate resilience initiatives. Current projects integrate multi-instrument atmospheric data with Bayesian frameworks to address pressing environmental challenges in developing regions.