Find Academic Supervisors

• Magnetoencephalography
• Neuronal Activity
• Brain Network
• +5 more

Sheng Wang serves as a Visiting Faculty member in the Department of Neuroscience and Biomedical Engineering at Aalto University's School of Science. His research bridges neuroscience, biomedical engineering, and computational approaches to understand brain function and disorders. Dr. Wang's research focuses on brain criticality, neuronal synchronization, and network dynamics using advanced neuroimaging techniques including magnetoencephalography (MEG) and electroencephalography (EEG). His work particularly examines these phenomena in the context of epilepsy and neurodegenerative disorders like Parkinson's disease. He applies computational approaches including machine learning to analyze complex brain network data and develop biomarkers for clinical applications. His publication record shows a clear trajectory focusing on brain network dynamics, with recent work exploring cortical criticality changes in neurodegenerative conditions and developing novel computational methods for epileptogenic zone localization. His research demonstrates strong interdisciplinary collaboration across neuroscience, engineering, and clinical medicine. Dr. Wang has contributed to significant datasets including the 'Modules in Human Electrophysiological Connectomes of Phase-Synchronization,' supporting open science in neuroscience research. His work contributes to UN Sustainable Development Goals related to good health and well-being through advancing understanding of neurological disorders.

Nada SanadView profile

Researcher

• data-driven decision-making
• human-machine collaborative rationality
• hybrid intelligence
• +9 more

Nada Sanad is a postdoctoral researcher at the Empirical Software Engineering in Software, Systems, and Services (M3S) research unit at the University of Oulu's Faculty of Information Technology and Electrical Engineering. She earned her Ph.D. (2024) in Information Processing Science from the University of Oulu, focusing on data-driven decisions and human-machine collaboration. She holds a B.Sc. (2011) and M.Sc. (2013) in Business Informatics from the German University in Cairo, Egypt, with a focus on data mining and big data analytics. Her research interests span data-driven decision-making, hybrid intelligence, human-machine collaboration, AI/ML for decision support, big data analytics, and business intelligence. Her work emphasizes ethical and practical applications of AI in decision-making processes, particularly in autonomous systems and manufacturing contexts. Recent publications (2023–2025) highlight trends in evaluating AI-driven decisions, hybrid intelligence frameworks, and data governance in industry. She contributes to projects like OXILATE, integrating AI insights into actionable expertise. Nada Sanad has not been listed as having formal advisees but collaborates actively in interdisciplinary teams at the M3S unit. She maintains profiles on ORCID, SCOPUS, Google Scholar, and ResearchGate.

Riikka HirvonenView profile

Researcher

• Educational Psychology
• Developmental Psychology
• School Well-being
• +3 more

Riikka Hirvonen is a Senior Researcher at the University of Eastern Finland (UEF) in the School of Applied Educational Science and Teacher Education, part of the Philosophical Faculty. She holds a PhD in Psychology and has been at UEF since 2019, previously working at the University of Jyväskylä. Her research focuses on primary and secondary students’ academic behaviors, emotions, and well-being, particularly exploring how temperament and learning environments influence achievement and adjustment. She is affiliated with the Motivation, learning, and well-being (MoLeWe UEF) research group and leads projects like 'Sustainable Food Education and Food Waste' and 'STAIRWAY study.' Her educational background includes a PhD in Psychology, with no listed formal degrees beyond this. Research interests span academic emotions, self-regulation, statistical modeling, and teacher education roles. Notable projects investigate motivation dynamics during educational transitions and pandemic impacts on student well-being. Riikka’s work emphasizes practical pedagogy in teacher training schools, balancing subject expertise with mentorship for student teachers. Recent publications (2021–2025) highlight themes like teacher educator roles, maternal homework involvement, and adolescent mental health interventions. She collaborates widely, co-authoring studies on classroom climate, perfectionism, and remote learning during the pandemic. Key contributions include developing programs like the 'Youth Compass' for adolescent mental health and analyzing bidirectional influences between family involvement and academic motivation. Her research bridges theory and practice, aiming to improve support systems for students with learning or adjustment challenges.

Ricardo Henriques CorreiaView profile

Assistant Professor

• Biodiversity Conservation
• Human-Nature Interactions
• Ecosystem Services
• +3 more

Ricardo Henriques Correia is an Assistant Professor at the Biodiversity Unit of the University of Turku, PhD. His research focuses on biodiversity conservation, human-nature interactions, ecosystem services, and digital methods in ecological studies. He actively develops computational tools like gtrendsAPI (an R package for Google Trends integration) and contributes to conservation culturomics, which leverages online data to assess public engagement with environmental issues. His work spans multiple continents, including analyses of conservation priorities in sub-Saharan Africa, Brazil, and Europe. He collaborates with interdisciplinary teams to explore topics such as species charisma in academic literature, political vulnerability of protected areas, and invasive species detection using machine learning. Correia also investigates the cultural and psychological dimensions of human-nature relationships, linking biodiversity awareness to societal well-being. Ricardo’s research emphasizes leveraging digital platforms (e.g., social media, citizen science) to address conservation challenges. He has published extensively in high-impact journals like Proceedings of the Royal Society B , PLoS Biology , and Biological Conservation , often focusing on data-driven approaches to biodiversity monitoring and policy evaluation. His contributions include pioneering the use of culturomics to quantify species salience and public interest in conservation efforts. He is affiliated with the BISONS Lab , an interdisciplinary research group at the University of Turku. While no personal scientific awards are explicitly listed, his work has been recognized in innovation awards from the Journal of Biogeography (2022) for advancing methodological approaches in conservation geography. Ricardo’s grants and advising activities are not detailed in the provided texts, but his research portfolio indicates sustained support for projects involving open-access publishing, stakeholder collaboration, and digital data integration. His work bridges ecology, technology, and social sciences to create actionable insights for global conservation strategies.

Riikka KangaslampiView profile

Lecturer

• Discrete Geometry
• Mathematics Education
• Graph Theory
• +3 more

Riikka Kangaslampi is a University Lecturer in the Computing Sciences department at Tampere University, affiliated with the Faculty of Information Technology and Communication Sciences. She holds a Doctor of Science degree and the title of docent in mathematics. Her research focuses on discrete geometry, mathematics education, and graph theory, with particular emphasis on interdisciplinary approaches combining mathematics with arts, architecture, and engineering education. Her research interests include discrete curvatures in graphs, student approaches to learning in engineering mathematics, and innovative pedagogical methods. She leads studies on instructional models, student-centered learning environments, and the psychological aspects of mathematics education. Collaborations involve multidisciplinary teams exploring connections between mathematics and creative fields. Recent work examines changes in student learning approaches during the pandemic, interdisciplinary group work dynamics, and the impact of different teaching methodologies. She contributes to both theoretical mathematics through graph curvature studies and applied educational research addressing practical teaching challenges in higher education. Her research groups include the Technology Supported Mathematics Education Research Group and the Algebra, Geometry and Topology Research Group. She actively publishes in education-focused journals like International Journal of Education in Mathematics, Science and Technology, and mathematics theory journals such as Communications in Analysis and Geometry.

• Information Systems
• Technostress
• Extended Reality (XR)
• +7 more

Henri Pirkkalainen is a Professor of Information and Knowledge Management at Tampere University's Faculty of Management and Business, leading the Doctoral Programme in Business and Technology Management (TOTO). He is Vice Director of the Research Centre of Gameful Realities and Editor-in-Chief of the Scandinavian Journal of Information Systems. His research focuses on mitigating technostress, exploring metaverse and extended reality (XR) applications, and analyzing the impact of technology on organizational workflows and employee well-being. He holds a Master’s from the University of Jyväskylä and transitioned from IT consulting to academia through EU project coordination. His career emphasizes bridging academic disciplines and fostering interdisciplinary collaboration. Key research areas include technostress in software development, robotic workplace integration, and gamification strategies. He investigates how immersive technologies like the metaverse affect user experiences and organizational efficiency, with recent studies on AI-driven recommendation systems in education and micro-credential platforms. Pirkkalainen advocates for balancing technological innovation with human-centric solutions to address burnout and resistance to digital tools. His academic contributions span over 50 peer-reviewed articles, with a focus on digital transformation challenges. Beyond academia, he plays drums semi-professionally and bakes sourdough bread, practices he links to sustained creativity and problem-solving in research.

• Flexible Manufacturing Systems
• Production Systems
• Engineering Education
• +3 more

Ville Toivonen is a Doctoral Researcher at Tampere University of Technology's Faculty of Engineering and Natural Sciences , focused on production engineering and engineering education. He holds a Master of Science (Technology) and Bachelor of Science (Technology) in Industrial Management, with research contributions spanning flexible manufacturing systems, digital twins, and SME network collaboration.

• Service Design
• Creative Services
• Fast Fashion
• +4 more

Karl-Jacob Mickelsson is a Senior Lecturer at Åbo Akademi University's School of Business and Economics, Faculty of Social Sciences, Economics and Law. His research bridges service design, digital innovation, and sustainability, with a focus on creative services, fast fashion CSR, and health/social care ecosystems. SDG Contributions Industry, Innovation and Infrastructure Reduced Inequalities Good Health and Well-being Sustainable Cities and Communities His scholarly work explores: Service design methodologies (ActS framework) Digital platforms for professional competence reflection AI as a creative service enabler CSR reputation dynamics in fast fashion User-defined healthcare ecosystems Publications show expertise in: Service system modeling Human activity theory applications Stakeholder alignment in CSR AI-human collaboration Meta-service design Chronic condition management

• Extended Reality Technologies
• Organizational Adoption
• Information Systems
• +3 more

Henri Jalo is a Postdoctoral Research Fellow at the Faculty of Management and Business, Department of Information and Knowledge Management at Tampere University. His research focuses on extended reality (XR) technologies, organizational adoption challenges, and their applications in facility management, industrial collaboration, and digital campus environments. He specializes in mixed methods studies analyzing user resistance, enabling factors for technology diffusion, and virtual team dynamics. Key research themes include: Extended Reality (AR/VR/MR) adoption in SMEs and industrial sectors Metaverse collaboration and virtual workspaces Technology-enabling factors for digital transformation Social virtual reality applications in property lifecycle management His recent work (2021–2024) emphasizes XR's strategic role in organizational innovation, remote collaboration, and facility lifecycle optimization. He has conducted large-scale surveys on XR adoption in European manufacturing and pioneered studies on metaverse collaboration effectiveness over sustained periods. Publications highlight interdisciplinary approaches combining information systems theory with practical industry challenges in construction, real estate, and higher education environments. Current projects likely explore emerging XR applications in post-pandemic organizational workflows and digital twin integration.

Samuli SimeliusView profile

Researcher

• Ancient History
• Archaeology
• Roman Urbanism
• +4 more

Samuli Simelius is an active University Researcher at the Centre for European Studies, University of Helsinki. He serves as Supervisor for the Doctoral Programme in History and Cultural Heritage and is affiliated with the Helsinki Inequality Initiative (INEQ) and Law, Governance and Space research group. His work bridges traditional archaeological methods with innovative digital approaches, particularly focusing on ancient social structures and urban environments. Simelius specializes in Roman urbanism, social inequality in antiquity, and the application of digital humanities to historical research. His recent work heavily features AI-assisted analysis of ancient social stratification, particularly examining visual representations of inequality in Roman urban contexts. His research combines traditional archaeological fieldwork with cutting-edge digital methodologies, creating interdisciplinary bridges between historical studies, spatial analysis, and computational approaches. He has been actively involved in multiple research projects focused on Roman urban inequality, including the RUIn project and the Urbaani eriarvoisuus antiikin Roomassa initiative. His publication trends show a significant shift toward digital methodologies in the last few years, with numerous 2024-2025 publications exploring AI applications in historical research, Roman urban inequality metrics, and visual reconstructions of ancient social structures. This represents an evolution from his earlier work which focused more on Pompeian gardens, Roman domestic architecture, and spatial analysis of ancient cities. Simelius maintains an active presence in academic discourse through 108 recorded activities including conference presentations, public talks, and academic visits. His media engagement demonstrates a commitment to public scholarship, with 8 media contributions discussing historical accuracy in video games, ancient societal structures, and contemporary relevance of classical studies. His research is supported by multiple active projects including the RUIn project (2024-) and Urbaani eriarvoisuus antiikin Roomassa (2025-2028), funded by Kone Foundation and Säätiö Institutum Romanum Finlandiae. He participates in international collaborations including the Casa della Regina Carolina Project (since 2018) and the Ancient Labor Network (2024), demonstrating extensive engagement with the global archaeological community. His institutional affiliations with the Helsinki Inequality Initiative position his work at the intersection of historical research and contemporary social inequality studies.

Ekaterina GilmanView profile

Researcher

• Data Analytics
• Context Modeling
• Machine Learning
• +6 more

Ekaterina Gilman, D.Sc. (Tech), is a Researcher at the University of Oulu's Center for Ubiquitous Computing, Faculty of Information Technology and Electrical Engineering. She is supported by the Academy of Finland and has collaborated with Northern Finland Biobank Borealis and the Centre for Health and Technology. Her research spans Data Analytics Ubiquitous Computing Machine Learning Internet of Things Smart Environments with applications in intelligent urban environments, stream reasoning, and wireless communications. Recent publications highlight trends in Edge computing architectures Concept drift detection Social distancing monitoring Well-being measurement Smart city data challenges . She has participated in projects funded by the European Regional Development Fund, Business Finland, Academy of Finland, and EU Horizon 2020. She serves as a reviewer and organizer in scientific communities and has over 30 publications.

Mehrad MahmoudianView profile

Researcher

• Machine Learning
• Statistical Data Analysis
• Survival Analysis
• +2 more

Mehrad Mahmoudian serves as a Doctoral Researcher in the Department of Computing and Project Researcher at the Institute of Biomedicine, University of Turku. He is affiliated with the Computational Biomedicine research group under Elo Lab, operating from Biocity 7th floor (Office 7096) at Tykistökatu 6, Turku. His research spans Machine Learning , Statistical Data Analysis , and Survival Analysis applied to biomedical challenges. Key focus areas include cancer genomics, reproductive health disorders, microbiome analysis, and clinical risk prediction. His methodological innovations address high-dimensional biological data through algorithm development for feature selection, epigenomic analysis, and predictive modeling. Analysis of his publications reveals a consistent trajectory in developing computational tools for biomedical data interpretation. His work bridges molecular biology (epigenetics, transcriptomics) with clinical applications (cancer prognosis, pregnancy disorders, cardiovascular risk), emphasizing robust statistical frameworks and machine learning pipelines for translational research. As a core member of the Computational Biomedicine group, he contributes to collaborative projects involving multi-omics integration, clinical decision support systems, and biomarker discovery. His technical expertise spans proteomics, metaproteomics, and genomic data analysis pipelines, with significant contributions to open-source computational methods like ROTS for differential peak detection.

• Inverse Problems
• Tomography
• Medical Imaging
• +2 more

Alexander Meaney is a Postdoctoral Researcher in the Department of Mathematics and Statistics at the University of Helsinki, Finland. His research centers on inverse problems with applications spanning medical imaging, tomography, and interdisciplinary biological studies. His core research interests include inverse problems, tomography, and computational mathematics, with specific focus on CT reconstruction algorithms, radiation dose reduction, and dynamic imaging techniques. Meaney develops mathematical models for multi-spectral and low-dose CT systems while addressing practical challenges in mammography quality control and plant development imaging. His methodological work emphasizes directional total variation regularization and synergistic reconstruction approaches. Analysis of Meaney's publications reveals a consistent trajectory in advancing tomographic reconstruction methods, particularly through challenge-based frameworks like the Helsinki Tomography Challenge. His work bridges theoretical mathematics with clinical and biological applications, showing increasing emphasis on multi-energy systems and real-world implementation. Key trends include the integration of machine learning in reconstruction pipelines and cross-disciplinary dataset development for benchmarking. Meaney actively participates in Academy of Finland-funded projects, notably the Centre of Excellence of Inverse Modelling and Imaging (2023-2025) and its predecessor (2018-2025), where he collaborates on grant-supported research in inverse modeling. These projects involve substantial computational resources and international partnerships. His collaborative network includes the Inverse Problems group at Helsinki, with documented academic visits to institutions like CWI Amsterdam. Meaney contributes to open science through publicly available datasets on Zenodo for dynamic X-ray tomography, supporting reproducibility in imaging research.

• Software Engineering
• Cybersecurity
• Machine Learning
• +7 more

Adnan Ashraf serves as a Senior University Lecturer at the Department of Information Technology within the Faculty of Science and Engineering at Åbo Akademi University, Finland. His academic profile spans software engineering, cybersecurity, and applied artificial intelligence with emphasis on maritime systems and drone technologies, supported by extensive EU and national research funding. His research portfolio demonstrates deep expertise in: Security frameworks for DevOps and IoT networks Machine learning applications in performance testing Edge computing optimization for resource-constrained environments Swarm robotics navigation and collision avoidance Systematic literature reviews in emerging software domains Analysis of his 46+ publications (2010-2024) reveals consistent focus on bridging theoretical models with practical implementations. Key trends include security enhancement through SDN controllers, reinforcement learning for UAV path planning, and systematic reviews of API documentation practices. His work consistently addresses real-world challenges in critical infrastructure domains with strong empirical validation. Dr. Ashraf has secured significant research funding including EU Horizon 2020 VeriDevOps (as Principal Investigator) and MegaM@Rt2 projects (as Co-Investigator), demonstrating leadership in collaborative research addressing DevOps security and runtime modeling challenges. While specific student supervision details aren't publicly enumerated, his project leadership indicates active mentorship in software engineering research.

• Directed Energy Deposition
• Additive Manufacturing
• Aluminum Alloy
• +5 more

Reza Asadi is a Researcher in the Doctoral Programme in Engineering Sciences , focusing on automation technology and mechanical engineering. His research spans advanced manufacturing techniques, particularly directed energy deposition (DED) and additive manufacturing. Research Interests include directed energy deposition, neural networks, aluminum alloy processing, and thin-walled structures. He employs machine learning (e.g., CNNs) and signal processing techniques (e.g., wavelet transforms) to optimize manufacturing processes like laser-wire DED and milling. Recent Publications highlight deep learning for melt pool analysis, IoT systems in DED, and predictive modeling of bead geometries. Collaborations involve institutions in Finland and Europe, with key contributions to DED process monitoring and material sensitivity studies.