جستجوی استاد راهنمای دانشگاهی

Hamid Darabiمشاهده پروفایل

پژوهشگر

• Geosciences
• Environmental sciences
• GIS
• +۱ مورد دیگر

Hamid Darabi is a Postdoctoral Researcher at the Department of Geosciences and Geography within the Faculty of Science at the University of Helsinki. His research spans multiple environmental and geospatial disciplines, with a focus on applying advanced computational methods to analyze environmental systems and dynamics. He maintains an active research profile with several publications appearing in 2024 and 2025 in high-impact environmental science journals. Dr. Darabi's research interests center on the application of geospatial technologies to pressing environmental challenges. His work integrates remote sensing , GIS , and machine learning approaches to address complex environmental phenomena. Key research themes include climate change impacts on mountain ecosystems, drought susceptibility mapping, vegetation dynamics monitoring, wildfire effects on specific habitats, and water resource management challenges. His methodological expertise spans both traditional geospatial analysis and cutting-edge deep learning applications for environmental data. Analysis of Darabi's recent publication record (2024-2025) reveals a strong interdisciplinary approach combining environmental science with computational methods . His work demonstrates increasing sophistication in applying artificial intelligence to environmental challenges, particularly in drought susceptibility mapping and vegetation trend analysis. The research consistently addresses real-world environmental management issues while advancing methodological approaches in geospatial analysis. His collaborations span multiple international institutions, reflecting the global relevance of his research topics.

• Sustainable Development
• Virtual Reality Applications
• Charitable Giving Behavior
• +۷ مورد دیگر

Ilia Gugenishvili is a Senior Lecturer at the School of Business and Economics , Åbo Akademi University. His work bridges Sustainable Development Goals (SDGs) with Virtual Reality (VR) , charitable giving , and managerial innovation , focusing on behavioral and sustainability challenges in business contexts. Research Interests : Nudge theory, VR applications in fashion/consumption, burnout management, multicultural business dynamics, and SDG integration in higher education. Key Awards : Recipient of the 2024 Best Voluntary Sector Review Article Prize , Researcher of the Year , and Fil Roses to ÅAU Staff for academic excellence. Collaborative Impact : Active in conferences spanning sustainable consumption, AI forecasting, and nonprofit communication. Notable co-authored works include studies on Ukrainian displacement resilience and metaverse identity.

Johan Bobackaمشاهده پروفایل

استاد

• Electroanalytical Chemistry
• Electrochemical Sensors
• Solid-Contact Ion-Selective Electrodes
• +۵ مورد دیگر

Johan Bobacka is a Professor of Analytical Chemistry at the Laboratory of Molecular Science and Engineering, Åbo Akademi University . His research focuses on electroanalytical chemistry , electrochemical sensors , and sustainable technologies , including solid-contact ion-selective electrodes , Na-ion batteries , and machine learning-assisted chemical analysis . Co-founder and senior scientific advisor of GlucoModicum Oy (non-invasive glucose monitoring) Editor of Sensors & Actuators: B. Chemical and advisory board member for multiple journals Chairman of the Johan Gadolin Process Chemistry Center (Åbo Akademi) Supervised 15 doctoral and 52 MSc theses 185 peer-reviewed publications (H-index 46) His recent publications emphasize sustainable materials (e.g., lignin-based carbon, graphene composites) and smart sensor design (machine learning integration, coulometric transduction). Awards include the 2001 Finnish Chemical Industry Innovation Prize for conducting polymer applications. Activities involve hosting international researchers and advancing SDG-aligned technologies.

• Control Systems Engineering
• Marine Energy Systems
• Process Optimization
• +۵ مورد دیگر

Jari Böling is a University researcher at Åbo Akademi University, affiliated with the Faculty of Natural Sciences and Engineering in the Department of Process and Systems Engineering. His research focuses on developing technologies for a sustainable future, particularly in marine engineering and control systems with strong connections to UN Sustainable Development Goals. Böling's research expertise spans multiple engineering domains with specialized focus areas including: Distributed control and fault-tolerant control systems Marine energy systems and cruise ship optimization Process engineering applications for sustainability Machine learning integration in industrial control systems Complex system optimization techniques Analysis of Böling's publication trends reveals a strategic evolution from theoretical control systems toward applied sustainable technologies. His recent work demonstrates increasing integration of data analytics and machine learning with traditional control engineering to address environmental challenges in marine transportation. The research shows a clear progression toward practical implementations that reduce energy consumption and emissions in cruise ship operations and other marine applications. Böling actively supervises students, having guided 12 bachelor's theses in energy technology in 2020. His research portfolio includes significant projects funded by Business Finland: DAZE: Data Analytics for Zero Emission Marine (2023-2026) as Co-Principal Investigator INDECS: Integration of design and operation of cruise ship energy systems (2023-2025) as Responsible researcher CASEMATE: Computationally aided systems engineering for marine technology (2022-2025) as Principal researcher CPT: CLEAN PROPULSION TECHNOLOGIES (2021-2023) as Co-Investigator Energy technology development project in Vaasa (2011-2017) as Co-Investigator

Käthe Dahlströmمشاهده پروفایل

مدرس ارشد

• Structural Bioinformatics
• Protein Structure-Function Relationship
• Notch Signaling Pathway
• +۵ مورد دیگر

Käthe Dahlström is a Senior Lecturer in the Department of Biochemistry and Cell Biology at Åbo Akademi University's Faculty of Natural Sciences and Engineering. She is affiliated with the InFLAMES flagship (Innovation Ecosystem based on the Immune System) focusing on solutions for health. Her academic work centers on structural biology and bioinformatics approaches to understanding protein structure-function relationships. Dr. Dahlström's research primarily focuses on structural bioinformatics , with particular emphasis on protein 3D structure determination using both computational modeling and crystallographic methods. Her work explores the structural basis for ligand specificities, especially for proteins relevant to human health and disease. Key research areas include Notch signaling pathway components, copper-containing amine oxidases, and molecular recognition mechanisms. Analysis of her publication history shows a consistent research trajectory in structural biology with applications in cancer biology, enzymology, and drug design. Her recent work has increasingly incorporated machine learning approaches for protein structure prediction, reflecting current trends in computational structural biology. She has established productive collaborations, particularly with researcher T.A. Salminen, resulting in multiple high-impact publications. Dr. Dahlström is an active member of the Structural Bioinformatics Laboratory (SBL) where she contributes to advancing methodologies for protein structure determination and analysis. Her research has practical implications for understanding disease mechanisms and developing targeted therapeutic approaches.

Jetro Tuulariمشاهده پروفایل

دانشیار

• Neuroscience
• Brain development
• Neuroimaging
• +۱۲ مورد دیگر

Jetro Tuulari is an Associate Professor and Docent in the Department of Clinical Medicine at the University of Turku, where he also serves as Research Manager in Clinical Neurosciences and Doctoral Researcher in the Department of Computing. He is the Principal Investigator of the FinnBrain Neuroimaging Lab and Head of Neuroimaging at the InterLearn Centre of Excellence. He is affiliated with the Centre for Eudaimonia and Human Flourishing at the University of Oxford and part of the international Lifespan consortium developing human brain growth charts. His research focuses on how early life exposures, genetics, and environmental factors shape brain structure and function, influencing long-term health and wellbeing. Using advanced neuroimaging techniques such as MRI, fMRI, dMRI, PET, and EEG, his team investigates developmental cognitive neuroscience, with emphasis on maternal health, childhood adversity, obesity, and intergenerational effects. His work bridges clinical medicine, computing, and population neuroscience, contributing to large-scale cohort studies like FinnBrain, ABCD, and the Developing Human Connectome Project. His recent publications (2024–2025) reflect a strong trend in population neuroscience, neonatal brain development, epigenetics, and methodological innovation in neuroimaging. Key themes include maternal BMI and brain development, prenatal stress and child outcomes, transgenerational epigenetic inheritance, and AI-driven analysis of neuroimaging data in conditions like Long COVID. Finnish Medical Foundation Emil Aaltonen Foundation Sigrid Juselius Foundation Signe and Ane Gyllenberg Foundation Hospital District of Southwest Finland State Research Grants Alfred Kordelin Foundation Juho Vainio Foundation Orion Research Foundation He supervises a vibrant research team of post-doctoral fellows, doctoral students, and undergraduates within the FinnBrain Neuroimaging Lab. He has played a key role in launching the Human Neuroscience Master’s Programme at the Turku Brain and Mind Center and coordinates courses on neuroimaging methods. His international collaborations include researchers at Oxford, Cambridge, KCL, Charité – Universitätsmedizin Berlin, and the University of California, Irvine. He leads the FinnBrain Neuroimaging Lab, which conducts multimodal neuroimaging analyses within the FinnBrain Birth Cohort. The lab is part of broader initiatives like InterLearn and the Lifespan consortium, focusing on synergistic data analysis, brain network modelling, and population-level neuroscience.

• Oncology
• Pharmacology
• Computational Biology
• +۳ مورد دیگر

Olli Yli-Harja is a Professor in Biomedicine at Tampere University. His research spans oncology, pharmacology, and computational biology, with a focus on glioblastoma treatment and machine learning applications in biomedical contexts. Doctor of Science (Technology), Lappeenranta University of Technology (1989) Master of Science (Technology) in Automation Engineering, Lappeenranta University of Technology (1985) His work intersects biomedicine and computational methods , targeting cancer therapies and dynamical systems modeling. Recent studies include adenosine receptor antagonists for glioblastoma and DNA methylation analysis in pediatric tumors. Publications highlight trends in scientific machine learning , adenosine pharmacology , and epigenetic tumor mechanisms . Collaborations span pharmacology, genetics, and AI-driven biomedical research. Activities include conference presentations, editorial board roles, and media appearances discussing cancer treatment innovations.

• High-Temperature Corrosion
• Biomass Combustion
• Waste-to-Energy Processes
• +۳ مورد دیگر

Emil Vainio is a Research Fellow at the Faculty of Science and Engineering, Åbo Akademi University. His work focuses on high-temperature corrosion, biomass combustion, and sustainable energy technologies, contributing to the UN Sustainable Development Goals related to clean energy and environmental sustainability. University: Åbo Akademi University School: Faculty of Science and Engineering Rank: Research Fellow His research explores corrosion mechanisms in energy systems, particularly in biomass and waste combustion, emphasizing the role of alkali chlorides, sulfuric acid, and hygroscopic salts. He develops innovative monitoring techniques (e.g., linear polarization resistance) and investigates chemical looping combustion and NOx emission reduction. Recent publications (2022–2025) highlight his expertise in calcium chloride behavior, ammonium chloride corrosion, and sustainable extraction of critical metals from e-waste. His work bridges experimental studies with thermodynamic modeling, addressing both industrial and environmental challenges. Projects like GLCE (Greener and Low-Carbon Extraction) involve collaborations across institutions, focusing on e-waste recycling and energy recovery. While no specific scientific awards are listed, his contributions to combustion technologies and material science are evident in peer-reviewed articles and conference participation.

• Cyber Physical Systems
• Generative Models
• Adaptive Testing
• +۵ مورد دیگر

Jarkko Peltomäki is a researcher in the Faculty of Science and Engineering, Department of Information Technology, specializing in cyber-physical systems verification and testing. His work focuses on developing advanced falsification techniques using generative models and adaptive testing strategies. His primary research interests include: Cyber Physical Systems (100% fingerprint weight) Generative Models and GANs (33%) Adaptive Testing methodologies (33%) Falsification algorithms (33%) Tool Competitions like ARCH-COMP (33%) Requirements Engineering for complex systems (33%) Unmanned Aerial Vehicle validation (33%) Multi-arm Bandit optimization (33%) Analysis of his 2022-2025 publications reveals increasing integration of generative adversarial networks (GANs) into cyber-physical system testing, with significant contributions to the ARCH-COMP benchmarking framework. His work demonstrates a clear evolution from traditional falsification methods toward adaptive, model-driven approaches that leverage machine learning for test generation and coverage optimization, particularly in UAV and hybrid system contexts. Scientific awards: None documented in provided sources. Grant activity includes participation as Co-Investigator in the European Commission-funded ADOaRT project (2021-2024), focusing on adaptive testing for cyber-physical systems. No student advising information is available. His research outputs include multiple datasets (OGAN/WOGAN Experimental Results) supporting reproducibility in falsification studies. He actively contributes to the ARCH-COMP international research network, coordinating falsification category evaluations and developing standardized validation methodologies for hybrid system verification tools.

Tiina A. Salminenمشاهده پروفایل

استاد

• Structural Bioinformatics
• Protein Structure and Function
• Infection and Inflammation Mechanisms
• +۳ مورد دیگر

Tiina A. Salminen is a Professor at the Department of Biochemistry and Cell Biology, Faculty of Natural Sciences and Engineering, Åbo Akademi University. Her research integrates structural bioinformatics and experimental approaches to study protein 3D structures, focusing on molecular mechanisms in infection, inflammation, and cancer. She combines crystallography with computational modeling to explore protein-ligand interactions, drug targets, and diagnostic markers. Research Interests: Structural bioinformatics, protein function prediction, molecular mechanisms of disease, computational modeling. Projects: Leads initiatives like Biocenter Finland (2024–2028) and TuProtCore (2023–2025), supported by the Finnish Academy. Key Collaborations: Works with researchers across Finland on structural biology and translational medicine. Publication Trends: Recent work includes ML-based protein structure prediction, PET imaging for inflammation, and cyanobacterial metabolism studies. Her articles span biochemistry, structural biology, and biomedical applications, emphasizing drug design and disease biomarkers. Laboratory: Head of the Structural Bioinformatics Laboratory (SBL), Åbo Akademi University, advancing integrated structural biology infrastructure.

• Crisis Communication
• Information Overload
• Situational Awareness
• +۴ مورد دیگر

Joachim Högväg is a Researcher at Åbo Akademi University's Faculty of Humanities and Social Sciences, affiliated with the Experience Lab Solutions for health. His work bridges cognitive science and practical applications in crisis management, virtual reality, and democratic innovation, utilizing biometric data and user-centered design methodologies. His research focuses on information processing under stress , particularly examining situational awareness during crises and information overload in emergency contexts. Högväg investigates how visual attention mechanisms affect decision-making, as evidenced by his VR-based forensic psychology studies and analysis of crisis communication during the COVID-19 pandemic. His work extends to digital democratic tools , where he develops accessible applications for citizen engagement in local politics through user experience optimization. Recent publications reveal an interdisciplinary trajectory combining cognitive science, human-computer interaction, and political communication. His studies increasingly incorporate biometric measurements and virtual reality environments to simulate real-world crisis scenarios, while maintaining strong connections to practical societal applications in healthcare and governance. Högväg actively contributes to externally funded research as Co-Investigator on projects including INTAKT (reducing academic intention-action gaps among Finnish-Swedish students), VRwitness (eyewitness research in VR), and Pocket Democracy (local politics engagement tools). These projects receive support from foundations like the Swedish Cultural Foundation and Swedish-Ostrobothnian community. He operates within the Experience Lab Solutions for health framework and maintains collaborative networks across disciplines, evidenced by multi-institutional projects addressing societal challenges through technological innovation. His upcoming June 2025 conference presentation on VR forensic applications demonstrates ongoing research momentum.

• Artificial Intelligence
• Machine Learning
• E-commerce Platforms
• +۷ مورد دیگر

Jozsef Mezei is a Professor at the School of Business and Economics, Faculty of Social Sciences, Economics and Law, at Åbo Akademi University. His research lies at the intersection of artificial intelligence, information systems, and business analytics, with a strong focus on customer satisfaction, sentiment analysis, and e-commerce platforms. His research interests include Artificial Intelligence , Machine Learning , Large Language Models , Customer Review Analysis , Fuzzy Logic , and Configurational Methods in digital business environments. He applies computational intelligence techniques to understand user behavior, trust, and satisfaction in online platforms. The most recent publications highlight a strong trend toward integrating Large Language Models with traditional data analysis frameworks like CRISP-DM and qualitative comparative analysis (QCA), as well as continued innovation in fuzzy systems for sentiment and decision modeling. His work bridges technical AI methods with practical business applications, especially in e-commerce and digital health. He has contributed to research recognized under the UN Sustainable Development Goals, particularly in digital innovation and inclusive economic growth. While no specific scientific awards are listed, his work has been published in high-impact journals and top-tier conferences such as HICSS and Bled eConference. Jozsef Mezei supervises academic work, with at least two supervised projects documented. His research is supported by active collaboration networks across Europe, particularly in Finland and neighboring countries. He has developed frameworks combining sentiment analysis with fuzzy logic, applied to areas like mobile banking, recommendation systems, and customer feedback integration. He is affiliated with research in digital health usage, exploring how information systems facilitate healthcare innovation. His lab or research group appears to focus on intelligent systems for business decision-making, though no explicit lab name is provided. Future work is likely to further explore generative AI, trust modeling, and hybrid AI systems in digital platforms.

• Data Ownership
• Aspect-Based Sentiment Analysis
• Internet of Things (IoT)
• +۳ مورد دیگر

Ville Harkke is a Senior Lecturer at the School of Business and Economics, Åbo Akademi University. His work bridges computational linguistics and business informatics, with a focus on data ownership, sentiment analysis, and IoT applications in decision-making systems. Research Themes: Data Ownership, Aspect-Based Sentiment Analysis, IoT Systems Institutional Affiliation: School of Business and Economics, Åbo Akademi University Contact: ville.harkke@abo.fi Research Interests revolve around Technical and ethical aspects of IoT data management Natural Language Processing (NLP) for social media sentiment extraction Business informatics frameworks for digital transformation His work integrates Machine Learning with domain-specific challenges in urban analysis and data governance. Scientific Output shows a consistent focus on IoT ecosystems and sentiment analysis, with recent advancements in RoBERTa-based models for Finnish neighborhood studies. His 2024 publication on Suomi24 data demonstrates cutting-edge applications of NLP in sociocultural contexts.

• Artificial Intelligence
• Data Forecasting
• Predictive Analytics
• +۳ مورد دیگر

Dumitru Iulian Năstac is an academic faculty member specializing in Information Technology. On 29 Apr 2024, he hosted an international academic visitor from POLITEHNICA University of Bucharest (Romania) for an activity focused on adaptive data forecasting using artificial intelligence.

Mika Murtojärviمشاهده پروفایل

دانشگاهی

• Algorithms
• Programming
• Machine Learning
• +۸ مورد دیگر

Mika Murtojärvi is a Senior Researcher and University Teacher in Software Engineering at the University of Turku. His work bridges research and education in computer science, with a focus on algorithms, machine learning, and software systems. He holds a PhD in Computer Science (2016) and has over a decade of teaching experience. Research Interests: His research spans algorithm development for applications in computational geometry, biomedical informatics, e-learning, and parallel computing. Key areas include survival prediction in cancer, EEG-based neurological classification, GPU-accelerated geographic algorithms, and platform-independent educational tools. His work often integrates real-world data with machine learning and optimization techniques. The recent publications highlight a strong trend in applying algorithmic and machine learning methods to healthcare and environmental challenges. Topics such as survival prediction in prostate cancer, EEG-based Parkinson’s classification, and GPU-optimized coastal algorithms reflect interdisciplinary research at the intersection of computer science, medicine, and geosciences. The use of R packages and e-learning systems also shows a commitment to practical, software-based solutions. Scientific Awards: No awards mentioned in the text. Advising and Grants: Mika supervises BSc theses and has taught various core computer science courses. While specific grants are not listed, his research in biomedical and environmental computing suggests involvement in funded projects. He has contributed to tools like ePCR, indicating software development for research dissemination. Labs and Teams: He collaborates with researchers such as Antti Airola, Tapio Pahikkala, and Jari Björne, suggesting active participation in research teams focused on machine learning and biomedical informatics. His work on GPU algorithms also indicates ties to high-performance computing groups.