جست‌وجوی استاد و پژوهشگر

• Ecology
• Fungal Ecology
• Machine Learning Applications
• +۳ مورد دیگر

Niklas Moser is a Researcher at the Department of Biological and Environmental Science within the Faculty of Mathematics and Science at the University of Jyväskylä. He is actively affiliated with the Predictive Community Ecology Group, jointly led by Professors Nerea Abrego and Otso Ovaskainen. His research integrates computational methods with ecological field studies, focusing on fungal community dynamics and hybrid modeling frameworks. Key interests include: Plant-fungal associations along altitudinal gradients Wind-mediated dispersal mechanisms in mainland-island systems Development of process-informed neural networks for ecological prediction His work bridges theoretical ecology with machine learning innovation, emphasizing model interpretability and ecological process integration. Recent publications reveal strong trends in applying advanced statistical modeling to fungal biogeography and community assembly. His 2024-2025 work demonstrates increasing methodological sophistication, particularly in merging neural networks with ecological theory to address spatial and abiotic drivers of biodiversity patterns. Moser maintains active research collaborations across international teams, as evidenced by co-authorship with researchers from multiple institutions. His laboratory work centers on the Predictive Community Ecology Group's computational infrastructure for analyzing large-scale ecological datasets.

Matti Lassasمشاهده پروفایل

استاد

• Mathematics
• Inverse Problems
• Partial Differential Equations
• +۴ مورد دیگر

Matti Lassas is a Professor at the University of Helsinki within the Faculty of Science , specifically the Department of Mathematics and Statistics . His research focuses on Inverse Problems , Partial Differential Equations , and Geometric Analysis , with significant applications in Quantum Computing and Tomography . Selected Appointments ERC Centre of Excellence of Inverse Modelling and Imaging (2023-2028) Academy Professor (2019-2023) Research Trends: Recent publications analyze nonlinear inverse problems, geometric reconstruction in Finsler manifolds, quantum chaos bounds for manifolds, and neural operators for stable inversion. His work bridges mathematical theory with computational methods, including semi-algebraic neural networks. Scientific Awards Calderon Prize Professor E.J. Nyström Prize (2020) Vaisala Prize (2004) Supervision: He has supervised multiple doctoral theses, including those of Anna Suomenrinne-Nordvik, Salla Latva-Äijö, Antti Kujanpää, and Lauri Ylinen. His activities include organizing international conferences like Inverse Days and hosting visiting scholars such as Hiroshi Isozaki and Gabriel Paternain.

• Microbiology and virology
• Ecology, evolutionary biology
• Computer and information sciences
• +۳ مورد دیگر

Tommi Vatanen is an Associate Professor at the University of Helsinki, affiliated with the Helsinki Institute of Life Science (HiLIFE) and holding the Title of Docent in the Faculty of Medicine. As an Academy Research Fellow, he leads the Computational Microbial Ecology group and supervises doctoral candidates in the Doctoral Programme in Microbiology and Biotechnology. His research integrates microbiology, ecology, and computational science to investigate microbiome dynamics. Research interests span: Microbiome assembly : Early-life gut colonization, bacteriophage interactions, and mobile genetic elements Clinical applications : Fecal microbiota transplantation for obesity, diabetes, and neurodevelopmental conditions Computational approaches : Metagenomic analysis, AI-driven functional annotation, and resistance gene prediction His recent publications (15 most recent shown) demonstrate consistent focus on gut microbiome modulation across lifespans, with emphasis on clinical translation. Key thematic clusters include bacteriophage therapeutics, ethnic microbiome variations, and computational solutions for antimicrobial resistance. Awards and honors include: Web of Science Highly Cited Researcher (2020, 2021) Illumina Emerging Researcher Award (2019) University of Auckland Early Career Research Excellence Award (2021) Best PhD Thesis (2017) He leads multiple funded projects including Academy of Finland grants (2022-2027) and JDRF Australia collaborations (2023-2025) investigating bacteriophage roles in infant microbiome development. The Computational Microbial Ecology group employs multi-omics and clinical trial data to advance microbiome therapeutics.

• Computational Social Science
• Digital Democracy
• Human-Computer Interaction
• +۴ مورد دیگر

Matti Nelimarkka is a University Lecturer at the Centre for Social Data Science, University of Helsinki, where he leads the Helsinki Social Computing Group. He holds dual expertise with a PhD in Computer Science and a Master's in Political Science. His academic affiliations include membership in Helsinki Institute for Information Technology (HIIT) and visiting researcher status at Aalto University's Department of Computer Science. His research bridges computational methods and social theory, focusing on: Validity/reliability of computational social science Digital democracy and political participation systems Critical algorithm studies and power dynamics in technology Integration of HCI with political science (Political HCI) Machine learning applications in social research Recent publications (2024-2025) demonstrate strong focus on generative AI ethics, VR social interaction, digital governance, and public health machine learning models. Awards: Apps4Education (2015) Nokia Scholarship (2015) He actively supervises doctoral candidates in Social Sciences and Law programs and leads multiple grants including Academy of Finland projects on language technology infrastructure (FIN CLARIA) and digital lobbying. Current projects span through 2028. He co-founded Rajapinta (Finnish association for social science/IT research) and collaborates with industry partners like Futurice.

Heidi Jauhiainenمشاهده پروفایل

پژوهشگر

• Egyptology
• Comparative Religion
• Language technology
• +۲ مورد دیگر

Dr. Heidi Jauhiainen is a Postdoctoral Researcher at the Department of Languages, University of Helsinki, and member of the Centre of Excellence in Ancient Near Eastern Empires (ANEE). With a PhD in Egyptology and BSc in Computer Science, her work bridges ancient text analysis with digital humanities. University of Helsinki Department of Languages Centre of Excellence in Ancient Near Eastern Empires Her research focuses on: Digital epigraphy for Egyptian and Mesopotamian scripts Machine-readable ancient text creation Language technology for dead languages Quantitative analysis of religious texts Statistical dating of cuneiform documents Lexical networks in Akkadian and Egyptian Recent publications demonstrate technical and philological contributions to: Hieroglyphic text alignment algorithms Geospatial analysis of Greek-Egyptian texts Neo-Assyrian religious quantification Akkadian emotion mapping fastText embeddings for ancient languages She leads the MaReTE project and contributes to ANEE's digital infrastructure development, with presentations at ICE XIII and Rencontre Assyriologique Internationale.

Bilgehan Akdemirمشاهده پروفایل

پژوهشگر

• Distributed Machine Learning
• Edge Computing
• Federated Learning
• +۱ مورد دیگر

Bilgehan Akdemir is a Doctoral Researcher at the University of Oulu within the Faculty of Information Technology and Electrical Engineering . He is affiliated with the Centre for Wireless Communications - Networks and Systems (CWC-NS) and the Wireless Medical Communications (WiMeC) research group. Educational Background : M.Sc. in Communication Engineering from Yildiz Technical University, Istanbul, Turkey (2022). His research focuses on distributed machine learning algorithms and edge computing , particularly for digital healthcare applications. Current work involves deep learning-based medical imaging data processing across distributed local-edge and cloud computing environments. Key technical domains include machine learning , artificial intelligence , wireless communications engineering , and Internet of Things . Projects : TOMOHEAD, Eware-6G. Contact : Email: bilgehan.akdemir@oulu.fi | Address: Pentti Kaiteran katu, 1, P.O. Box 4500, 90014 Oulu, Finland.

Burak Turhanمشاهده پروفایل

استاد

• Software Engineering
• Artificial Intelligence
• Empirical Software Engineering
• +۲ مورد دیگر

Professor Burak Turhan is affiliated with the University of Oulu , where he serves in the Faculty of Information Technology and Electrical Engineering , specifically within the Department of Software Engineering . His research bridges Software Engineering and Artificial Intelligence , with a focus on empirical studies of software development challenges and applications in Digital Health . His work spans technical and human factors in software engineering, predictive modeling in emergency medicine, and pandemic-era software development adaptations. Key collaborations include the Australasian College for Emergency Medicine, Clinical Trials Network and University of Melbourne researchers. Publications address propeller acoustics, ambulance wait time prediction models, and remote work dynamics during the COVID-19 pandemic. Recent publications (sorted by year) demonstrate interdisciplinary expertise: 2025: Propeller noise patterns in forward flight 2024: Synchronized propeller acoustics 2022: Emergency medicine wait time modeling 2021: Ambulance patient wait time prediction 2020: Pandemic programming impacts

Ferdinando Hanyمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Machine Learning
• Signal Processing
• +۴ مورد دیگر

Ferdinando Hany serves as a Researcher in the Research Unit of Health Sciences and Technology within the Faculty of Medicine at the University of Oulu, specializing in the Medical, Imaging, and Physics Technology (MIPT) research group. His work bridges engineering and medical technology with a focus on real-world health applications. His academic foundation includes: M.Sc. in Electrical Engineering, University of Twente, Netherlands (2002) Hany's research expertise centers on artificial intelligence and machine learning applied to physiological signal interpretation, particularly electrocardiography (ECG) and photoplethysmography (PPG). He has pioneered methods for ultra-short-term ECG feature extraction and PPG pulse wave decomposition to assess arterial stiffness, alongside developing motion recognition systems using 3D accelerometer and gyroscope data through collaborations with Chinese research teams. His work directly contributes to wellbeing technology and non-invasive health monitoring solutions. No scientific awards or honors were documented in the source material. Research funding includes doctoral support from the Finnish Cultural Foundation (North-Ostrobothnia Regional Fund) during 2016-2017 and Academy of Finland grants for projects including BullStop—an initiative analyzing violence-related events through ECG classification. The text provides no indication of student supervision or grant management responsibilities. Hany operates within the MIPT research ecosystem at the University of Oulu, maintaining active international partnerships focused on sensor-based health technology development.

• Material Science
• Rheology
• Bio-based Foams
• +۷ مورد دیگر

Leevi Viitanen is a Visiting Faculty member at the Department of Applied Physics, Aalto University, affiliated with the Complex Systems and Materials research group. He holds a Doctor of Science (Tech.) in Technical Physics, awarded in 2022, and multiple Master’s and Bachelor’s degrees in Engineering and Technology from Aalto University. Doctor of Science (Tech.), Technical Physics – Aalto University (2022) Master’s Degree, Engineering and Technology – Aalto University (2017) Master’s Degree, Engineering and Technology – Aalto University (2017) Bachelor of Science (Tech.), Technical Physics – Aalto University (2016) His research focuses on sustainable material systems, particularly bio-based foams derived from cellulose and lignin. He investigates rheological behavior, yield stress, hydrophobicity, and microstructure dynamics in soft materials. His work integrates experimental physics with machine learning to predict foam yielding and optimize material performance. He is deeply involved in developing eco-friendly alternatives to plastics, contributing to UN Sustainable Development Goals. The most recent publications highlight a strong trend in utilizing lignin and cellulose for creating functional, scalable, and sustainable materials, with applications in energy storage, packaging, and green composites. His research bridges fundamental soft matter physics with industrial innovation. Leevi Viitanen has actively contributed to scientific discourse through conference presentations, including topics such as controlling foam yielding with vibrations and predicting local yielding using machine learning. He is also associated with Woamy, an award-winning Finnish startup commercializing bio foam technology, indicating impactful knowledge transfer and entrepreneurial engagement. His collaborative network includes prominent researchers like J. Koivisto and M. J. Alava. He has participated in media engagements discussing dynamics of low-density gels and advancements in cellulose foams for energy storage, reflecting public and industrial interest in his work. His research has been referenced in patents, underscoring its technological relevance. Leevi Viitanen is a key contributor to the advancement of sustainable materials through interdisciplinary research, combining physics, engineering, and environmental innovation.

• Rheology
• Creep
• Crack Propagation
• +۱۲ مورد دیگر

Juha Koivisto is a Research Fellow at the Department of Applied Physics, Aalto University, specializing in complex systems and materials. His work focuses on the mechanical behavior of materials such as foams, hydrogels, and alloys, with applications in sustainable construction and advanced manufacturing. Education: Doctoral degree in Engineering and Technology, Aalto University (awarded October 16, 2013) Master's degree in Engineering and Technology, Helsinki University of Technology (awarded September 18, 2007) Research Interests: His research spans rheology, creep, crack propagation, strain rate effects, and digital image correlation. He investigates the mechanical properties of bio-based materials, including foams and hydrogels, often integrating machine learning and computational modeling. His work contributes to sustainable development, particularly in green building materials and plastic alternatives. Recent Research Trends: His recent publications (2023–2025) reveal a strong focus on sustainable materials, including bio-based foams and coatings, rheological modeling with machine learning (e.g., Gaussian Process Regression), and open-source software development (pyRheo). He also explores smart, adaptive materials for 4D printing applications, demonstrating a blend of experimental physics and computational innovation. Scientific Awards: Advising and Grants: Juha Koivisto has supervised at least two theses, indicating his role in mentoring early-career researchers. He is the Principal Investigator of the EU-funded ARCHIBIOFOAM project (2024–2027), which focuses on digital design and robotic fabrication of biofoams for adaptive architecture. This project highlights his leadership in interdisciplinary, grant-funded research aimed at sustainable construction. Labs and Teams: He is part of the Complex Systems and Materials research group at Aalto University, collaborating with Prof. Mikko Alava and others. His team works on experimental and computational aspects of material failure, rheology, and smart material design, frequently using advanced techniques like digital image correlation and acoustic emission monitoring.

• Computational Electromagnetics
• Antenna Engineering
• Plasmonics
• +۲ مورد دیگر

Pasi Ylä-Oijala serves as a Staff Scientist in the Department of Electronics and Nanoengineering at Aalto University, Finland. His research expertise lies at the intersection of computational electromagnetics, antenna engineering, and plasmonics, with applications in next-generation wireless systems and nanophotonics. Educational background: Doctoral degree in Natural Sciences, University of Helsinki (1999) Licentiate degree in Natural Sciences, University of Helsinki (1998) Master's degree in Natural Sciences, University of Helsinki (1992) His primary research interests include computational methods for electromagnetic scattering, antenna design for 5G/6G communications, plasmonic nanostructures, and integral equation techniques. Ylä-Oijala has developed advanced numerical approaches for analyzing complex scatterers and antenna systems, contributing to both theoretical understanding and practical engineering solutions in wireless technology and optical materials. Recent publication trends show increasing integration of machine learning with electromagnetic simulations for antenna array optimization, alongside fundamental investigations into symmetry breaking phenomena in plasmonic systems. His work consistently bridges theoretical electromagnetics with real-world applications in mobile communications and nanoscale optics. No scientific awards were explicitly listed in the current profile. Ylä-Oijala has supervised 5 theses and secured participation in multiple major research grants, including: FORESAIL 3: Centre of Excellence in Research of Sustainable Space (Academy of Finland, 2023-2025) EHIR: Wireless impulse radio data link powered by energy harvesting (Academy of Finland, 2020-2023) FORESAIL2: Finnish Centre of Excellence in Research of Sustainable Space (Academy of Finland, 2020-2022) RFC Viikari: Antenna array development for mobile communications (Business Finland, 2019-2021) Finnish Centre of Excellence in Research of Sustainable Space (Academy of Finland, 2018-2021) He actively collaborates within Aalto University's Electromagnetics research group and maintains international partnerships, including recent work with Ecole Polytechnique Federale de Lausanne (EPFL). His research team focuses on advancing computational methods for electromagnetic problems while developing innovative antenna solutions for emerging communication technologies.

Santeri Rytkyمشاهده پروفایل

پژوهشگر

• Medical Physics
• Computed Tomography
• Machine Learning
• +۹ مورد دیگر

Santeri Rytky is a Doctoral Researcher at the Research Unit of Health Sciences and Technology , part of the Faculty of Medicine at the University of Oulu , Finland. He holds a Master of Science degree in Biophysics from the University of Oulu (June 18, 2019) and is currently completing his residency as a specializing medical physicist at Oulu University Hospital. Education : MSc in Biophysics (University of Oulu, Faculty of Science, 2019) Research Interests : Application of artificial intelligence to osteoarthritis imaging Medical physics and clinical diagnostics Computed tomography (CT) and bioimaging Machine learning in musculoskeletal disease detection Clinical Experience : Previously worked at Mikkeli Central Hospital (October 2021–February 2023) as a specializing medical physicist, integrating clinical insights into his research on diagnostic imaging technologies. Research Groups : Affiliated with the Diagnostics of Osteoarthritis (DIOS) research group and collaborates with experts in biomedical engineering, computer science, and clinical medicine.

Antti Isosaloمشاهده پروفایل

پژوهشگر

• Machine Learning
• Medical Image Analysis
• Computer Vision
• +۷ مورد دیگر

Antti Isosalo is a Postdoctoral Researcher at the Faculty of Information Technology and Electrical Engineering of the University of Oulu, Finland. He holds a Ph.D. in Medical Physics and Technology and a Master of Science (Tech.) in Information Engineering (Engineering Mathematics). Education: Ph.D. (Medical Physics and Technology), M.Sc. (Information Engineering) from University of Oulu Research interests: Deep learning Medical image analysis Pattern recognition Machine vision Breast cancer screening Distributed computing He is affiliated with the Wireless Medical Communications (WiMeC) and Medical Imaging in Diagnostics, Algorithms and Software (MIDAS) research groups. His current work focuses on AI applications in medical imaging, particularly through projects like TOMOHEAD and Tech2Heal.

Simo Saarakkalaمشاهده پروفایل

استاد

• Osteoarthritis
• Musculoskeletal Imaging
• Biomechanics
• +۴ مورد دیگر

Simo Saarakkala is Professor of Biomedical Engineering and Head of the Research Unit of Health Sciences and Technology at the University of Oulu's Faculty of Medicine. He also serves as Scientific Director of Infotech Oulu Focus Institute, with research centered on osteoarthritis diagnostics and imaging across tissue, cellular, and clinical levels. His work focuses on: Understanding osteoarthritis etiology and progression mechanisms Developing early diagnostic methodologies for pre-symptomatic detection Integrating machine learning and computer vision in musculoskeletal imaging Translating biomechanical research into clinical applications Prof. Saarakkala leads the DIOS (Diagnostics of Osteoarthritis) research group comprising multidisciplinary scientists and engineers. His grant portfolio includes prestigious European Research Council funding with active projects spanning tissue-level analysis to clinical implementation. Professional recognition includes: ERC Starting Grant (2014-2018) for pioneering osteoarthritis imaging research ERC Proof of Concept Grant (2020-2021) for clinical translation of diagnostic tools

Leran Luمشاهده پروفایل

پژوهشگر

• Density functional theory
• 2D materials
• CO2 reduction
• +۲ مورد دیگر

Leran Lu is a Doctoral Researcher at the Nano and Molecular Systems Research Unit within the Faculty of Science at the University of Oulu. Their work focuses on computational chemistry and machine learning applications for studying 2D materials and CO2 reduction processes. University of Oulu, Faculty of Science Nano and Molecular Systems Research Unit Research Interests: Density functional theory 2D materials CO2 reduction Machine learning Computational chemistry Contact: Leran.Lu@oulu.fi