جست‌وجوی استاد و پژوهشگر

• Materials Physics
• Nanoscience
• Radiation Damage
• +۳ مورد دیگر

Aslak Joutsi Johannes Fellman is a Doctoral Researcher in Materials Physics at the University of Helsinki, affiliated with the Doctoral Programme in Materials Research and Nanosciences. His work focuses on computational materials science, particularly radiation damage in nuclear materials like tungsten and iron. Active participant in the INNUMAT project (European Commission, 2022–2026) Recipient of Kulturfonden grants (2023–2024) Research interests span multiscale modeling, radiation-induced defect formation, and machine learning applications in materials science. Recent publications emphasize molecular dynamics simulations of radiation damage mechanisms in ferromagnetic and liquid iron, as well as tungsten under cascade overlap with voids and vacancy clusters. His scholarly output includes three peer-reviewed articles since 2019, with contributions to Journal of Physics: Condensed Matter and Journal of Nuclear Materials . Collaborations involve researchers from Finland, Sweden, and international institutions, utilizing computational methods to advance understanding of material behavior under extreme conditions.

Nahid Atashiمشاهده پروفایل

پژوهشگر

• Geosciences
• Environmental sciences
• Urban meteorology modeling
• +۳ مورد دیگر

Nahid Atashi is a Postdoctoral Researcher at the University of Helsinki, affiliated with the Faculty of Science. She holds positions in the Institute for Atmospheric and Earth System Research (INAR) and the Helsinki Institute of Sustainability Science (HELSUS). Her work is centered within the Air Quality Research Group. She holds a Ph.D. (details unspecified) and has conducted research in Jordan, Iran, Kenya, and other regions. Research Interests : Atashi specializes in geosciences and environmental sciences with a focus on urban meteorology modeling, climatology, and atmospheric science. Her core research areas include dew formation dynamics, particulate matter analysis, and climate change impacts. She employs advanced modeling techniques to study hydrological processes in arid zones and urban air quality. Publications Trends : Her research spans interdisciplinary topics such as dew formation modeling in Jordan/Iran/Kenya, particulate matter studies in Middle Eastern cities, and climate change linkages. Her 2020-2024 work emphasizes machine learning applications in transportation systems and climate-driven drought analysis. Notable contributions include dew formation zone delineation using cluster analysis and regional climate modeling. Awards : No scientific awards explicitly mentioned in available records. Grants & Advising : No grant information or student advisement records provided. Her research collaborations include institutions in Jordan, Kenya, and Iran. Labs/Teams : Active member of the Air Quality Research Group within INAR, contributing to sustainability-focused projects at HELSUS.

Jussi Tohkaمشاهده پروفایل

استاد

• Biomedical Image Analysis
• Machine Learning
• Neuroinformatics
• +۳ مورد دیگر

Jussi Tohka is a Professor at the University of Eastern Finland (UEF) in the Faculty of Health Sciences, affiliated with the A.I. Virtanen Institute for Molecular Sciences. His primary role is in Biomedical Image Analysis, focusing on machine learning applications in neuroimaging, signal processing, and medical data analysis. Key research interests include predictive modeling for neurodegenerative diseases, MRI harmonization, and advanced image segmentation techniques. Academic Position: Professor of Biomedical Image Analysis Affiliations: UEF Brain Research Unit, Kuopio Biomedical Image Analysis Center (KUBIAC) Projects: Neuro-Innovation, Enhancing Innovation Potential via Biomedical Image Analysis His research combines computational methods with clinical applications, addressing challenges in epilepsy biomarkers, traumatic brain injury, and Alzheimer’s disease progression. Notable contributions include developing tools for data harmonization across multisite studies and optimizing neural network architectures for medical image analysis. Publications span topics like deep learning for dendrite segmentation, predictive modeling of amyloid positivity, and MRI-based assessments of brain microstructure. His work bridges fundamental neuroscience with translational medical imaging solutions.

Narayan Puthanmadam Subramaniyamمشاهده پروفایل

استاد مهمان

• Neuroscience
• Biomedical Engineering
• Machine Learning
• +۵ مورد دیگر

Narayan Puthanmadam Subramaniyam is a Visiting Professor at the Department of Neuroscience and Biomedical Engineering, Tampere University of Technology. His research focuses on biomedical signal processing and computational neuroscience, with a strong emphasis on integrating machine learning with neuroimaging techniques. Education: Tekniikan tohtori (Doctor of Science) in Medical Technology from Tampere University of Technology Active in neuroscience and biomedical engineering, Subramaniyam's work explores deep brain stimulation, EEG/MEG signal analysis, and emotion classification using spiking neural networks. His publications span topics like cortical parcellation, functional connectivity, and feature fusion of multimodal data. Research Trends: His recent studies combine machine learning with neurological signal processing, focusing on applications in Parkinson's disease, anesthesia monitoring, and emotion recognition. Key methods include clustering techniques, complexity metrics, and deep learning algorithms. Collaborations: Active in international collaborations, with network links in neuroscience and computer science domains. Publications: Contributions to journals like Scientific Reports , Sensors , and Journal of Neuroscience Methods , addressing challenges in signal processing and brain-inspired computing.

• 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.

Miriam Nokiaمشاهده پروفایل

استاد

• Behavioral Neuroscience
• Cognitive Neuroscience
• Memory Formation
• +۵ مورد دیگر

Miriam Nokia is a Professor at the Department of Psychology, University of Jyväskylä, specializing in the neural basis of learning and memory. Her research integrates electrophysiological measurements with behavioral analysis to explore hippocampal function, cardiorespiratory rhythm interactions, and the impact of physical fitness on cognitive performance. Research Focus : Hippocampal plasticity, memory consolidation, interoception, and neural dynamics during learning Projects : Brain-wide memory consolidation, sensory gating, cardiorespiratory learning synchrony Teaching : Cognitive neuroscience and neuropsychology courses Recent publications highlight her work on hippocampal theta oscillations, cardiorespiratory modulation of learning, and physiological correlates of engagement in digital environments. She collaborates with interdisciplinary teams using MEG/EEG, machine learning, and animal models to study memory reorganization during rest and sleep. Her lab investigates how intrinsic physiological rhythms (heart rate, breathing) interact with neural processes to regulate learning efficiency and memory stability across the lifespan.

• Materials Physics
• Radiation Damage
• Fusion Materials
• +۳ مورد دیگر

Fredric Granberg is an Associate Professor in the Department of Physics at the University of Helsinki, affiliated with the EUROFusion Advanced Computing Hub. He holds the title of Docent and supervises the Doctoral Programme in Materials Research and Nanosciences. His research focuses on radiation damage in fusion materials, computational materials science, and molecular dynamics simulations. Key projects include Kulturfonden-funded initiatives (2022–2024) exploring fusion materials and defect evolution in tungsten. Granberg’s work emphasizes atomistic-level studies of materials under extreme conditions, such as ion irradiation and high-energy particle interactions. He has collaborated internationally, including a visiting researcher stint at Oak Ridge National Laboratory (2016). His research spans defect kinetics modeling, machine-learned interatomic potentials, and plasma-wall interaction modeling for fusion reactors like EU-DEMO. Research Interests: Radiation damage mechanisms, tungsten materials behavior, OKMC simulations, defect evolution, and high-entropy alloys. Labs/Teams: EUROFusion Advanced Computing Hub, Department of Physics labs at University of Helsinki. His publications (62+ articles from 2014–2025) highlight advancements in computational modeling of defect production, sputtering mechanisms, and alloy stability. Recent studies include machine learning applications for interatomic potentials and experimental-computational synergy in vacancy distribution analysis.

• Neuroscience
• Medical Imaging
• Neurological Disorders
• +۷ مورد دیگر

Hanna Renvall is an Assistant Professor at the Department of Neuroscience and Biomedical Engineering, Aalto University. Her academic journey includes a Master's degree in Engineering and Technology from Helsinki University of Technology (2010) and a Ph.D. in Medical and Health Sciences from the University of Helsinki (2004). Her research interests span: Neuroscience Medical Imaging (MEG, fMRI) Neurological Disorders (Parkinson’s, dementia) Brain Network Analysis Evoked Potential Studies Signal Processing Algorithms Recent publications focus on artifact removal in MEG data, cortical beta rhythms during movement, and AI-driven dementia risk prediction. She also contributes to advancing non-invasive brain stimulation protocols and real-world neuroscience applications. Scientific activities include organizing the MEG Nord conference (2023), co-hosting TMS-EEG workshops, and leading projects like MoBI (mobile brain imaging for dementia risk). Her work bridges neurotechnology with clinical applications, emphasizing translational research.

Kai Nordlundمشاهده پروفایل

استاد

• Computational Materials Physics
• Radiation Effects in Materials
• Nanoscience
• +۳ مورد دیگر

Kai Nordlund is a Professor of Computational Materials Physics and Vice Rector at the University of Helsinki. He holds affiliations with the Helsinki Institute of Sustainability Science (HELSUS), Helsinki Institute of Urban and Regional Studies (Urbaria), and the EUROFusion Advanced Computing Hub Finland. His research focuses on radiation effects in materials, nanoscience, and computational modeling of defects in solids. Nordlund has led projects such as the MachQu initiative, advancing quantum mechanics-based material design, and contributed to the MATENA researcher community. His awards include the Magnus Ehrnrooth Prize (2007), Theodor Homen Prize (2014), and the Knight, First Class of the Order of the White Rose (2016). Nordlund has supervised numerous doctoral theses and actively participates in international conferences, workshops, and fusion research collaborations, including roles in EUROFusion and the ITER project. Key research areas include radiation damage in fusion materials, defect dynamics in metals, and the development of machine-learned interatomic potentials for large-scale simulations. His work bridges computational physics with experimental validation, addressing challenges in nuclear energy and materials science.

• Biopolymer Chemistry
• Biosystems Engineering
• Nanocellulose Applications
• +۳ مورد دیگر

Daria Robertson is a Doctoral Researcher at Aalto University, affiliated with the Bioproducts and Biosystems department. Her research focuses on biopolymer chemistry and engineering, particularly in nanocellulose-based materials, lignin applications, and carbonization processes. The most recent publications highlight her contributions to sustainable materials science, including self-extinguishing hybrid foams, 3D-printed lignin-cellulose composites, and carbon fiber fabrication. Her work spans additive manufacturing, electrochemical CO₂ reduction, and energy storage technologies. For collaborations or inquiries, contact her at daria.robertson@aalto.fi.

• Computational Chemistry
• Materials Science
• Nanotechnology
• +۳ مورد دیگر

Richard Jana is a Postdoctoral Researcher in the Department of Chemistry and Materials at Aalto University . His research focuses on computational materials science, particularly the modeling of nanoscale and amorphous materials using advanced simulation techniques. Research interests include: Computational modeling of nanomaterials Machine learning in materials discovery Structural and mechanical properties of amorphous solids Surface chemistry and hierarchical nanostructures Recent work highlights trends in combining machine learning with density functional theory , studying iron nanoparticles , amorphous carbon , and metallic glasses through simulations. He is affiliated with the DAS Group at Aalto University.

• Materials Science
• Computational Physics
• Radiation Damage
• +۵ مورد دیگر

Ali Hamedani is a Postdoctoral Researcher focusing on computational materials science and radiation damage analysis. He has contributed to multidisciplinary projects involving machine learning interatomic potentials and multiscale modeling of radiation-induced defects. Department of Applied Physics Nuclear Materials and Engineering His research spans Materials Science , Computational Physics , and Nuclear Engineering , with applications in: Radiation damage in semiconductors and ceramics Machine learning-driven molecular dynamics High-pressure material behavior Perovskite solar cell optimization Recent work highlights trends in silicon defect analysis , ZrC/ ZrN ceramics , and multi-objective optimization of energy materials. Publications emphasize cross-disciplinary approaches combining first-principles calculations with machine learning .

Ville Pulkkiمشاهده پروفایل

استاد

• Acoustics
• Signal processing
• Audio
• +۱ مورد دیگر

Ville Pulkki serves as a Professor in the Department of Information and Communications Engineering at Aalto University, Finland, maintaining active research output evidenced by publications extending into 2025. His professional contact details include email (ville.pulkki@aalto.fi) and phone (+358505208392), confirming current institutional affiliation. His research expertise spans: Acoustics (particularly underwater and room acoustics) Signal processing for spatial audio systems Audio codec development and compression Spatial sound perception and localization Analysis of his 15 most recent publications reveals dominant research trajectories: underwater bioacoustics applications using spatial audio and 360° video for marine ecosystem monitoring; advanced spatial post-filtering techniques addressing noise reduction and source separation in complex acoustic environments; perceptually-optimized codecs for higher-order ambisonics compression; and fundamental investigations into sound localization challenges including median plane perception and standing wave interference. His work consistently bridges theoretical signal processing with practical applications in virtual reality, marine biology, and auditory perception. No scientific awards, fellowships, or major prizes are documented in the provided materials. While the source text confirms Professor Pulkki's active research status through ongoing publications, it lacks specific details regarding graduate student supervision, research grants, or laboratory leadership. His extensive publication record across diverse spatial audio domains suggests significant collaborative research activity and potential involvement in funded projects, though concrete evidence of advising relationships or grant management is absent from the available information. Similarly, no dedicated research laboratories, departmental teams, or institutional research groups under his direct leadership are mentioned in the source material, despite the technical depth of his work requiring substantial experimental infrastructure.

• Catalysis
• Computational Chemistry
• Materials Science
• +۵ مورد دیگر

Karoliina Honkala is a Professor and Deputy Head of the Department of Chemistry at the University of Jyväskylä's Faculty of Mathematics and Natural Sciences. She leads research in the Physical Chemistry unit focusing on catalytic reaction mechanisms and materials design for sustainable energy applications. Her research investigates catalytic reaction selectivity, computational modeling of electrochemical systems, and sustainable material development. Key interests include: Design of efficient catalysts for biomass conversion and hydrogen production Computational methods for reaction mechanism analysis Nanoporous materials for environmental applications Sustainable resource recovery and urban mining Honkala's recent publications (2024-2025) demonstrate strong emphasis on DFT computational methods applied to catalytic systems, with recurring themes in sustainable chemistry, reaction optimization, and nanomaterial design. Her work frequently combines experimental validation with theoretical modeling. She leads several major research initiatives: HPC² project developing nanoporous materials for water splitting HyPER project mapping hydrogen storage materials MLNovCat consortium using machine learning for catalyst design

Ville Janssonمشاهده پروفایل

پژوهشگر

• Computational Materials Science
• Nuclear Materials
• Fusion Technology
• +۳ مورد دیگر

Ville Jansson is a researcher affiliated with the University of Helsinki, specializing in computational materials science and simulation techniques. He serves as a doctoral programme supervisor in the Doctoral Programme in Materials Research and Nanosciences and teaches Monte Carlo Simulations in Physics (5cr), a course offered every second year. Education Doctor of Philosophy in Theoretical Physics (University of Helsinki, 2014) Master of Science in Theoretical Physics (University of Helsinki, 2008) His research focuses on developing computational models for particle physics materials, nuclear materials, and fusion materials using Kinetic Monte Carlo (KMC) and Molecular Dynamics (MD) simulations. He is the primary developer of the open-source KMC code Kimocs , designed for simulating atomic-scale surface evolution. The Kimocs repository includes collaborations with researchers like Ekaterina Baibuz and Flyura Djurabekova. Articles from 2015–2022 highlight applications in Cu/Fe surface diffusion, nanotip formation, and high electric field effects, integrating machine learning for improved simulation accuracy. Recent research outputs involve collaborations with Jyri Kimari, Stefan Parviainen, and Andreas Kyritsakis. He has presented findings at academic events (2018–2020) and contributed to projects such as the Materials- and Nanophysics Researcher Community (MATENA) in 2011.