جست‌وجوی استاد و پژوهشگر

Anette Hallمشاهده پروفایل

پژوهشگر

• Neurodegenerative Diseases
• Alzheimer's Disease
• Frontotemporal Dementia
• +۴ مورد دیگر

Anette Hall is a Senior Researcher at the Institute of Clinical Medicine , School of Medicine, University of Eastern Finland. She holds a D.Sc. (Tech.) and M.Sc. (Tech.) in Technical Physics (Computational Biophysics) from Tampere University of Technology, and has been actively involved in neurodegenerative disease research since 2011. Education: D.Sc. (Tech.) - Tampere University of Technology M.Sc. (Tech.) - Tampere University of Technology Research Focus: Specializing in machine learning applications for Alzheimer's disease and frontotemporal dementia diagnostics, with emphasis on metabolomics , CSF biomarkers , and disease progression modeling . Publications: 15+ peer-reviewed articles between 2013-2025 focusing on dementia prediction models , amyloid pathology , and metabolic profiling in neurodegenerative contexts. Collaborations: Participates in European Union Horizon 2020 initiatives, Alzheimer’s Disease Neuroimaging Initiative, and AddNeuroMed consortium. Her work develops disease state fingerprint tools and web-based cognitive testing platforms for early detection of neurodegenerative disorders, particularly Alzheimer's and frontotemporal lobar degeneration.

• Pharmaceutical Chemistry
• Tablet Manufacturing
• Powder Flow Analysis
• +۳ مورد دیگر

Osmo Antikainen is a University researcher and visiting researcher at the Division of Pharmaceutical Chemistry and Technology, Faculty of Pharmacy, University of Helsinki. He serves as a Supervisor in the Doctoral Programme in Drug Research. His research focuses on pharmaceutical chemistry and technology, particularly tablet manufacturing, powder flow properties, and AI-driven quality control. Recent work includes AI frameworks for tablet compression and image-based analysis of powder dynamics. Antikainen has supervised doctoral theses on topics like pharmaceutical powder behavior and formulation stability. He collaborates with organizations such as Care4living Oy, DAIN Studios Oy, and Business Finland on projects like NIR-Based PAT Applications and LifeFactFuture . His publications (65 total) and projects (3 active/inactive) span 2000–2025, with a focus on process optimization and material interactions in pharmaceutical manufacturing.

Heli Viljakainenمشاهده پروفایل

دانشیار

• Nutritional Epidemiology
• Clinical Epidemiology
• Genetic Epidemiology
• +۸ مورد دیگر

Heli Viljakainen is an Associate Professor at the University of Helsinki , leading the Folkhälsan Research Center and serving as a Visiting Researcher at HUS Children's and Adolescent Diseases. Her research focuses on multidisciplinary approaches to understanding childhood weight development. Education : Human Nutrition Expertise : Clinical Research, Omics Sciences, Nutritional Epidemiology Research Interests : She investigates genetic and environmental risk factors for overweight in children, integrating computational genomics , nutritional epidemiology , and public health to identify early prevention strategies. Scientific Outputs : Recent publications highlight her work on oral microbiome-diet interactions , mental health-weight associations , and perinatal influences on obesity . Collaborations span genetic epidemiology , vitamin D studies , and prevention research . Supervision : She mentors doctoral candidates in projects like Fin-HIT cohort studies and dietary-salivary microbiome analyses. Active projects include longitudinal research on satiety responsiveness and obesity mechanisms.

• Educational Sciences
• Mathematics Education
• Virtual Learning
• +۳ مورد دیگر

Reito Salonen is a Project Planner at the Department of Educational Sciences , Institute of Humanities and Social Sciences (HSSH) , University of Helsinki , and a key researcher in educational sciences, particularly focusing on collaborative learning, visual attention in teaching, and virtual learning environments. Research Interests include: Collaborative geometry problem-solving dynamics Teacher visual attention in co-teaching settings Emotional states in virtual learning Evidence-centered design in educational assessment Physiological measures for learning analytics Sociodigital practices post-COVID-19 distance learning Notable Research Trends from his publications (2025-2024) involve interdisciplinary methods combining educational psychology, eye-tracking technology, and data-driven assessment frameworks to study student-teacher interactions and digital learning resilience.

• Linguistics
• Interactional Linguistics
• Multilingualism
• +۴ مورد دیگر

Salla Kurhila is a Professor at the Department of Finno-Ugric and Nordic Studies, Faculty of Humanities, University of Helsinki. Her research focuses on interactional linguistics, multilingualism, and language learning, particularly in institutional and workplace settings. She actively contributes to the Helsinki Inequality Initiative (INEQ) and serves as a supervisor in the Doctoral Program in Linguistics. Her work spans conversation analysis, digital interaction, and cross-linguistic studies. Recent Research Trends: Her publications emphasize multilingual workplace dynamics, conversation analysis, and language policy. Notable projects include flexible multilingualism in academic governance and Finnish language acquisition among immigrants. Scientific Awards: Member of the Teachers' Academy (2016) Blog Abstract Competition Winner, Conversation Research Days (2020) Special Mention, Finnish Economists' Business Book 2024 (2025) Supervision & Projects: She has supervised multiple projects on Finnish language learning, professional communication, and prosodic analysis. She collaborates with the Finnish Academy of Science, HY's Future Fund, and the Emil Aaltonen Foundation.

Anisia Katinskaiaمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Language Learning
• Grammatical Error Correction
• +۴ مورد دیگر

Anisia Katinskaia is a doctoral researcher at the University of Helsinki, holding dual affiliations with the Department of Digital Humanities and Department of Computer Science. Her research bridges computational linguistics and language education, focusing on practical applications of natural language processing to enhance language learning experiences. She actively contributes to the academic community through publications in major computational linguistics conferences and participation in significant research projects. Dr. Katinskaia's research interests center on natural language processing applications for language learning, with particular expertise in grammatical error correction, text difficulty assessment, and intelligent tutoring systems. Her work demonstrates a strong focus on applying transformer models and large language models to solve practical challenges in language education, with notable contributions in Russian and Tatar language processing. She has developed innovative approaches for assessing grammatical correctness, estimating text difficulty, and creating adaptive learning tools that respond to individual learner needs. Analysis of her publication record shows a clear trajectory from foundational work in grammatical error detection (particularly for Russian language) toward more sophisticated applications of modern language models like GPT-3.5 and transformer architectures. Her recent work demonstrates increasing sophistication in probing linguistic capabilities of AI models and developing practical educational applications, with a growing emphasis on minority languages like Tatar. The interdisciplinary nature of her research connects computational linguistics with educational theory and cognitive science. Dr. Katinskaia has received significant recognition for her work, including: Best Paper Award (2018) Outstanding paper award (2023) The Open Science Award (2018) She is actively involved in multiple research projects including Know-AI (funded by the Academy of Finland), Revita: Language learning and AI, LLL: Language Learning Lab, and Easy Language for accessible workplace (funded by Business Finland). Her collaborative approach is evident through her work with researchers like Yangarber, Hou, Vu Anh, and others across multiple projects and publications. She regularly presents her research at international conferences and has participated in prestigious events like the Lisbon Machine Learning School. Dr. Katinskaia is a key member of the Language Learning Lab research group at the University of Helsinki, where she contributes to developing cutting-edge tools that apply AI to language education challenges. Her work on the Easy Language project specifically targets making workplace communication more accessible through language technology solutions.

Miracle Amadiمشاهده پروفایل

پژوهشگر ارشد

• Computational Epidemiology
• Mathematical Modeling of Infectious Diseases
• Bayesian Statistics
• +۳ مورد دیگر

Miracle Amadi is a Postdoctoral Researcher (Research Fellow) in the Department of Computational Engineering at the School of Engineering Sciences, Lappeenranta-Lahti University of Technology (LUT University), Finland. Amadi's research focuses on developing and applying computational and statistical models to study infectious disease dynamics, including malaria, HIV, dengue, and COVID-19, with a particular emphasis on the impact of environmental factors and intervention strategies. Amadi's research interests span computational epidemiology, mathematical modeling of infectious diseases, Bayesian statistics, and public health. Their work integrates advanced statistical techniques such as Bayesian model selection, parameter estimation, and uncertainty quantification with epidemiological data to address critical public health challenges. Recent projects have examined the relationship between meteorological factors and disease incidence, the evolution of insecticide resistance in malaria vectors, and the effectiveness of non-pharmaceutical interventions during the COVID-19 pandemic. Analysis of Amadi's recent publications (2018-2025) reveals a strong trend in applying hybrid modeling approaches, including agent-based and spatio-temporal models, to complex epidemiological problems. A significant portion of the work focuses on malaria, with additional contributions to HIV, dengue, lumpy skin disease, and COVID-19. The research consistently emphasizes the role of environmental and climatic factors in disease transmission and the evaluation of control strategies, demonstrating a commitment to data-driven public health decision-making.

Ville Ojanenمشاهده پروفایل

استاد

• Sustainable Urban Development
• Innovation Management
• Industrial Services
• +۷ مورد دیگر

Ville Ojanen is a tenured Professor at Lappeenranta University of Technology (LUT), affiliated with the School of Engineering Sciences. His academic career spans over two decades with continuous scholarly contributions in engineering management, sustainability, and innovation. His research interests focus on sustainable urban development, innovation management, industrial services, asset management, and product-service systems. His work bridges engineering, sustainability, and business perspectives, with particular emphasis on how organizations can develop sustainable practices and innovative service models. Professor Ojanen's recent publications (2020-2025) demonstrate a clear trajectory toward sustainable urban development, smart city innovations, and digital transformation in industrial services. His work on citizen participation frameworks, digital twins for machine operations, and sustainability challenges in biobased packaging shows interdisciplinary engagement across engineering, environmental science, and social sciences. His research has appeared in high-impact journals such as Cities, International Journal of Human-Computer Interaction, and Sustainability, reflecting both the interdisciplinary nature and practical relevance of his work.

Tuomas Eerolaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Vision
• Pattern Recognition
• +۵ مورد دیگر

Tuomas Eerola is an Associate Professor in Computational Engineering at Lappeenranta-Lahti University of Technology's School of Engineering Sciences. Previously, he served as a Postdoctoral Researcher at the same institution's Machine Vision and Pattern Recognition Laboratory from 2010 to 2020. He also holds the Title of Docent (Adjunct Professor) from 2015 to present. Dr. Eerola received both his M.Sc. and Ph.D. degrees in Information Technology from Lappeenranta University of Technology in 2006 and 2010, respectively. His research spans computer vision, machine vision, pattern recognition, and image processing, with particular focus on wildlife monitoring, plankton recognition, and industrial applications. His publication record shows consistent research output with over 50 publications, primarily focusing on animal re-identification (particularly ringed seals), plankton recognition systems, and wood processing applications. Recent work demonstrates increasing focus on deep learning approaches, multimodal systems, and practical applications in both ecological monitoring and industrial settings. Dr. Eerola actively serves as a peer reviewer for numerous prestigious journals including Ecological Informatics, Expert Systems with Applications, GigaScience, International Journal of Computer Vision, Mammalian Biology, and Measurement. His research has established him as a specialist in applying computer vision techniques to ecological monitoring problems, particularly in developing systems for identifying individual animals based on their natural patterns, which has significant implications for wildlife conservation efforts.

• Design
• Computer Science
• Augmented Reality
• +۷ مورد دیگر

Camila Hergatacorzian is a Doctoral Researcher at the Department of Design within Aalto University's School of Arts, Design and Architecture. Her work integrates design thinking with technological innovation across diverse domains. Research Focus: Augmented Reality (AR) applications for healthcare (Parkinson's disease mobility assistance) Tangible User Interfaces (TUIs) in educational settings Digital service development for public institutions Computational thinking integration in kindergarten education Participatory cultural mapping for urban development Recent publications highlight AR-based medical devices (2023), classroom technology evaluation (2024), and digital service collaborations in public libraries (2024). She served as a visiting researcher at the Interactive Technologies Institute (Oct 2024–Apr 2025) and maintains an ORCID profile (0009-0004-6079-7135) with 32 Mendeley readers.

Salu Yliriskuمشاهده پروفایل

مدرس ارشد

• Participatory Design
• User-Centered Design
• Design Concepts
• +۳ مورد دیگر

Salu Ylirisku is a Senior Lecturer at the Aalto School of Electrical Engineering, specializing in design pedagogy and transdisciplinary education. Their work bridges engineering education with participatory design methodologies, contributing to UN Sustainable Development Goals related to quality education. Doctoral Degree in Arts and Design, Aalto University (2013) Master's Degree in Engineering and Technology, University of Helsinki (2002) Research interests include participatory design, user-centered design processes, and innovative approaches to engineering education. They have collaborated with Microsoft Research Cambridge and led interdisciplinary projects like the Interactive Lights Installation at Flash Vallisaari. Their publications emphasize transdisciplinary frameworks, co-design methods, and sensory-driven design solutions. Recent publications (2021-2023) focus on reimagining design pedagogy for online environments, language dynamics in design, and multidisciplinary curriculum development. Key subfields span embodied interaction, educational technology, and collaborative design practices.

Juho Vepsäläinenمشاهده پروفایل

مدرس

• Web Development
• JavaScript
• Static Site Generation
• +۷ مورد دیگر

Juho Vepsäläinen is a Lecturer in the Department of Computer Science at Aalto University, specializing in web development, JavaScript, and hybrid rendering models. His research bridges traditional content management systems (CMS) with modern static site generation (SSG) techniques while exploring serverless edge computing and developer experience. Education: Master of Science in Information Technology, University of Jyväskylä (2005-2011) Doctoral Thesis on hybrid rendering models in web application development (2025) Research Focus: Vepsäläinen’s work centers on optimizing web application performance through edge computing, serverless architectures, and disappearing frameworks. He investigates how to retain the benefits of CMS and SSG while reducing complexity and enhancing resumability in development workflows. Publication Trends: Recent articles emphasize serverless edge-powered solutions, hybrid rendering models, and the evolution of disappearing frameworks. Keywords span Web Development , Edge Computing , and Performance Optimization , with subfields including distributed networks, content delivery systems, and framework-less architectures. Collaborations: Collaborated with Antti Hellas and Petri Vuorimaa on edge computing and web performance, contributing to conferences like WEBIST and journals such as IEEE Access .

Jose Ladoمشاهده پروفایل

استادیار

• Quantum Materials
• Graphene
• Topological Superconductivity
• +۵ مورد دیگر

Jose Lado is an Assistant Professor at the Department of Applied Physics, Aalto University. His research focuses on exotic quantum states in two-dimensional materials and twisted van der Waals systems, including topological superconductivity, quantum spin liquids, and fractionalized matter. He actively collaborates with experimental groups and leads projects like ULTRATWISTROICS and ERC-funded FQF P4 T30428 . Research Interests : Correlated quantum materials, topological superconductivity, graphene-based heterostructures, and moiré quantum matter Key Themes : Electronic correlations, symmetry-breaking states, quantum engineering of fractional particles, and spin-textured flat bands His recent publications emphasize non-Hermitian topology, Kondo lattice dynamics, and machine learning applications in many-body systems. Awards include three Early Career recognitions (2021-2023). He contributes to UN Sustainable Development Goals through quantum material innovation.

Matthijs de Jongمشاهده پروفایل

پژوهشگر ارشد

• Quantum Optomechanics
• Nanomechanics
• Casimir Physics
• +۲ مورد دیگر

Matthijs de Jong is a Postdoctoral Researcher at the Department of Applied Physics within the Faculty of Applied Sciences at Delft University of Technology, affiliated with the Quantum NanoOptomechanics and Forces research group. His work bridges theoretical modeling and experimental physics in quantum nanoscale systems. He earned his Doctorate from Delft University of Technology in December 2022 with research on dynamical behavior of trampoline membranes , specializing in Optomechanics and Nanomechanics. His educational foundation includes advanced training in quantum measurement techniques and nanofabrication. Dr. de Jong's research centers on Quantum Optomechanics and Nanomechanics , with significant contributions to Casimir Physics and Computational Physics . He develops Finite Element Analysis frameworks to model quantum phenomena in mechanical resonators while conducting precision experiments on nanoscale forces. His work directly impacts quantum computing hardware development and fundamental force measurement techniques at microscopic scales. His 2024 publications reveal a dual focus: quantum control of acoustic resonators for information processing and computational modeling of electrostatic forces in complex geometries. These studies demonstrate his expertise in translating theoretical quantum frameworks into experimental implementations, particularly for Casimir force measurements in superconducting systems. Dr. de Jong actively contributes to open science through research datasets and participates in key conferences like the MQSens Workshop (June 2024), advancing collaborative efforts in quantum sensing and nanomechanics. As a core member of the Quantum NanoOptomechanics and Forces group, he develops experimental platforms for measuring quantum effects in mechanical systems, with emphasis on superconducting devices and nanoscale force characterization techniques.

Kaisu Lankinenمشاهده پروفایل

استاد مهمان

• Neuroscience
• Neuroimaging
• Magnetoencephalography
• +۲ مورد دیگر

Kaisu Lankinen is a Visiting Professor at the Department of Neuroscience and Biomedical Engineering at Aalto University . Her research focuses on Magnetoencephalography (MEG) , neural synchrony , and social interaction , combining machine learning and neuroimaging techniques. Education Diplomi-insinööri (Master of Science in Technology), Aalto University, 2011 Tekniikan kandidaatti (Bachelor of Science in Technology), Elektroniikan ja sähkötekniikan koulutusohjelma, 2009 Research Trends : Her recent work explores social conflict resolution through neural alignment, letter processing in sensory cortices, and open-source software development for MEG/EEG analysis. Themes include ecological validity and neural dynamics . Labs & Collaborations : She collaborates with institutions like University of California, Berkeley (2017 visiting researcher) and contributes to tools like HNN-core .