جست‌وجوی استاد و پژوهشگر

Arno Solinمشاهده پروفایل

دانشیار

• Machine Learning
• Signal Processing
• Sensor Fusion
• +۸ مورد دیگر

Dr. Arno Solin is a tenured Associate Professor in Machine Learning at Aalto University's Department of Computer Science and an Academy of Finland Research Fellow . He leads the Aalto machine learning research group and serves as Director of the Finnish Doctoral Program Network in AI (AI-DOC) . His work bridges probabilistic modeling with practical applications in sensor fusion and real-time inference. ELLIS Scholar (European Laboratory for Learning and Intelligent Systems) Adjunct Professor at Tampere University Member of Young Academy Finland (2021–2025) Research Interests focus on data-efficient machine learning with probabilistic methods for real-time inference and sensor fusion. Key areas include Gaussian processes, diffusion models, stochastic differential equations, and uncertainty quantification in deep learning. His group develops methods that combine structural constraints with adaptive learning for deployment on resource-limited hardware. Publication Trends show consistent output in top venues (NeurIPS, ICML, ICLR, AISTATS) with emphasis on diffusion models , 3D scene reconstruction , and real-time probabilistic modeling . Recent works explore physics-informed learning, heterophily-aware graph models, and compressed representations for world models in reinforcement learning. Scientific Recognition : Awarded AI Researcher of the Year 2024 by AI Finland Teacher of the Year 2023 at Aalto CS ISIF Jean-Pierre Le Cadre Best Paper Award (2018) MLSP Schizophrenia Classification Challenge Winner (2014) NeurIPS/ICML Reviewer Awards Research Leadership includes coordinating Finland's AI Center of Excellence program and directing the Finnish Doctoral Program Network in AI (AI-DOC). He supervises 15+ doctoral/postdoctoral researchers and has spun off Spectacular AI , a company commercializing sensor fusion technology.

Andres Luceroمشاهده پروفایل

دانشیار

• Interaction Design
• Human-Computer Interaction
• Mobile Interfaces
• +۱ مورد دیگر

Andres Lucero is Associate Professor of Interaction Design at Aalto University's Department of Art and Media, specializing in human-computer interaction for mobile devices and interactive surfaces. His research integrates human-computer interaction, design methodologies, and playful interfaces. He holds a PhD from Eindhoven University of Technology and has industry experience from Nokia, where he led user-centered design projects as Senior Researcher. Research explores tangible interfaces, social wearables, museum experience design, human-AI collaboration, and cross-cultural co-design approaches. Recent projects investigate conversational agents in design processes, persona generation workflows, and freeform interactive devices. Dr. Lucero received the Honourable Mention Award at MUM 2020 for innovative interaction research. His work advances design methods through first-person perspectives, AI integration, and novel interaction paradigms.

Eero Hyvönenمشاهده پروفایل

استاد

• Semantic Web
• Linked Data
• Artificial Intelligence
• +۲ مورد دیگر

Eero Hyvönen is a Professor of Computer Science at Aalto University and Director of the Helsinki Centre for Digital Humanities (HELDIG) at the University of Helsinki. He leads the Semantic Computing Research Group (SeCo), specializing in Semantic Web technologies and applications. Hyvönen holds an Adjunct Professor title at the University of Helsinki's Department of Computer Science. His work focuses on developing national-level semantic web infrastructure, with applications in digital humanities, cultural heritage, and AI. He has published over 500 research articles and books, receiving numerous awards including the Decoration of Knight, First Class, of the Order of the White Rose of Finland (2018). Hyvönen chairs editorial boards of journals like Semantic Web and serves on committees for major conferences. His research spans semantic web technologies, linked open data, and AI applications in cultural heritage domains. Key projects include Sampo portals (e.g., LetterSampo, OperaSampo) for cultural data analysis, ParliamentSampo for parliamentary data, and FindSampo for archaeological finds. His work emphasizes interdisciplinary collaboration, integrating law, history, and computing through initiatives like FIN-CLARIAH. Hyvönen advises doctoral and master's students, notably Annastiina Ahola and Jouni Tuominen, who have won awards under his supervision. He directs research infrastructures, chairs international boards, and actively contributes to open data policies and standards development.

Antti Honkelaمشاهده پروفایل

استاد

• Privacy-preserving machine learning
• Differential Privacy
• Bayesian Machine Learning
• +۳ مورد دیگر

Antti Honkela is a Professor of Data Science at the University of Helsinki's Department of Computer Science, within the Faculty of Science. He also serves as the Coordinating Professor for the Privacy-preserving and Secure AI Research Programme at the Finnish Center for Artificial Intelligence (FCAI), and as Deputy Director of the Master's Programme in Data Science. His roles include membership in the Health and Social Data Permit Authority (Findata) and as an Action Editor for Transactions on Machine Learning Research. Honkela's research focuses on privacy-preserving machine learning, differential privacy, Bayesian methods, and their applications in computational biology and healthcare. He leads projects such as the European Lighthouse in Secure and Safe AI (ELSA) and the Data Literacy for Responsible Decision-making initiative. His work emphasizes developing robust frameworks for privacy-aware AI, including differentially private synthetic data and federated learning. Honkela has advised numerous PhD and Master's students, and his contributions span theoretical advancements and practical implementations, such as the D3p Python package for differentially private probabilistic programming. Key contributions include advancements in Bayesian inference from synthetic data, privacy accounting mechanisms, and computational methods for genomic epidemiology. His interdisciplinary approach bridges machine learning, statistics, and healthcare, addressing challenges in data privacy and secure AI deployment.

Hilda Ruokolainenمشاهده پروفایل

مدرس ارشد

• Information Science
• Social Sciences
• Qualitative Research
• +۳ مورد دیگر

Hilda Ruokolainen is a Senior Lecturer at Åbo Akademi University, affiliated with the School of Business and Economics. Her work focuses on misinformation as a social phenomenon, particularly within asylum seeker contexts, using qualitative methodologies like semi-structured interviews and empirical research. University: Åbo Akademi University School: School of Business and Economics Email: hilda.ruokolainen@abo.fi ORCID: 0000-0003-2521-4390 Her research spans information science, social sciences, and migration studies, emphasizing collaborative qualitative practices and the creation process of data. Recent publications analyze official misinformation, methodological approaches, and network effects in information research. Key trends in her work include social dynamics of misinformation, empirical studies on service workers, and the intersection of information practice with computer science. She advocates for embracing complexity in collaborative research frameworks.

• Social and Cultural Anthropology
• Southeast Asia
• Indonesia
• +۹ مورد دیگر

Timo Kaartinen serves as Professor of Social and Cultural Anthropology and Vice Dean for Research and Doctoral Education at the University of Helsinki 's Faculty of Political Science . Since 1992, he has conducted extensive research in Southeast Asia with a focus on Indonesia, exploring communicative practices, narratives, and cultural responses to uncertainty. His teaching spans social change in bachelor's, master's, and doctoral programs, covering environmental anthropology, political anthropology, cosmologies, religions, and linguistic anthropology. PhD in Anthropology, University of Chicago (2001) Docent (Adjunct Professor), University of Helsinki (2011) Research interests center on ethical discourse in Indonesian Islamic universities, resource politics in oil palm estates, and linguistic anthropology with emphasis on storytelling, folk poetry, and minority language revitalization. His work combines ethnographic focus on Southeast Asia with theoretical contributions to frontier studies and postcolonial anthropology. Recent publications examine frontier temporalities (2020-2025), Islamic transformations (2019), and oral narrative structures (2017-2013). Key projects include ARCTIC Research Centre (2025-2029), Diversity in Society and Life (DIVSOL) (2025-2030), and Religious Movements in Ethical Life (2019-2023). Grants from the Academy of Finland and University Profiling Funding support these initiatives. Academic activities include keynote speeches at international conferences (e.g., Empowering Local Wisdom 2014, Labor Migration in Asia-Pacific 2013) and editorial roles. He has conducted fieldwork in Indonesia since 1992, focusing on Bandanese cultural heritage and Maluku religious dynamics . His methodological approach combines ethnographic fieldwork with historical document analysis .

Marketta Kyttäمشاهده پروفایل

استاد

• Environmental Psychology
• Child-Friendly Urban Planning
• Public Participation GIS (PPGIS)
• +۶ مورد دیگر

Marketta Kyttä is a Professor of Land Use Planning at Aalto University's Department of Built Environment. She holds a PhD in Architecture from Helsinki University of Technology (2004) and leads the Spatial Planning and Transportation Engineering Master’s program. Research Interests: Child- and age-friendly urban environments SoftGIS methodology for participatory mapping Social sustainability and urban health Public participation in planning Activity space modeling Scientific Awards: Lea Pulkkinen award Tapio Nummenmaa award Geospatial World Forum's WebGIS Innovation Award (2010) Oskari Vilamo award (2020) Oppikirja-palkinto for urban planning literature Methodological Contributions: SoftGIS (PPGIS innovation) Commercialization as Maptionnaire software International Collaborations: Affiliated with universities in Italy, Australia, and the US. Her work spans 80+ countries through Maptionnaire’s global adoption.

Suvi Saarikallioمشاهده پروفایل

استاد

• Music Psychology
• Music Education
• Music Therapy
• +۷ مورد دیگر

Suvi Saarikallio is a Professor of Music Education at the University of Jyväskylä, Finland , affiliated with the Faculty of Humanities and Social Sciences and the Department of Music, Art and Culture Studies . She leads interdisciplinary research bridging music psychology, education, and therapy, with a focus on youth development, emotion regulation, and well-being. Research Groups: Centre of Excellence in Music, Mind, Body and Brain (2022-2029), Musiconnect (2022-2027) Key Projects: Music and You, Stress & music listening, MPACT (Music and Sports), Music and Cross-modal Associations, SOSUS (Social Sustainability for Children) Research Trends: Her recent publications explore music's role in emotional regulation, cross-modal perception, health outcomes, and educational applications. Themes include AI's impact on music evaluation, rhythm's connection to cognitive skills, and music's influence on stress and social-emotional development. Contact: suvi.saarikallio@jyu.fi

Eetu Mäkeläمشاهده پروفایل

استاد

• Digital Humanities
• Human Sciences–Computing Interaction
• Computational Humanities
• +۳ مورد دیگر

Eetu Mäkelä is a Professor of Digital Humanities at the University of Helsinki, leading the research group at the Helsinki Centre for Digital Humanities. He focuses on computational methods in humanities and social sciences, including datafication and interdisciplinary collaboration. He serves as Technical Director of DARIAH-FI and a Research Programme Director at the Helsinki Institute for Social Sciences and Humanities. Currently, he heads the preparatory group for the Helsinki Liberal Arts and Sciences Bachelor’s Programme. His research emphasizes technological and theoretical foundations of computational research, with notable contributions to linked open data, sociolinguistic analysis, and historical text mining. He has developed widely used tools like Recon, Palladio, and Octavo, which are employed in academic and public sectors. His work has garnered over 20 awards, including best paper and open science recognitions. Key areas of expertise include digital humanities methodologies, data integration, and open science practices. He actively contributes to teaching, designing courses such as 'Methods for Digital Humanities' and demonstrating innovative pedagogical approaches. His recent projects involve analyzing 18th-century philosophical texts and sociolinguistic change using computational methods. Awards: Multiple best paper awards, open data awards, and open science awards. Grants/Advising: Leads research initiatives funded by the Academy of Finland and other bodies. Mentors interdisciplinary research teams but no specific student names listed. He maintains active roles in academic infrastructure, including the DARIAH-FI initiative and the Helsinki Institute’s datafication program. His work bridges technical innovation with humanities scholarship, emphasizing practical, enduring systems for academic and public use.

• Artificial Intelligence
• Data Science
• Computational Creativity
• +۲ مورد دیگر

Hannu Toivonen is a Full Professor of Computer Science at the University of Helsinki, affiliated with the Faculty of Science and the Department of Computer Science. He leads the Discovery Research Group and is part of the Helsinki Institute for Information Technology (HIIT) and the Finnish Center for Artificial Intelligence (FCAI). He obtained his PhD in Computer Science from the University of Helsinki in 1996 and has held his professorship since 2002. His research spans Artificial Intelligence , Data Science , Computational Creativity , and Data Mining , with applications in generative art, automated journalism, and bioinformatics. His research focuses on: Developing AI systems for creative tasks (e.g., poetry, music, and art generation) Cross-lingual natural language processing and unsupervised learning Ethical and societal implications of AI in media and labor Analysis of his 15 most recent publications (2021–2025) reveals a strong emphasis on computational creativity and AI-driven content generation , with interdisciplinary applications in digital humanities, journalism, and biology. Trends include ethical AI frameworks, human-AI collaboration, and innovative evaluation methods for generative systems. Scientific Awards & Honors: Knight, First Class, Order of the White Rose of Finland (2019) Best Applied Research Award, IEEE ICDM (1998) Honorary Member of TKO-äly (2010) Member of Finnish Academy of Science and Letters He has supervised over 20 doctoral theses and secured ~7 MEUR in grants (e.g., EU projects: Embeddia , Newseye ). He leads the Discovery Research Group and collaborates with institutions like VUB (Belgium) as a Francqui International Professor (2025).

• Statistical signal processing
• Robust statistical methods
• Array processing
• +۶ مورد دیگر

Esa Ollila serves as Associate Professor in the Department of Signal Processing and Acoustics at Aalto University, Finland, and holds an adjunct professorship in Statistics at the University of Oulu. His academic appointments include Academy of Finland Research Fellow (2010-2015) and prior senior research/lecturing roles at both institutions. His educational background features: M.Sc. in Mathematics, University of Oulu (1998) Ph.D. in Statistics (with honors), University of Jyväskylä (2002) D.Sc.(Tech) in Signal Processing (with honors), Aalto University (2010) Professor Ollila's research centers on statistical signal processing and robust statistical methodologies , with significant contributions to array processing, high-dimensional data analysis, and covariance matrix estimation. His work bridges theoretical statistics with practical applications in radar systems, wireless communications, and big data analytics, emphasizing robustness against outliers and computational efficiency in modern data-intensive environments. Current focus areas include compressed sensing, sparse approximation, and blind source separation techniques. Analysis of his 15 most recent publications (2024-2025) reveals three dominant trends: (1) robust covariance learning for massive random access systems, (2) integrated sensing and communications (ISAC) for 6G networks using advanced beamforming, and (3) geometric approaches to elliptical distributions in statistical inference. His work increasingly incorporates deep learning (GANs, graph neural networks) while maintaining strong foundations in classical signal processing theory. Key recognitions include: Academy of Finland Postdoctoral Fellowship (2004-2007) Academy of Finland Research Fellowship (2010-2015) His research has been supported through prestigious Academy of Finland grants totaling over a decade of continuous funding. Professor Ollila currently leads an active research group at Aalto University, supervising doctoral candidates and collaborating internationally with institutions including Princeton University (where he served as Visiting Post-doctoral Research Associate during 2010-2011). He maintains strong ties with the University of Oulu through his adjunct professorship and has contributed to EURASIP's Special Area Team on Theoretical and Methodological Trends in Signal Processing. The Esa Ollila Research Group focuses on cutting-edge challenges in statistical signal processing, with current projects spanning robust DOA estimation under non-Gaussian noise, covariance matrix learning for massive MIMO systems, and machine learning-enhanced radar-communication integration. The group actively develops open-source tools like the fitHeavyTail R package for heavy-tailed distribution modeling and maintains collaborations with industry partners in wireless communications.

• Computer Vision
• Machine Learning
• Deep Learning
• +۶ مورد دیگر

Esa Rahtu is a Professor in the Department of Computer Science at Aalto University, Finland. His research focuses on computer vision, machine learning, and deep learning applications. He leads projects in image coding, neural networks, 3D reconstruction, object pose estimation, and anomaly detection. Rahtu has contributed to over 98 research outputs since 2017, with recent work emphasizing Gaussian splatting for SLAM, neural radiance fields, and hybrid video codecs for human-machine compatibility. His expertise spans visual-inertial odometry (e.g., ADVIO dataset), LiDAR-based place recognition, and manufacturing quality control systems. Key areas include: 3D scene reconstruction using Gaussian splatting techniques Deep learning models for anomaly detection in industrial processes Hybrid video codecs optimizing human perception and machine processing Multi-sensor fusion for robotic navigation and indoor mapping Notable datasets include ADVIO for visual-inertial odometry and FIORD for 3D reconstruction benchmarking. His research aligns with UN SDG 9 (Industry, Innovation & Infrastructure) and SDG 4 (Quality Education) through advancements in smart manufacturing and educational technology. Rahtu has received continuous research funding, including a grant period from April to June 2018. His work emphasizes practical applications, collaborating on real-world challenges like paper manufacturing quality control and smartphone-based 3D reconstruction.

• Participatory Design
• Indigenous Education
• Gender Justice
• +۴ مورد دیگر

Nathaly Carolina Pinto Torres is a Doctoral Researcher at Aalto University's Department of Design, working on critical design interventions for marginalized communities. Since 2020, she has led the "Emergencia de Educación en la Amazonía Ecuatoriana" project, collaborating with indigenous students and Confeniae to develop pictographic communication systems challenging social exclusion. Her research spans: Participatory design with indigenous communities Gender justice in education during crises Epistemic justice in plurinational contexts Visual resistance strategies in Amazonian regions Postcolonial educational frameworks Design for socio-environmental transformation Publication trends show focus on: Visual communication systems for marginalized groups Crisis-driven educational design Decolonial methodologies Intersectional analysis of exclusion Epistemic justice in academia Collective resilience building Scientific recognition includes: Best Demo Award (2021) SENESCYT International Graduate Scholarship (2019) Netherlands Fellowship Programmes (NFP) (2010)

• Digital Design and Manufacturing (D2M)
• Sustainable Manufacturing
• Optimization Driven Design
• +۷ مورد دیگر

Inigo Flores Ituarte is a Research Professor at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He leads the Digital Design and Manufacturing (D2M) research lab, focusing on sustainable manufacturing and twin-transition strategies integrating digital and green technologies. His work emphasizes optimization-driven design, additive manufacturing innovations, and AI-driven expert systems to enhance energy efficiency and reduce environmental impacts. Key research pillars include: Pillar 1: Twin-transition in Engineering Design and Manufacturing Processes, addressing sustainable manufacturing and intelligent systems Pillar 2: Development of open D2M systems and Process-Structure-Property-Performance (PSPP) linkages in advanced materials His research explores multi-disciplinary optimization combining model-based simulations and data-driven techniques. Notable contributions include generative AI integration in CAD systems, cognitive manufacturing systems, and cost-effective process monitoring using CNN-based methods. Inigo's work emphasizes environmental sustainability, with a focus on reducing manufacturing's energy consumption (54% of global use) and CO2 emissions. He advocates for interconnected material systems, smart manufacturing processes, and AI-assisted decision-making to achieve cognitive intelligence in industrial operations. His D2M lab's overarching goal is to maximize product/process performance while improving cost-effectiveness and minimizing environmental footprints. Recent projects include railway bogie demonstrators via multi-material deposition and sensor systems leveraging IoT and ChatGPT integration.

Kimmo Vehkalahtiمشاهده پروفایل

مدرس ارشد

• Social Data Science
• Social Statistics
• Multivariate Methods
• +۳ مورد دیگر

Kimmo Vehkalahti is a Senior University Lecturer and docent at the University of Helsinki, specifically affiliated with the Centre for Social Data Science within the Faculty of Social Sciences. He serves as a Teachers' Academy Supervisor in the doctoral program and maintains an active research profile with numerous publications and projects. His research interests focus on social data science, social statistics, multivariate methods, open data science, and statistical data processing using R programming. Vehkalahti has developed expertise in applying statistical methods to social science research questions and data visualization. His recent publications demonstrate a strong focus on multivariate analysis applications in behavioral sciences, social data visualization, and student well-being research. The publications span diverse areas including statistical methodology, data visualization techniques, and educational interventions. Fellow of the Teachers' Academy (2013) Best Teacher of the City: Kaupungin Paras Opettaja (2010) Good Teacher: Hyvä Opettaja (2009) Magister Bonus - Good Teacher (2003) One of the best teachers of Open University (2017) Vehkalahti actively supervises academic work with 40 thesis supervisions and 10 PhD supervisions documented. He participates in significant research projects including SASE Stress as strength in education (since 2022) and WELLS - Promoting university students' well-being and life-long learning (since 2019). His academic service includes conference participation, peer review, and organizational roles in international statistical organizations.