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Fabian Fagerholm is an Assistant Professor in the Department of Computer Science at Aalto University. His work bridges software engineering, human-computer interaction, and empirical research methodologies. He actively participates in research groups such as Software and Service Engineering (SSE) and Human-Computer Interaction and Design (HCID). Fagerholm's research explores: Continuous experimentation in software development Developer cognition and mental models Agile methodologies and team dynamics Low-code platforms and end-user programming Software engineering education and pedagogy His publications reflect a strong empirical focus, with recurring themes of human factors in technical systems and educational innovation. He has received notable awards including: Journal of Systems and Software Best Paper Award (2018) EUROMICRO SEAA Distinguished Paper Award (2017) Teacher of the Year (2013) Nokia Foundation Scholarship (2013) Fagerholm contributes to software engineering infrastructure through tools for experimentation and boundary artifacts, enhancing collaboration in distributed teams.

• Software Engineering
• Human-Computer Interaction
• Agile Development
• +3 more

Aapo Hyvärinen is a Professor of Computer Science at the University of Helsinki , affiliated with the Helsinki Institute for Information Technology and the Helsinki Probabilistic Machine Learning Lab . He previously held the position of Professor of Machine Learning at the Gatsby Computational Neuroscience Unit, University College London (2016-2019). Education : Undergraduate Mathematics at University of Helsinki, Vienna, and Paris; Ph.D. in Information Science from Helsinki University of Technology (1997) His research focuses on machine learning and computational neuroscience , particularly: Independent Component Analysis (ICA) Natural Image Statistics Causal Representation Learning Neural Signal Processing Applications to brain imaging (MEG, CryoEM) Recent publications emphasize causal discovery , identifiable machine learning , and nonlinear ICA . Key projects include: VETURI (AI for health) DIGIMIND (AI in mental health) CIFAR grants (2022-2025) Scientific awards : Highly Cited Researcher (2010) He serves as Action Editor for the Journal of Machine Learning Research and Neural Computation , and has held Area Chair roles at NeurIPS, ICML, ICLR, AISTATS, and UAI conferences. His work bridges theoretical machine learning with neuroscience and philosophical implications of artificial intelligence .

• Machine Learning
• Computational Neuroscience
• Artificial Intelligence
• +7 more

Olav Tirkkonen serves as a Full Professor in the Department of Communications and Networking at Aalto University, Finland, a position he has held since August 2006. He leads the Communication Theory research group, driving innovation in wireless communication systems. His academic journey includes a distinguished career spanning industry and academia, with significant contributions to 3G, 4G, and 5G technologies. His educational qualifications are: Doctor of Science (Ph.D.) in Theoretical Physics, Helsinki University of Technology, 1994 Master of Science (M.Sc.) in Theoretical Physics, Helsinki University of Technology, 1990 Professor Tirkkonen's research interests are centered on wireless communications, with a focus on physical layer processing, coding theory, and quantum information processing. His group explores advanced topics including 5G and beyond wireless networks (spectrum management, large-scale MIMO, ultra-reliable low-latency communication), network-level interference coordination, collaborative caching, machine learning applications for wireless channel geography, coding on manifolds, and quantum communication systems. This research bridges fundamental theory with practical implementation in next-generation wireless networks. Analysis of his recent publications (2024-2025) indicates a predominant focus on machine learning techniques for wireless channel modeling (channel charting), pilot allocation in MIMO systems, and quantum error correction. His work is instrumental in addressing key challenges in 5G/6G networks, particularly in scenarios demanding ultra-reliability, low latency, and efficient resource utilization. His scientific contributions include: Co-inventor of approximately 80 families of patents and patent applications Co-author of the book "Multiantenna transceiver techniques for 3G and beyond" Throughout his career, Professor Tirkkonen has mentored numerous graduate students and secured substantial research funding from various sources. His industry experience at Nokia Research Center (1999-2010) and visiting position at Cornell University (2016-2017) have enriched his research perspective and fostered strong industry-academia collaborations. The Communication Theory group, under his leadership, maintains active collaborations with leading institutions and companies worldwide, positioning Aalto University at the forefront of wireless communications research.

• Wireless Communications
• Coding Theory
• Quantum Information Processing
• +5 more

Professor Petri Kuosmanen is affiliated with Aalto University as a faculty member of the School of Engineering and holds a position in the Department of Energy and Mechanical Engineering and the Mechatronics unit. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2004) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (1992) Master's Degree in Engineering and Technology, Helsinki University of Technology (1988) His research focuses on Industrial Internet and Rotor Dynamics , with significant contributions to elevator systems , hydraulics , and wastewater treatment plant design . Recent work includes optimizing natural frequencies in rotor systems and developing digital twins for engineering education . Key trends in his 2024 publications include: Rotor dynamics and vibration analysis Smart data validation in industrial IoT networks Cold-climate adaptations for wastewater treatment Automated fiber optics coating mechanisms Energy efficiency in aeration systems As Principal Investigator, he leads projects like DRIVE FORWARD (2024–2027) and GOOD (2021–2024), focusing on electrified mobile machinery. He actively collaborates with networks such as DAAAM International (Chair) and European CLUSTER-university network (Member).

• Mechatronics
• Rotor Dynamics
• Industrial Internet
• +7 more

Teemu Roos is a Professor at the Department of Computer Science , University of Helsinki , and a Principal Investigator for the Complex Systems Computation Group under the Helsinki Institute for Information Technology. He serves as a Supervisor for the Doctoral Programme in Computer Science and leads multiple research initiatives, including Distributed AI in Supercomputing , AI & Kids , and Generation AI . Dr. Roos also holds a Docent title in Computer Science. His research spans Artificial Intelligence , Machine Learning , and Data Science , with a focus on AI education , graph neural networks , Bayesian modeling , and health informatics . He has pioneered tools like Elements of AI , a free online course now translated into 22 EU languages, and explores the ethical implications of AI-generated content in authorship and inventorship. The 15 most recent publications highlight applications in environmental forecasting (e.g., Mediterranean Sea via graph-based deep learning), healthcare (e.g., skin cancer detection with transfer learning), and social media analysis (e.g., explainable AI platforms for K-12 education). Methodologically, his work advances clustering algorithms , dimensionality reduction , and approximate nearest neighbor search . Scientific Awards: Cor Baayen Award (2009) Nokia Foundation Recognition Award (2019) Best Paper Honorable Mention Award (2013) ICT Influencer of the Year 2019 (Vuoden TiVi-vaikuttaja 2019) World Summit AI's Top-50 Innovators in 2020 Dr. Roos has supervised 2 doctoral students and contributed to 163 academic activities , including invited talks at MIT, University of Cambridge, and the Finnish Institute in Rome. He has secured funding from the Academy of Finland and the Strategic Research Council, focusing on projects like Fast AI-assisted Space Environment Prediction and Urban Exerciser .

• Artificial Intelligence
• Machine Learning
• Data Science
• +6 more

Senior Lecturer Outi Salo-Ahen is affiliated with Åbo Akademi University's Faculty of Natural Sciences and Engineering , Department of Pharmacy. Her research focuses on computational pharmacology, drug design, and pharmaceutical chemistry, particularly targeting chemokine receptors (CCR5/CXCR4) and transient receptor potential channels (TRPA1) for therapeutic applications. Doctor of Pharmacy (2006, University of Kuopio/UEF) MSc in Pharmaceutical Chemistry (2001, UEF) BSc in Pharmacy (1999, UEF) University Pedagogy Modules 1-5 (2012-2015) Her work contributes to UN Sustainable Development Goals through education and pharmaceutical innovation . Recent research trends include: Antimicrobial resistance solutions TRPA1 channel modulation Nanotechnology-enabled drug delivery Multi-target HIV-1 inhibitors 3D printing of biocompatible materials Computational analysis of nucleic acid frameworks She actively supervises doctoral projects, serves on assessment panels, and leads collaborations like Nordic Pharmaceutical Translation and Innovation. Her 60+ publications demonstrate expertise in molecular modeling and drug discovery.

• Pharmaceutical Chemistry
• Molecular Modeling
• Drug Design
• +5 more

Pekka Marttinen is a tenured Associate Professor of Machine Learning at Aalto University, Department of Computer Science, and leads the Machine Learning for Health (Aalto-ML4H) group within the Helsinki Institute for Information Technology HIIT. Education: M.Sc. in Applied Mathematics, University of Helsinki (2004) Ph.D. in Statistics, University of Helsinki (2008) Title of Docent in Information and Computer Science, Aalto University (2015) Research Focus: His methodological work spans large language models, reinforcement learning, deep learning, probabilistic machine learning, and causal inference . These techniques are applied to critical domains of healthcare, bioinformatics, statistical genetics, epidemiology, and personalized medicine . The group develops novel algorithms, theoretical guarantees, and open-source software that enable data-driven discovery and decision-making in medicine and biology. Publication Trends: Across 2022-2024 the lab has concentrated on (i) rigorous causal reasoning over temporal clinical data, (ii) principled uncertainty quantification in LLMs, (iii) representation learning for neural network comparison, and (iv) translational projects that turn raw EHRs into actionable clinical insights. Earlier work integrated high-dimensional genomics with metabolomics and mapped evolutionary forces in bacterial pathogens. Scientific Awards & Recognition: While no specific awards are listed, his sustained publication record in top-tier venues (NeurIPS, ICML, AISTATS, Nature Genetics, PLOS CB) and his role as responsible professor of the Machine-Learning, Data-Science and AI major signify significant peer recognition. Advising & Grants: Prof. Marttinen currently mentors 8 PhD students as primary supervisor and an additional 7 PhD students as co-supervisor. He has already graduated 8 PhDs since 2014. The group is supported through competitive funding including the Finnish Center for Artificial Intelligence (FCAI) doctoral program. Labs & Teams: He directs the Machine Learning for Health (Aalto-ML4H) research group, comprising postdocs Hans Moen, Ti John, Alexander Nikitin, Negar Safinianaini, Linli Zhang, Zhiyuan Li, and the above-mentioned PhD cohort.

• Machine Learning
• Large Language Models
• Reinforcement Learning
• +8 more

Ruben Vicente-Saez is a Visiting Professor at Aalto University's Department of Industrial Engineering and Management. His work focuses on Open Science and Open Innovation, contributing to global efforts aligned with the UN Sustainable Development Goals, particularly in education and academic qualification. Aalto University College of Engineering Department of Industrial Engineering and Management His research explores the normative structures, mechanisms, and collaborative frameworks enabling open science practices. Key areas include data sharing, open innovation governance, and strategic policy development for sustainable academic ecosystems. Recent publications highlight his contributions to mainstreaming open science across European universities, developing governance models, and co-creating research proposals through open innovation practices. His work bridges computer science methodologies with social science insights to advance scientific collaboration.

• Open Science
• Open Innovation
• Knowledge-Sharing
• +3 more

Matti Haavisto is a University Instructor in the Department of Computing Sciences at Tampere University's Faculty of Information Technology and Communication Sciences. He is affiliated with the Hervanta Campus and can be reached via email matti.haavisto@tuni.fi or phone number +358401981478. While explicit research interests are not detailed in the provided information, his department affiliation suggests expertise in areas such as software engineering, data science, and cybersecurity. No recent articles, grants, or awards are listed in the text.

• Computer Science
• Software Engineering
• Data Science
• +3 more

Toni Kotnik is an Associate Professor in the Department of Architecture at Aalto University, Finland. He holds dual expertise in mathematics and architecture, with a Ph.D. from the University of Zurich and a second degree in architecture. His roles include principal of d’HKL , a Zurich-based experimental architecture firm, and adjunct lecturer at institutions like Harvard University and the Bartlett School of Architecture. His research focuses on integrating science, engineering, and computation into architectural design, emphasizing structural innovation and sustainability. Education: Ph.D. in Mathematics (Dr. sc. Nat.), University of Zurich, 1999 Second degree in Architecture Research Interests: Computational design and generative systems Structural aesthetics and neuroaesthetics Sustainable urban and architectural solutions Parametric modeling and material systems Key Contributions: Advances in graphic statics and form-finding Design strategies for high-density urban environments Integration of AI and generative tools in architectural practice Recent Work Trends: Recent articles emphasize computational methods for industrial layout optimization, AI’s role in architecture, and embodied perception in structural design. His work bridges theoretical research with practical applications, such as the Singapore Hawker Centre redesign and experimental structures like hypar-combined shells. Awards: Aalto University Doctoral Thesis Awards (2022) Best Presentation Award (2019) Oscari-Vilamo Award (2023) Advising & Grants: Supervised 4 theses, including recipients of awards like the Metex Award shortlist. Active in international academic networks, serving on conference committees (e.g., International Association for Shell and Spatial Structures) and editorial roles (e.g., Automation in Construction journal). Labs & Teams: Leads the d’HKL studio, collaborating globally on projects like the AA/ETH Pavilion and the Hypercube for Gardens by the Bay. Research focuses on experimental design and material systems.

• Computational Design
• Architectural Engineering
• Structural Design
• +4 more

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.

• Digital Humanities
• Human Sciences–Computing Interaction
• Computational Humanities
• +3 more

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).

• Artificial Intelligence
• Data Science
• Computational Creativity
• +2 more

Antti Poso is a Professor of Drug Design at the University of Eastern Finland (Kuopio), affiliated with the School of Pharmacy under the Faculty of Health Sciences. His research focuses on computer-aided molecular design, particularly targeting anti-cancer drugs and anti-microbials. Key projects include the EDCMET project (2019–2024) and the GeneCellNano Flagship (2020–2028). He leads the Molecular Modeling and Drug Design Research Group, specializing in QSAR analysis, kinase inhibition profiling, and systems-level drug response modeling. Recent work includes studies on SARS-CoV-2 inhibitors, endocrine disruptors, and bacterial pathogenesis. His findings bridge chemical structure with biological outcomes, leveraging computational tools like CCA and molecular dynamics simulations. Collaborations span medicinal chemistry, pharmacology, and systems biology, contributing to both academic and applied drug discovery efforts. Education: Not explicitly stated in texts; assumed to hold advanced degrees in pharmacy or chemistry. Research Themes: Drug design, molecular modeling, QSAR, computational biology, and anti-infective agents. Key Contributions: Over 150+ publications, including influential works on chemoinformatics-driven drug response analysis and structure-based inhibitor design. Publications highlight advancements in kinase inhibitors, anti-microbial strategies, and viral hijacking mechanisms. His work emphasizes translating computational insights into therapeutic solutions for cancer, infectious diseases, and metabolic disorders.

• Drug Design
• Molecular Modeling
• Anti-Cancer Drugs
• +3 more

Sanna Järvelä is a Professor in the Faculty of Education and Psychology at the University of Oulu, where she leads the Learning and Educational Technology Research Lab (LET). She is a leading figure in learning sciences, with a focus on self-regulated learning, collaborative learning, and AI integration in educational contexts. Her research is supported by major international and national grants, including from the Jacobs Foundation. Research Interests: Self-regulated learning and socially shared regulation Computer-supported collaborative learning (CSCL) Artificial intelligence and adaptive technologies in education Development and application of multimodal research methods Her work bridges theoretical advancement with innovative methodological practices, contributing significantly to the understanding of learning in digital environments. While no specific publications are listed, her research output is extensive and highly cited, evidenced by her inclusion in Stanford University’s top 2% most-cited scientists list (2024). Scientific Awards and Honors: Member of the Finnish Academy of Science and Letters (2015) Francqui Chair, Ghent University (2015–2016) Learning Sciences Fellow (2022) Knight First Class of the Order of the White Rose of Finland (2022) Finnish Ostrobothnia Cultural Foundation Science Prize (2023) Stanford University’s Top 2% Scientist List (2024) Advising and Grants: As the head of the LET Lab and co-PI of the Center for Learning and Living with AI (CELLA), funded by the Jacobs Foundation, she mentors researchers and leads large-scale interdisciplinary projects. She also leads the University of Oulu’s Profi 7 Hybrid Intelligence research programme, shaping strategic research directions in AI and education. Labs and Teams: She founded and leads the Learning and Educational Technology Research Lab (LET), a vibrant research group focused on advancing knowledge about technology-enhanced learning. She is also a member of the OECD PISA 2025 ‘Learning in the Digital World’ expert team, influencing global educational policy and assessment frameworks.

• Learning Sciences
• Educational Technology
• Self-Regulated Learning
• +5 more

Toni Rantanen is a Doctoral Researcher at Aalto University in the College of Built Environment. His work focuses on integrating geospatial data with game engine technologies for advanced 3D visualization and analysis of urban environments. Specializes in digital twin applications Active in urban sustainability research Collaborates with the MeMo research group Research Interests Geospatial Data Integration : Developing frameworks for open data standards in urban digital twins 3D Visualization : Creating immersive virtual environments for watershed analysis and lighting simulations Environmental Analysis : Using game engines for change detection and urban park evaluation Interactive Mapping : Designing user-friendly geospatial tools Reality Modeling : Capturing built environment changes through multitemporal data Recent publications demonstrate expertise in urban digital twin development , 3D geovisualization , and game engine applications for environmental research. Collaborative work spans multiple disciplines including urban planning , GIS technology , and virtual reality evaluation .

• Geospatial Data
• Urban Planning
• 3D Visualization
• +2 more