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Dr. Olle Järv is an Academy Research Fellow at the University of Helsinki's Department of Geosciences and Geography. As Docent in Human Geography and holder of a joint PhD from University of Tartu and Ghent University, his research focuses on leveraging big data sources like mobile phone records and social media for analyzing human mobility patterns across European cross-border regions. Key research areas: Spatial segregation, urban diversity, transnationalism, and pandemic-induced mobility changes Current projects: BORDERSPACE (2020-2025) – Mapping transnational spaces through mobility data MOBI-TWIN (2023-2026) – Regional mobility patterns in twin transitions WinWin4WorkLife (2024-2027) – Sustainable cross-border remote work His methodological innovations include developing tools for analyzing social media data and mobile phone records to study urban dynamics. Recent recognitions include the 2024 Research Council of Finland Award and 2021 Best Paper Award from Journal of Location Based Services.

• Human mobility
• Big data analysis
• Spatial segregation
• +7 more

Janne Lindqvist is an Associate Professor at the Department of Computer Science, Aalto University. His research bridges security engineering, human-computer interaction (HCI), and privacy, with a focus on making security systems usable and user-centric. University: Aalto University Department: Department of Computer Science Rank: Associate Professor Email: janne.lindqvist@aalto.fi Lindqvist’s work spans security engineering , privacy systems , and user research , emphasizing practical authentication methods, password management, and human behavior in security contexts. He explores how users interact with systems like TPM APIs, gesture passwords, and mobile authentication mechanisms. Recent publications highlight trends in authentication systems , ubiquitous computing security , and mobile user behavior . Key themes include biometric authentication, gesture-based security, and balancing usability with cryptographic robustness. CHI'25 Honorable Mention Award CHI'24 Best Paper Award His research integrates empirical studies with technical implementations, such as analyzing password forgetting patterns and developing acoustic sensing for vehicle detection (e.g., Auto++, BO-Ear). Collaborative efforts span machine learning, psychology, and embedded systems.

• Security Engineering
• Science of Security
• Human-Computer Interaction
• +4 more

Juha Järvelä is a Staff Scientist at the Department of Built Environment , Aalto University, and a member of the Aalto Environmental Hydraulics Lab . His research focuses on environmental hydraulics, particularly on Hydraulics of environmental channels Modeling of vegetated flows Environmentally sound hydraulic engineering Järvelä's research spans fluid dynamics in river systems, with an emphasis on vegetation-flow-sediment interactions. Key areas include flow resistance in flexible and rigid vegetation, hydrodynamic modeling of floodplains, and nature-based solutions for water management. His recent publications investigate Blockage effects of woody vegetation Longitudinal dispersion in patchy vegetation Two-stage channel performance in agricultural settings Hydrodynamic characterization of natural-like plants Järvelä has received notable scientific recognition, including 2014 : Outstanding Reviewer Award from the American Geophysical Union for Water Resources Research 2005 : Doctoral Dissertation Award from the Oskari Vilamo Foundation Contact: juha.jarvela@aalto.fi | Phone: +358505626727 | Postal: Tietotie 1 E, 02150 Espoo, Finland

• Environmental Hydraulics
• Hydraulic Engineering
• Vegetated Flow Modeling
• +3 more

Mikko Kurimo is a Full Professor at Aalto University's Department of Information and Communications Engineering, School of Electrical Engineering. He earned his M.Sc., Lic.Tech., and D.Sc.(Tech.) from Helsinki University of Technology (1992, 1994, 1997) and pioneered neural networks for automatic speech recognition (ASR) in his PhD thesis. After research roles at IDIAP (Swiss AI center) and visiting positions at University of Colorado, Edinburgh, SRI, ICSI, and Nitech, he leads Aalto's ASR group since 2000. His work focuses on unsupervised subword modeling for morphologically complex languages (Finnish, Estonian, Turkish, Arabic) and large speech foundation models. PhD in Neural ASR (Helsinki University of Technology, 1997) Research Scientist at IDIAP (Switzerland) Visiting Fellow at University of Colorado, Edinburgh, SRI, ICSI, Nitech Head of Aalto ASR Group (2000-present) His research spans deep learning for ASR, spoken language modeling , and low-resource language solutions . Recent work explores continued pre-training of self-supervised models, multimodal emotion recognition, and pronunciation assessment using LLMs. He led the winning team in the 2017 Multi-Genre Broadcast challenge and secured competitive funding in Tekes Challenge Finland and EC's H2020-ICT-2017. Key article trends include: Advancements in children's speech recognition and dysarthric speech processing Integration of generative AI for language learning feedback Specialization in low-resource Uralic languages (Finnish, Northern Sámi) Development of robust ASR systems for complex phonetic environments Scientific Awards ACM Multimedia 2023 Computational Paralinguistics Challenge Prize First place in MGB3 2017 Arabic ASR Challenge ISCA Best Student Paper Award (2011) Professeur Invité at Université de Saint-Etienne (2005-2006) Royal Society International Short Visit Fellowship (2004) Professor Kurimo leads the Speech Recognition Group at Aalto, collaborating with COIN (Centre of Excellence in Computational Inference) and AIRC (Adaptive Informatics Research Centre). His projects like CaptainA mobile app demonstrate practical applications of ASR in language education. He has supervised numerous publications with co-authors in domains spanning bandwidth extension, stuttering detection, and speech sound disorder assessment.

• Deep Learning
• Automatic Speech Recognition (ASR)
• Spoken Language Modeling
• +3 more

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.

• Computer Vision
• Machine Learning
• Deep Learning
• +6 more

Sami Sykkö serves as a Professor of Practice at LUT University's School of Economics, where his working life professorship (1.9.2022–31.12.2025) focuses on bridging academic theory with practical business applications. Funded by OP cooperative banks with 140,000 euros, his position emphasizes responsible business practices and evolving consumer behavior trends. Sykkö holds a Master's in International Marketing from the University of Vaasa (1996) with additional studies at Parsons School of Design in New York. His educational background combines economics with design sensibility, creating a unique interdisciplinary perspective. As he states: 'Clothing is more responsible the longer and more often it is used' , reflecting his philosophy on sustainable consumption. His research centers on what he calls 'a megatrend that's hard to imagine being more interesting' - responsibility in business and consumption. Sykkö examines how consumer patterns are shifting, where customer flows are heading next, and how needs, habits, and desires are changing. He emphasizes that 'not only trade but also the life of all humanity is at stake' in these discussions. Through his Taloustango podcast series, Sykkö analyzes economic trends by bringing together university experts and business representatives to discuss greenwashing, sustainable consumption, and design's future. His approach favors real-world examples over theoretical lessons, drawing from his extensive professional network. Professional Recognition Nominated for Presenter of the Year (2018) Widely praised for hosting skills: 'The highest quality hosting I've ever experienced,' 'A master of situational awareness' Academic Engagement Sykkö plans to host 'Professor Sykkö's Question Hour' with Finnish business leaders and aims to become 'Finland's first TikTok professor' to reach younger audiences. His co-hosted 'Sami & Jorma' podcast (42,497 followers) demonstrates his ability to connect academic concepts with cultural discussions on fashion, design, and travel. Professional Activities Beyond academia, Sykkö has interviewed three Finnish presidents, Karl Lagerfeld, and Jane Fonda. He has reported on major global events including the London terrorist attack and Paris Fashion Week. His editorial work includes revamping Gloria magazine and editing publications for the Didrichsen Art Museum.

• Responsible Consumption
• Sustainable Business Practices
• Consumer Behavior
• +4 more

Valeriy Vyatkin is a Professor at the Department of Electrical Engineering and Automation, Aalto University. His research focuses on advancing industrial automation, control systems, and their integration with emerging technologies like machine learning and digital twins. He specializes in standards such as IEC 61499, addressing interoperability, formal verification, and performance optimization in distributed automation systems. Key research interests include: Physics-informed machine learning for industrial processes (e.g., steel rolling, reservoir engineering) Formal methods for control system validation and safety-critical applications Development of adaptive automation frameworks for Industry 5.0 challenges, including human-robot collaboration and energy systems Interoperability between legacy and modern industrial standards (OPAS, OPC UA) Recent work emphasizes real-time simulation, FPGA-based control prototyping, and AI-driven solutions for energy efficiency and sustainability in manufacturing, horticulture, and process industries. Publications span topics like robotic walker design, probabilistic model checking, and decentralized learning management systems. He collaborates on EU and industry-funded projects, focusing on digital twin implementation, edge computing, and virtual commissioning. His team develops tools for automated code generation, system migration, and anomaly detection in complex industrial settings.

• Industrial Automation
• Control Systems
• Machine Learning Applications
• +5 more

Yuqing Wang is a Postdoctoral Researcher in the Department of Computer Science at the University of Helsinki, Finland, actively contributing to software engineering research with expertise in anomaly detection for microservices and test automation maturity. Contactable via yuqing.wang@helsinki.fi and phone +358505934630/+358294151310, Wang participates in major EU and Academy of Finland projects including LUMI AI Factory (2025-2028) and MuFAno (2023-2026). Research focuses on two interconnected domains: anomaly detection in cloud-native systems using meta-learning for cross-system log analysis and trace categorization, and test automation maturity assessment frameworks. Recent work pioneers datasets like LO2 for microservice API anomalies and tools like LogLead for integrated log processing, while earlier studies establish quantitative links between test automation maturity and product quality in open-source ecosystems. Publications reveal an evolving trajectory from foundational test automation maturity models (2018-2020) toward advanced AI-driven anomaly detection (2024-2025), with 2022-2023 bridging both domains through empirical studies on agile practices and maturity impacts. Current work emphasizes cross-system generalization and multimodal fusion for microservice reliability. No scientific awards are documented in available sources. Wang contributes to two significant grants: the EU Horizon Europe LUMI AI Factory developing AI service infrastructure (2025-2028), and the Academy of Finland MuFAno project advancing multimodal anomaly detection for microservices (2023-2026). These projects drive collaboration with industry partners on real-world system reliability challenges.

• Anomaly Detection
• Microservices
• Software Engineering
• +2 more

Professor Garg Vikas holds the position of Assistant Professor in the Department of Computer Science at the School of Science. His research spans quantum computing, artificial intelligence, and machine learning with applications in computational biology, healthcare, and drug design. He leads the HEALED/Garg project focused on human-steered machine learning for drug discovery and collaborates with institutions like MIT and industry partners. He co-founded YaiYai Oy, providing AI/ML solutions to global sectors. Education: PhD from MIT CSAIL under Tommi Jaakkola, with postdoctoral and industry experience at Amazon, Microsoft, and IBM. His work aligns with UN SDGs, particularly in healthcare and sustainable energy. Research interests include graph neural networks, generative models, and quantum AI. Recent projects involve climate modeling via physics-informed neural ODEs and optimizing quantum circuits using graph autoencoders. Key collaborations include MIT’s MLPDS Consortium and the Finnish Center for Artificial Intelligence. He supervises doctoral researchers like Yogesh Verma and postdocs such as Kogkalidis.

• Quantum Computing
• Artificial Intelligence
• Machine Learning
• +8 more

Janne Heikkilä is a Professor at the Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland. With over 30 years of experience in computer vision and machine learning, he leads the Center for Machine Vision and Signal Analysis (CMVS) and has contributed extensively to both theoretical and applied research. Research Interests: 3D computer vision, biomedical image analysis, computational photography, and deep learning. Scientific Leadership: IAPR Fellow, Senior IEEE Member, and former President of the Pattern Recognition Society of Finland. His work spans computer vision, radiotherapy planning, and biomedical imaging, with over 200 publications and 14,000 citations. He has secured funding from prestigious organizations like the Academy of Finland and Business Finland. His recent research focuses on debiasing AI models, 6D object pose estimation, and radiotherapy dose prediction. Scientific Awards: IAPR Fellow Senior Member of IEEE

• 3D Computer Vision
• Algebraic Geometry
• Biomedical Image Analysis
• +5 more

Simon Puglisi is a Professor at the University of Helsinki's Department of Computer Science, within the Faculty of Science. His research focuses on algorithms, bioinformatics, data compression, and string processing, with notable contributions to genomic data analysis and efficient indexing techniques. He holds the Alberto Apostolico Best Paper Award (2021) and leads the WILL # CHAIR # BOSSA project (2025–2029). His work includes scalable k-mer indexing tools like Themisto and advancements in Lempel-Ziv compression and suffix tree algorithms. He frequently collaborates internationally, participates in editorial roles for journals like the ACM Journal of Experimental Algorithmics , and contributes to conferences such as the International Symposium on Combinatorial Pattern Matching. Research Interests: Algorithm design for string processing and bioinformatics Efficient data structures for genomic data Compression techniques (e.g., Lempel-Ziv, Burrows-Wheeler) Dynamic and space-efficient algorithms Grants & Projects: WILL # CHAIR # BOSSA (2025–2029) Ongoing collaborations with institutions like the University of Melbourne and King's College London

• Algorithms
• Bioinformatics
• Data Compression
• +3 more

Andrea Santangeli serves as a Supervisor in the Doctoral Programme in Wildlife Biology and holds a Docentship in the Organismal and Evolutionary Biology Research Program at the University of Helsinki's Faculty of Biological and Environmental Sciences. He maintains an additional affiliation as an Honorary Fellow at the University of Cape Town's FitzPatrick Institute of African Ornithology under the National Research Foundation Centre of Excellence since August 2019. His research spans international collaborations across multiple continents, with particular focus on African and European conservation challenges. Dr. Santangeli completed his doctoral thesis titled 'Assessing the effectiveness of different approaches to species conservation' at the University of Helsinki in 2013. His educational background established the foundation for his current research program focused on evidence-based conservation strategies and effectiveness assessment. His research interests center on wildlife conservation biology, particularly avian ecology and species protection. Santangeli's work examines human-wildlife interactions, conservation prioritization, and the effectiveness of different conservation approaches. He investigates how climate change affects species distributions and community composition, with special attention to vulture conservation, bird-feeding practices, and the impacts of agricultural systems on biodiversity. His approach integrates ecological, social, and policy dimensions to develop comprehensive conservation solutions. Species conservation effectiveness Human-wildlife interactions Climate change impacts on biodiversity Vulture conservation Bird community dynamics Ecosystem services assessment Analysis of Santangeli's recent publications (2023-2025) reveals a strong focus on interdisciplinary conservation science addressing urgent global challenges. His work increasingly integrates One Health approaches, examining connections between wildlife health, ecosystem functioning, and human activities. Key themes include climate change adaptation strategies, human dimensions of conservation, and technological innovations for monitoring and protection. His research shows growing emphasis on policy-relevant science that directly informs conservation decision-making at multiple scales. His scientific recognition includes an Honorary Fellowship at the University of Cape Town's prestigious FitzPatrick Institute of African Ornithology, part of the DST NRF Centre of Excellence. This position acknowledges his significant contributions to African ornithology and conservation science, particularly his work on vulture conservation across the continent. As a doctoral supervisor, Santangeli guides the next generation of conservation scientists through the Wildlife Biology doctoral program. His research is supported by multiple projects, including the ongoing 'Understanding the drivers and species ecological traits underpinning the global trade in wild birds' (2019-2024), which examines wildlife trade dynamics and conservation implications. His work demonstrates strong international collaboration networks across Europe, Africa, and beyond. Santangeli's research activities involve extensive fieldwork, data analysis, and policy engagement. He participates in academic visits to institutions like the Center d'Études Biologiques de Chizé in France and contributes to scientific conferences and peer review for leading conservation journals. His work often involves citizen science approaches, as evidenced by the 'iratebirds' project on aesthetic attraction to birds.

• Ecology
• Evolutionary Biology
• Wildlife Conservation
• +4 more

Dr. Udayanto Atmojo is a Staff Scientist in the Department of Electrical Engineering and Automation at Aalto University. His research focuses on industrial automation systems, distributed control architectures, and IEC 61499 standard implementation. He holds a doctoral degree in Engineering from the University of Auckland. Research Focus: Distributed control systems using IEC 61499 standard OPC-UA integration for industrial interoperability Cybersecurity in Industry 5.0 environments Digital twin applications in industrial settings His publications demonstrate strong emphasis on industrial automation standards, secure data exchange, and virtual commissioning. Recent work addresses security challenges in human-intensive automated factories and confidential data sharing for life cycle assessments in process industries. Projects and Recognition: Principal investigator for TwinFlow project on distributed control systems (2024-2026) Contributor to CloViC project on cloud virtual commissioning Finalist in World Challenge Finland 2018 competition He develops laboratory test procedures for industrial applications and contributes to open science initiatives including FAIR principles for research software.

• Industrial Automation
• Distributed Control Systems
• OPC-UA Integration
• +3 more

Dr. Sabine Graf is a Full Professor at the School of Computing and Information Systems, Athabasca University. She holds a PhD in Computing and Information Systems from Vienna University of Technology (2007) and has been a faculty member since 2009. Her research focuses on user adaptive systems, learning/academic analytics, personalization, and game-based learning, with over $2.3M in external funding and 130+ peer-reviewed publications (cited 8,200+ times). She leads the OMEGA+ educational game project and the User Adaptive Systems (UAS) research cluster. Education: PhD in Computing and Information Systems, Vienna University of Technology, 2007 MSc in Computing and Information Systems, University of Vienna, 2003 Research Interests: Dr. Graf specializes in making learning systems more intelligent through adaptive interfaces, AI-driven recommendations, and data analytics. Her work bridges educational technology, artificial intelligence, and collaborative learning. Recent projects include developing OMEGA+, analyzing student behavior in online courses, and enhancing adaptive learning systems with context-aware features. Grants & Funding: NSERC Discovery Grant ($205,000), 2020 CFI John R. Evans Leaders Fund ($164,573), 2020 AU IDEA Lab Grant ($5,000), 2021 Multiple Mitacs Globalink Internships, NSERC awards, and AU-funded projects. Advising & Team: Dr. Graf has mentored over 30 students, including PhD, MSc, and postdoctoral fellows. Notable advisees include Moustafa Mahmoud (NSERC Scholar) and Mohammad Belghis-Zadeh (3MT Competition winner). The research team collaborates globally, with members from Brazil, Taiwan, Spain, and beyond. Labs & Initiatives: The Academic Analytics Tool (AAT) project and the OMEGA+ game platform are central to her work. The UAS cluster connects researchers worldwide to advance adaptive systems research.

• Educational Technology
• User Adaptive Systems
• Learning Analytics
• +7 more

Elina Mäkinen serves as Professor of Science, Technology, and Organization at Tampere University's Faculty of Management and Business. She concurrently holds a docentship at the University of Helsinki's Faculty of Social Sciences and serves on editorial boards including the Journal of Organizational Change Management. Her institutional affiliations reflect deep engagement with organizational studies across Nordic academic networks. Her academic background includes a B.Sc. and M.Sc. in Sociology from the University of Helsinki and a Ph.D. in Organization Studies from Stanford University. This foundation supports her research at the intersection of institutional theory and scientific practice. Mäkinen's research centers on interdisciplinary knowledge production, examining how academic careers evolve at disciplinary boundaries. She investigates ethical regulation in science, academic entrepreneurship, and team science dynamics, with particular focus on boundary work and knowledge integration processes. Her work reveals how researchers navigate institutional constraints while pursuing translational science. Analysis of her publication trajectory shows consistent focus on boundary phenomena in science, evolving from early work on clinical recruitment to recent studies of ethical governance. The corpus demonstrates methodological diversity across ethnographic, interview-based, and network analysis approaches within organizational sociology frameworks. As principal investigator, she leads two major projects: The Emergence of Health and Life Science Innovations (HeLSI) and Competing Imaginaries of Ethical Science (IMAGES), funded by the Foundation for Economic Education (2020-2023) and Emil Aaltonen Foundation (2023-2025). These projects examine structural and ethical dimensions of contemporary science. Her laboratory work centers on transdisciplinary collaboration, particularly through the New Social Research unit, where she investigates how researchers build shared epistemic frameworks across disciplinary divides. Current efforts focus on ethical regulation systems in non-medical research contexts.

• Interdisciplinary Science
• Transdisciplinary Science
• Team Science
• +7 more