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Giulio Jacucci is a Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Helsinki Information Technology Research Institute. He serves as a Supervisor in the Doctoral Programme in Computer Science, mentoring PhD candidates in human-computer interaction and related fields. His academic career spans over two decades with continuous research productivity from 2006 through 2025. Professor Jacucci's research interests center on Human-Computer Interaction , particularly focusing on Virtual Reality , Brain-Computer Interfaces , and Neuroadaptive Systems . His work explores how technology can adapt to users' cognitive and physiological states, with significant contributions to social virtual reality environments, embodied agents, and information retrieval systems. He investigates how virtual representations affect social behavior, time perception, and communication in digital spaces. His publication record shows a clear evolution from foundational work in information retrieval toward increasingly sophisticated neuroadaptive systems. Recent publications (2024-2025) demonstrate his leadership in examining social dynamics within virtual reality platforms, including votekicking mechanisms, mirror watching behaviors, and communication tools like mutes. His work bridges technical innovation with deep understanding of human social behavior in digital environments. Professor Jacucci currently leads multiple research projects funded by the Academy of Finland, including DataLit: Datalukutaito ja vastuullinen päätöksenteko (2023-2026) and MyModel: Selitettävyys suositusten hallinnassa (2023-2027). These projects focus on data literacy, responsible decision-making, and explainability in recommendation systems, reflecting his commitment to ethical and user-centered technology development. His research has received media attention, particularly around brain-computer interfaces and virtual reality applications, with coverage in outlets discussing how deep learning transforms mobile applications and sensor landscapes. He has presented his work at major conferences including CHI 2017 and continues to be an active contributor to the international research community.

• Human-Computer Interaction
• Virtual Reality
• Social Virtual Reality
• +4 more

Päivi Eriksson is a Professor of Management at the University of Eastern Finland (UEF) Business School. She co-leads the Innovation Management research group and coordinates the MSCA Neuro-Innovation PhD Programme (2021-2026) and NOVEL Postdoctoral Programme (2024-2029). Her research focuses on innovation management, academic entrepreneurship, and collaborative research methodologies. She leads the Neuro-Innovation and Impact research team within UEF's neuroscience community (NEURO). Key projects include DATASLEEP (2021-2025), CO-RESEARCH (2022-2026), and Shadows in Paradise (2022-2032). Her work bridges academic research with societal impact through initiatives like the Auria Biobank commercialization. She has authored/co-authored over 150 publications in journals like Journal of Affective Disorders , Qualitative Health Research , and International Journal of Human Resources Development . Eriksson's awards include research council grants and contributions to Elgar's Encyclopedia of Innovation Management . She advises on academic entrepreneurship policies and collaborates with 30+ external partners in healthcare, tech, and industry sectors. Her teaching emphasizes innovation empathy and service design frameworks for customer-centric solutions.

• Innovation Management
• Academic Entrepreneurship
• Collaborative Research
• +4 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

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

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

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

• Music Psychology
• Music Education
• Music Therapy
• +7 more

Paul-Christian Burkner is a researcher in the Department of Computer Science at Aalto University. His work focuses on Bayesian statistical methods, computational modeling, and probabilistic programming. He collaborates with Professor Aki Vehtari's research group and has published extensively on topics like model sensitivity, spatiotemporal analysis, and variable selection techniques. His research interests include: Bayesian inference and model comparison Computational statistics Probabilistic programming Machine learning algorithms Statistical modeling in social sciences Neuroimaging data analysis Recent publications demonstrate expertise in simulation-based calibration, spatiotemporal modeling, and Gaussian process approximations. Collaborations span psychology, neuroscience, and machine learning domains. Contact: ext-paul-christian.burkner@aalto.fi

• Bayesian Statistics
• Machine Learning
• Statistical Modeling
• +3 more

Kwantae Kim is an Assistant Professor at the Department of Electronics and Nanoengineering within Aalto University's School of Electrical Engineering . He leads the Tiny Systems and Circuits (TSirc) Group , focusing on power-efficient analog/mixed-signal ICs for biomedical and neuromorphic sensor systems. IEEE Senior Member (2025) Collaborates with institutions across Europe, Asia, and America Specializes in ultra-low-power AI-embedded IoT platforms His research emphasizes Tiny, Sensory, Intelligent, and Wireless IoT systems through: Development of energy-efficient IC architectures Democratizing access to advanced chip design Hardware-software co-design for edge computing Recent publications highlight innovations in: Spoken-language-understanding SoCs Temporal-sparsity-aware keyword spotting Open-source silicon frameworks Awards include: 2025 IEEE Senior Member 2023 Best Poster Award (AICAS) 2019 Samsung HumanTech Silver Award Research partnerships span: Prof. Tobi Delbruck (UZH/ETH Zurich) Prof. Hoi-Jun Yoo (KAIST) Prof. Shih-Chii Liu (UZH) Prof. Sohmyung Ha (NYU Abu Dhabi)

• Power-Efficient Analog/Mixed-Signal Integrated Circuits
• Biomedical Sensor Systems
• Neuromorphic Sensor ICs
• +3 more

Dr. Otto Lappi is a Research Fellow at the University of Helsinki's Department of Digital Humanities, Faculty of Arts. His work bridges cognitive science and human performance in complex dynamic tasks, particularly focusing on predictive processing in visuomotor control. PhD in Cognitive Science Title of Docent at University of Helsinki Academy Research Fellow (2020-2025) His research explores: Cognitive mechanisms in high-speed sports and driving Predictive gaze strategies and steering control Flow states in skill acquisition VR and eye-tracking applications in archaeomusicology Neural substrates of domain expertise Recent publications analyze: Flow-state dynamics in visuomotor learning Predictive gaze behavior in automated driving Computational models of attention in distracted driving Chunking mechanisms in high-speed sports performance Scientific contributions include: Academy Research Fellow (Research Council of Finland) Editorial work on high-performance cognition Organizing cognitive science workshops As doctoral supervisor, he has guided: Samuel Tuhkanen (Predictive Gaze and Steering) Jesse Kuokkanen (Mechanistic Computationalism) Ida Maasalo (Driver Behavior) Markus Mattsson (Psychometrics)

• Cognitive Science
• Human Performance
• Gaze Control
• +3 more

Dubravko Kicic is a Ph.D. Visitor (Faculty) at the Department of Neuroscience and Biomedical Engineering at Aalto University, specializing in advanced brain stimulation techniques and neuroengineering. His work primarily focuses on transcranial magnetic stimulation systems and their clinical applications. Education: Doctoral degree in Engineering and Technology from Helsinki University of Technology (awarded October 20, 2009) Master's degree in Engineering and Technology from Helsinki University of Technology (awarded June 14, 2005) Kicic's research centers on non-invasive brain stimulation technologies, particularly transcranial magnetic stimulation (TMS). His work spans neuroscience, biomedical engineering, and clinical applications for treating neurological and psychiatric conditions. He investigates how to optimize brain stimulation targeting, develop multi-locus TMS systems, and create robotic platforms for precise stimulation delivery. His fingerprint includes expertise in Transcranial Magnetic Stimulation, Behavioral Addiction, Magnetoencephalography, Neuromodulation, Pulse Rate analysis, and Signal Space engineering. Recent publications demonstrate a clear trend toward developing more precise and effective brain stimulation systems. Kicic's work focuses on multi-locus TMS for simultaneous stimulation of multiple brain areas, robotic targeting systems for improved accuracy, and real-time identification of brain states to optimize stimulation timing. His research bridges engineering innovation with clinical neuroscience applications, particularly for depression and pain treatment. Kicic has supervised at least one thesis and has been involved in media coverage regarding how magnetic brain stimulation can help patients with depression and pain. His collaborative work shows extensive international connections in the neuroscience and biomedical engineering fields. His research contributes to UN Sustainable Development Goals related to good health and well-being through developing advanced neurotechnologies for clinical applications.

• Neuroscience
• Biomedical Engineering
• Transcranial Magnetic Stimulation
• +4 more

Tarmo Lipping is a Professor in the Department of Computer Science and Engineering at the Faculty of Information Technology and Electrical Engineering, University of Oulu. His work bridges computing sciences with biomedical engineering, environmental modelling, and data-driven societal applications. Doctor of Science (Technology), Information Technology – Awarded 14 Feb 2001 Master of Science (Technology), Information Technology – Awarded 10 Sept 1993 His research focuses on electroencephalography (EEG) , mental workload assessment , depth of anesthesia monitoring , and machine learning applications in healthcare and human-computer interaction. He also contributes to environmental informatics , particularly in land uplift modelling and radionuclide transport , aligning with UN Sustainable Development Goals. Recent publications highlight trends in transformer networks for EEG analysis , wearable HCI systems , data-driven food safety , and participatory municipal governance . His work integrates deep learning, signal processing, and real-world deployment. Scientific awards include: CIMO opettajavaihto (2017) Lipping has supervised numerous master’s students and served as an examiner in diverse topics including data vault modelling , telecom revenue estimation , and EEG hyperscanning . He has evaluated funding applications, acted as a journal reviewer (65 times), and contributed to editorial work. His activities reflect strong engagement in academic service and interdisciplinary research mentorship. He has contributed datasets on Fennoscandian land uplift , lake isolation , and archaeological shorelines to PANGAEA, supporting open science in geosciences and environmental history.

• Biomedical Signal Processing
• Electroencephalography (EEG)
• Mental Workload Assessment
• +12 more

Tuija Tessaliina Tolonen is a Doctoral Researcher at the Department of Neuroscience and Biomedical Engineering, Aalto University. Her work focuses on neuroimaging, ADHD research, and brain connectivity. Research Interests: Functional and structural connectivity in adult ADHD Impact of early life stress on neural networks Cognitive neuroscience and neuroimaging methodologies Intervention studies with working memory training Selected Publication Trends: Her recent works examine brain network abnormalities in ADHD, neuroplasticity following cognitive training, and the effects of stress on developing brains. Collaborations span neuroscience, psychology, and biomedical engineering fields. Affiliations: Aalto University, Finland.

• Neuroscience
• Biomedical Engineering
• ADHD Research
• +3 more

Mia Liljeström is a Staff Scientist at the Department of Neuroscience and Biomedical Engineering, Aalto University. She holds a Doctoral Degree in Engineering and Technology from Aalto University (2010) and a Master's Degree in Engineering and Technology from Helsinki University of Technology (2002). Doctoral Degree: Aalto University, 2010 Master's Degree: Helsinki University of Technology, 2002 Her research focuses on Magnetoencephalography (MEG) , Functional Connectivity , and Brain Networks . She explores Transcranial Magnetic Stimulation (TMS) , Functional MRI , and Neural Networks to map language-critical brain areas and study cortical dynamics. Recent work includes automated speech artefact removal from MEG data and test-retest reliability of brain connectivity metrics. Mia actively participates in conferences like MEG Nord and has presented invited talks on language processing and large-scale brain networks. Her publications emphasize MEG-informed TMS, cortical beta modulation, and brain stimulation precision. She contributes to the UN Sustainable Development Goal of Quality Education through neuroimaging research.

• Magnetoencephalography
• Functional Connectivity
• Brain Networks
• +3 more

Pentti Juhana Henttonen is an active Researcher at the University of Helsinki, affiliated with the Swedish School of Social Sciences and the Institute of Humanities and Social Sciences. He serves as a Doctoral Researcher in the Doctoral Program in Human Behavior and works as a project planner, contributing to multiple research initiatives focused on human interaction and psychological phenomena. His research interests span cognitive science with particular emphasis on narcissism, sisu (the Finnish concept of inner strength and perseverance), second language acquisition, and physiological responses during social interactions. Henttonen employs diverse methodologies including physiological measurements, conversation analysis, and experience sampling methods to investigate how individuals process emotions, interact with others, and demonstrate mental fortitude in challenging situations. His publication record shows significant activity with 49 publications spanning from 2009 to 2025, with particular concentration in recent years (2023-2025). His work appears across interdisciplinary journals in psychology, linguistics, and social sciences, demonstrating a trend toward increasingly sophisticated methodologies combining physiological measurements with conversational analysis. Recent publications focus on narcissistic traits and their physiological correlates, the cultural phenomenon of sisu, and second language learner behavior. Henttonen actively contributes to the academic community through peer review services for journals including Scientific Reports, BMC Psychology, and Heliyon. He has organized academic events such as the HSSH workshop on motion energy and pose analysis and the HSSH seminar on VR methodology, demonstrating leadership in advancing methodological approaches in social science research. His research is supported through multiple projects funded by institutions including the Academy of Finland (Suomen Akatemia), with his most recent work focusing on patterns in second language learners' behavior (2023-2024) and previous projects examining narcissism (2019-2023) and neighbor dialogues (2018-2020). His work bridges theoretical psychological concepts with practical applications, as evidenced by his media appearances discussing narcissism and sisu for broader public understanding.

• Cognitive Science
• Narcissism
• Sisu (Finnish concept of inner strength)
• +5 more

Pyry Kivisaari is a Postdoctoral Researcher at the Department of Neuroscience and Biomedical Engineering, Aalto University, specializing in computational modeling of optoelectronic semiconductor devices. His work bridges theoretical physics and engineering applications with significant contributions to light-emitting diode and solar cell technologies. His primary research domains include: Optoelectronics and photonics Semiconductor device physics Nanoscale optoelectronic structures Numerical simulation frameworks Light-matter interaction in resonant cavities Efficiency enhancement mechanisms Analysis of his 15 most recent publications (2019-2024) reveals a consistent focus on thin-film and nanoscale optoelectronic devices, particularly examining carrier dynamics, light emission characteristics, and efficiency limitations in LED and solar cell architectures. His work frequently employs advanced simulation techniques to investigate novel device concepts like nanotree LEDs, double diode structures, and thermophotonic systems, with strong emphasis on practical engineering solutions for performance optimization. Dr. Kivisaari maintains active collaboration with leading researchers in semiconductor physics and has published in high-impact journals including Applied Physics Letters, Physical Review Applied, and Nano Letters, demonstrating sustained scholarly productivity in optoelectronic device research.

• Optoelectronics
• Semiconductor Devices
• Photonics
• +4 more