Find Academic Supervisors

• Marketing
• Consumer Behavior
• Retail Management
• +5 more

Hannu Saarijärvi is a Professor in the Faculty of Management and Business at Tampere University, specializing in Marketing. His research bridges consumer behavior, retail innovation, and data-driven health studies. Based in Tampere University's City Centre Campus, he explores transformative retailing and societal impacts of consumer data. University: Tampere University School: Faculty of Management and Business Department: Business Studies Email: hannu.saarijarvi@tuni.fi His research focuses on consumer behavior in omnichannel and second-hand retailing, data analytics using loyalty card datasets, and health research linking maternal experiences to dietary patterns. Recent studies examine sustainable diets , alcohol consumption dynamics , and food waste reduction . Key article trends highlight loyalty card data applications in health informatics , retail transformation , and sustainability . Collaborative studies with Finnish institutions analyze population-level consumption behaviors, legislative impacts, and digital service innovations. Professor Saarijärvi's work emphasizes value co-creation , customer experience , and strategic digitalization in retail contexts, with practical implications for public health and business models.

Turkka KeinonenView profile

Professor

• Industrial Design
• Human-Centered Design
• Product Concept Design
• +4 more

Turkka Keinonen is a Professor of Industrial Design at Aalto University School of Arts, Design and Architecture, serving as Vice Dean of Research and Head of Doctoral Education. His career spans academic leadership, industry roles in Finnish technology sectors (shipbuilding, medical equipment), and a visiting associate professorship at National University of Singapore. He specializes in human-centered design, product concept design, and ethical considerations in design. Keinonen’s research emphasizes public sector innovation, digital service development, and the intersection of technology with societal needs. His work bridges theory and practice, focusing on how design can foster equity, civic engagement, and sustainability. Recent projects explore libraries as digital innovation hubs, smart home technologies’ ethical implications, and volunteer-based IT services. He has authored influential books including Mobile Usability (2003), Product Concept Design (2006), and Designers, Users and Justice (2017), alongside over 100 publications. Keinonen’s research trends reflect a shift toward relational design in public sectors, emphasizing stakeholder collaboration and systemic change. His articles analyze digital literacy initiatives, quasi-public service models, and design’s role in mediating technological control. He advocates for ethical frameworks that prioritize user autonomy and societal justice in design processes. Labs/Teams: Active in Aalto’s design innovation networks, particularly in public service design and human-centered design methodologies. Collaborates with industry partners (e.g., Nokia Research Center) and Nordic institutions on applied design research.

• Digital Design and Manufacturing (D2M)
• Sustainable Manufacturing
• Optimization Driven Design
• +7 more

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.

• Video Coding
• Machine Learning
• FPGA Acceleration
• +3 more

Jarno Vanne is a Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on video coding standards, real-time systems, and hardware acceleration, particularly in the context of FPGA implementations and open-source tools. He leads projects involving VVC (Versatile Video Coding), V-PCC (Volumetric Video Coding), and HEVC (High Efficiency Video Coding), with an emphasis on efficiency, low latency, and machine learning integration. Key research interests include point cloud compression, saliency-guided encoding, parallelization schemes, and real-time video communication protocols. His work often addresses challenges in multi-party video streaming, embedded systems, and encryption mechanisms for privacy protection. He has contributed to open-source projects like the UVG dataset, Kvazaar encoder, and CiThruS simulation frameworks. Recent publications highlight advancements in VVC intra encoding optimizations, machine learning-driven partitioning schemes, and FPGA-accelerated solutions for edge computing. His research bridges theoretical video coding algorithms with practical implementations, aiming to improve compression efficiency while maintaining real-time performance.

• Digital Signal Processing
• Machine Learning
• Audio Technology
• +8 more

Prof. Vesa Välimäki is an Audio Signal Processing Professor at Aalto University's School of Electrical Engineering, leading the Audio Signal Processing Research Group within the Aalto Acoustics Lab. He also serves as Vice Dean for Research and Head of the Doctoral Programme at the university. His research focuses on digital signal processing, machine learning, and their applications in audio, acoustics, and music technology, particularly in artificial reverberation, audio filter design, and virtual analog modeling. He has pioneered techniques like velvet noise for reverberation synthesis and contributed to open-source tools like FLAMO. His academic accolades include IEEE, AES, and AAIA Fellowships, along with multiple best paper awards at venues like DAFx and ICASSP. He has advised numerous students, including recipients of prestigious awards like the Huawei Master's Thesis Award. Prof. Välimäki has held editorial roles at the Journal of the Audio Engineering Society and organized major conferences such as SMC-17. His work extends to applied projects like acoustic optimization for early childhood education facilities and immersive audio in virtual reality (e.g., the 'Space Walk' project). Key Projects: NordicSMC (Nordic University Hub for Sound and Music Computing), Aalto Acoustics Lab, FLAMO library Grants: NordForsk funding (2018–2023), Foundation for Aalto University Science and Technology His research spans both theoretical advancements (e.g., diffusion models for audio restoration) and practical implementations (e.g., real-time equalizers, headphone compensation systems). He collaborates internationally, contributing to acoustic measurement techniques and noise reduction strategies for diverse environments.

Magnus WesterlundView profile

Senior Lecturer

• Trustworthy AI
• Cybersecurity
• IT Security
• +6 more

Magnus Westerlund is a Senior Lecturer in Information Technology and Director of the Laboratory for Trustworthy AI at Arcada University of Applied Sciences in Helsinki, Finland. His industry background spans telecom and information management, and he holds a doctoral degree in Information Systems from Åbo Akademi University. He actively contributes to the Z-Inspection® network, focusing on ethical AI implementation and governance. Westerlund’s research emphasizes trustworthy AI, cybersecurity, and distributed systems. Key areas include AI regulatory compliance (e.g., EU AI Act), healthcare AI applications, blockchain security, and IoT edge solutions. His work bridges academia and industry, such as the Valohai-CSC collaboration for machine learning infrastructure in Finnish academia. His publications highlight practical AI assessment methods, ethical AI integration, and decentralized technologies. Notable contributions include frameworks for sustainable AI development, privacy-preserving autonomous systems, and smart contract-based IoT security protocols. Westerlund also explores educational innovations, such as integrating large language models (LLMs) into coding education. His research consistently addresses real-world challenges like pandemic-era healthcare AI, edge computing for IoT, and cybersecurity in autonomous systems.

Heikki HandroosView profile

Professor

• Mechatronics
• Robotics
• Machine Automation
• +5 more

Heikki Handroos is a Full Professor of Mechanical Engineering at LUT University, leading the Laboratory of Intelligent Machines since 1993. He holds a DSc (Technology) from Tampere University of Technology and has served as Vice-Dean of the Faculty of Technology (2007-2009) and currently chairs the Collegiate Body of LUT University. His research focuses on mechatronics, robotics, control systems, and fluid power, with over 300 publications and 2,400+ citations. He has supervised 34 doctoral theses and 150+ MSc projects, managed R&D projects exceeding €20M, and co-founded four tech startups. His work spans industrial collaborations, digital twin applications, and innovative robotics for nuclear energy (e.g., DEMO reactor maintenance systems). He has held visiting professorships in the U.S., Japan, and Russia, and actively contributes to academic editorial roles and professional societies like ASME and IEEE.

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

• Sound and Music Computing
• Music technology
• Artificial intelligence
• +8 more

Koray Tahiroglu is a University Lecturer at Aalto University's School of Arts, Design and Architecture, specializing in Sound and Music Computing. His work bridges artificial intelligence, digital musical instruments, and embodied interaction, with a focus on deep learning applications in audio synthesis and human-AI creative collaboration. His research explores New Interfaces for Musical Expression (NIME), sonic interaction, and physical computing. He collaborates with SOPI Research Group and Google Brain Team (Magenta) on AI-driven artistic innovation. Recent Publications : 2024 studies on dance-sound cross-correlation and intra-action frameworks; 2023 work on AI-terity and deep learning syllabi; 2022 explorations of GAN synthesis, musical expectations, and lifeworld sonification. Scientific Awards : Co-Creative Artificial Intelligence of Music (2022) 2010 grant for scientific publications and artistic activities 2017 Honorable Mention for mobile cultural heritage research Tahiroglu contributes to digital art education and leads projects at Media Lab Helsinki, advancing sonic interaction and generative audio systems.

Joel MeroView profile

Associate Professor

• B2B Digital Marketing
• Digital Data Analytics
• Marketing Agility
• +4 more

Joel Mero is an Associate Professor at the School of Business and Economics, University of Jyväskylä , leading the Digital Marketing and Communication (DMC) research group and directing the International Master's Program in Digital Marketing and Corporate Communication (DMCC) . He holds a D.Sc. (Econ.) from Jyväskylä University (2016) and has designed over 20 courses across 10 institutions, covering all academic levels from Bachelor to Doctoral. His research focuses on B2B digital marketing management , particularly leveraging digital data and technologies in business markets. Notable achievements include two Best Paper Awards (2017 & 2019) in the Industrial Marketing Management journal. His work explores topics such as influencer marketing, big data analytics, marketing agility, and AI-driven strategies. Current research groups include the Sound Science Lab (music perception) and Digital Marketing and Communication (DMC) . He collaborates on projects like the Finnish Quantum Flagship , aiming to advance quantum technology applications. Mero emphasizes practical applications of digital tools, bridging academic insights with industry needs. Publications span conceptual frameworks, empirical studies, and industry guides, with a focus on B2B customer journeys, AI in content creation, and data-driven decision-making. His teaching and research highlight agility, innovation, and the ethical use of emerging technologies in marketing.

Pia FrickerView profile

Associate Professor

• Computational Methodologies
• Urban Design
• Landscape Architecture
• +8 more

Prof. Pia Fricker is an Associate Professor and Vice Head of the Department of Architecture at Aalto University's School of Arts, Design and Architecture in Finland. She holds the Professorship of Computational Methodologies in Landscape Architecture and Urbanism, directing the Urban Studies and Planning Programme. Her research integrates urban design, landscape architecture, and digital design culture, focusing on data-driven methods, immersive environments, and adaptive urban development. Collaborations include ETH Zurich, Singapore University of Technology and Design, and Hafencity University Hamburg. Key projects include the Metaversity and Future Smart Cities initiatives. Fricker has led over 80 publications and exhibitions globally, including at the Venice Biennale and National Design Centre Singapore. She is an editorial board member for the Journal of Digital Landscape Architecture and peer reviewer for multiple journals. Awards include the Digital Landscape Architecture Award (2018) and DLA Scientific Merit Award (2021). Her teaching emphasizes computational pedagogy and digital innovation in design education. Education: PhD in Architecture (ETH Zurich, 2021) Postgraduate in Didactics (ETH Zurich, 2011) MAS in Computer Aided Architectural Design (ETH Zurich, 2003) MSc Arch in Urban Design & Landscape Architecture (Technical University of Karlsruhe, 2001) Research Interests: Computational design, parametric modeling, mixed reality, climate-adaptive ecosystems, generative AI, and sustainable urban development. Her work bridges emerging technologies with ecological and urban challenges, emphasizing interdisciplinary collaboration. Grants & Projects: Metaversity (2023–2025, Principal Investigator) Future Smart Cities Sasakawa (2023–2024, Principal Investigator) ABRA (2020–2023, Project Member) Awards: DLA Awards (2018, 2021) DLA Review Committee Awards (2020–2022) Exhibition Recognitions (Venice Biennale, National Design Centre Singapore) Labs/Teams: Leads the Urban Studies and Planning Programme and collaborates with interdisciplinary teams on projects like the RAILCORRIDOR Singapore initiative. Active in digital twin development and AI-driven design tools.

• Software Engineering
• Industrial Automation
• Cloud Computing
• +7 more

David Hästbacka is an Associate Professor (tenure track) at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on software engineering, industrial automation, and energy systems, emphasizing system architecture, interoperability frameworks, and dependable IoT solutions. He leads a research group exploring edge and cloud computing, semantic integration, and smart energy systems. Education & Professional Background : While specific educational details are not provided, his academic career includes roles such as Postdoctoral Researcher in the SEMIS project (2017-2020) and extensive involvement in EU-funded initiatives like COCOP (EU H2020) and Horizon Europe projects. Research Projects : Active in high-impact projects like Hedge-IoT (Horizon Europe, 2024-2027), TwinfFlow (Business Finland), and TRINEFLEX (Horizon Europe), with a focus on industrial automation, distributed systems, and energy grids. Past projects include FEMMa (Business Finland), DisMa (Academy of Finland), and Arrowhead (ECSEL). Teaching & Supervision : Specializes in Web/Cloud architectures, IoT systems, and dependable automation technologies. Supervises students in topics like edge computing frameworks and MLOps pipelines. Technical Contributions : Develops frameworks for industrial interoperability (e.g., OPC UA PubSub integration), edge-cloud toolchains, and MLOps methodologies. His work addresses challenges in microservices, Kubernetes distributions, and semantic data integration. Labs & Teams : Leads a research group advancing automation technologies through interdisciplinary collaboration, with partnerships in industry and academia to bridge theory and practice in smart systems.

Eric CoataneaView profile

Professor

• Manufacturing Systems
• Additive Manufacturing
• Causal Graphs
• +5 more

Eric Coatanea is a Professor at Tampere University, affiliated with the Automation Technology and Mechanical Engineering department within the Faculty of Engineering and Natural Sciences. His research focuses on manufacturing systems, causal graph networks, multi-disciplinary optimization, and AI integration in engineering design. He holds a BSc from University of West Brittany (1990), MSc from INSA Toulouse (1993), and teaching certification from Ecole Normale Supérieure (1994). Research interests include modeling manufacturing systems, additive manufacturing (e.g., Directed Energy Deposition), causal graphs for decision-making, and systems engineering. Notable awards include the Chevalier des Palmes Académiques (2018) and Marie-Curie Fellowship (2006–2008). Recent publications emphasize optimization algorithms combining AI (e.g., L-ANN-GWO), viscosity effects in 3D printing, and causal graph applications in MDO. His work bridges theoretical frameworks with practical engineering challenges, focusing on early design synthesis and sustainable manufacturing. Commitments include editorial roles (Journal of Integrated Design & Process Science), NSERC Canada advisory, and board memberships (Dynavio Cooperative Oy, Selko Oy). Current projects include LILIAM, ÄVE, and DIGITBrain initiatives.

• Superconductivity
• High-Field Magnets
• Particle Accelerators
• +3 more

Tiina Salmi is an Academy Research Fellow specializing in superconductivity and high-field magnet systems. She holds a Doctor of Science (Technology) in Electrical Engineering (2015) and a Master of Science in the same field (2009). Her research focuses on quench protection systems, superconducting magnet design for particle accelerators (e.g., Future Circular Collider, Muon Collider, and LHC upgrades), and material behavior under extreme conditions. Affiliations: Academy of Finland, collaborating with institutions like CERN and LARP. Key Projects: FCC dipole development, Muon Collider storage ring magnets, and HTS tape mechanical analysis. Editorial Roles: Editorial board member for IEEE Transactions on Applied Superconductivity (2020–present). Research Interests Her work addresses critical challenges in superconducting magnet technology, including quench dynamics, thermal management, and high-field stability. She employs computational models (e.g., FEM simulations) and AI-driven approaches to optimize magnet performance and safety. Recent focus areas include: Superconducting materials (Nb 3 Sn, ReBCO, HTS) under mechanical/thermal stress CLIQ protection systems for FCC-hh dipoles Surrogate models for predicting heater delays Mechanical behavior of 2G HTS tapes Grants & Activities Active in international collaborations like the Muon Collider Project and the LARP (LHC Accelerator Research Program). Conducted over 80 peer-reviewed publications (2011–2025) and presented at conferences since 2013. Her work aligns with SDGs 9 (Industry, Innovation) and 12 (Sustainable Consumption). Future Work Ongoing projects include optimizing superconducting magnets for next-gen colliders and advancing AI applications in magnet design. Exploring sustainable materials and cost-effective high-field magnet solutions for future accelerators.

• Educational Sciences
• Theatre, Dance, and Music Education
• Artificial Intelligence in Education
• +3 more

Lauri Väkevä is a Professor in the Department of Education at the University of Helsinki, specializing in educational sciences with a focus on performing arts, music education, and STEAM pedagogy. He actively supervises doctoral students in the Doctoral Programme in School, Education, Society, and Culture and leads the SKAPA project (2024–2026) on developing study paths in arts education. His research explores the intersection of artificial intelligence, creativity, and multimodal learning environments. Key Affiliations: Department of Education, Sibelius Academy collaboration, Gaudeamus publishing network Research Themes: AI in music education, safe spaces for artistic expression, responsible AI pedagogy, historical evolution of Finnish music institutions Recent Work Highlights : 2025: Generative AI as a Collaborator in Music Education (Action-Network Theory application) 2025: Voicing Responsible AI Pedagogy (Ethical frameworks for arts education) 2024: Changing Role of Sibelius Academy (Historical analysis of Finnish music education) Leadership & Engagement : Project Manager for SKAPA, organizing committee member for the 2024 Ainedidaktinen Symposium, and active participant in AI research events.