جست‌وجوی استاد و پژوهشگر

Heikki Remesمشاهده پروفایل

دانشیار

• Marine Engineering
• Structural Engineering
• Fatigue and Fracture Mechanics
• +۳ مورد دیگر

Heikki Remes serves as Associate Professor in the Department of Energy and Mechanical Engineering at Aalto University's School of Engineering, where he investigates high-performance steel structures for marine environments with emphasis on lightweight ship designs using advanced materials and manufacturing techniques. His research integrates fundamental fatigue and fracture mechanics with practical structural challenges, spanning from crystal-level material behavior to continuum-scale modeling. Key focus areas include welded joint integrity, additive manufacturing defects, and computational analysis of marine structures under extreme conditions. Recent publications reveal strong trends in fatigue assessment methodologies for complex welded geometries, experimental validation of distortion effects, and AI-enhanced damage prediction systems, reflecting his commitment to bridging theoretical mechanics with shipbuilding applications. Scientific Awards: Aalto Education Impact Award (2018) for establishing Marine Technology study programs SNAME Honorable Mention for 2018 Vice Admiral E. L. Cochrane Award Teaching Award of Aalto School of Engineering (2012) for educational tools No specific student advising or grant information appears in available sources, though his active publication record indicates ongoing research leadership. He contributes significantly to the Marine and Arctic Technology research group, driving projects on structural integrity assessment and advanced manufacturing solutions for next-generation marine vessels.

• Anomaly Detection
• Microservices
• Software Engineering
• +۲ مورد دیگر

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.

• Software Engineering
• Industrial Automation
• Cloud Computing
• +۷ مورد دیگر

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.

Garg Vikasمشاهده پروفایل

استادیار

• Quantum Computing
• Artificial Intelligence
• Machine Learning
• +۸ مورد دیگر

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.

• Ice Mechanics
• Fracture Mechanics
• Arctic Marine Technology
• +۴ مورد دیگر

Jukka Tuhkuri is a Professor at Aalto University's Department of Energy and Mechanical Engineering, specializing in ice mechanics and arctic marine technology . He serves as Editor-in-Chief of Cold Regions Science and Technology and became an Honorary Professor at University College London (Department of Earth Sciences) in 2023. His work spans numerical simulations using the Discrete Element Method (DEM) and experimental research in the Aalto Ice and Wave Tank, with fieldwork in both Arctic and Antarctic regions. Research Focus : Understanding ice fracture mechanics, sea ice ridge formation, and ice-structure interaction processes. He investigates how global warming alters ice conditions and affects loads on ships/marine structures, addressing risks from increased Arctic shipping activity. Scientific Awards 2023 POAC Founders Lifetime Achievement Award Teacher of the Year 2003 Espoo Ambassador 2012 1996 Best Dissertation Stipend from Helsinki University of Technology Collaborative Impact : His research directly informs offshore wind engineering and Arctic risk management frameworks through publications like Challenges with sea ice action on structures for Offshore wind (2023) and A comprehensive approach to scenario-based risk management for Arctic waters (2022).

Jukka K Nurminenمشاهده پروفایل

استاد

• Efficient Software Systems
• Energy-Efficient Software
• Mobile Peer-to-Peer
• +۶ مورد دیگر

Jukka K Nurminen is a Professor of Computer Science at the University of Helsinki (since 2019) and a Research Professor at VTT. He leads the Empirical Software Engineering research group and supervises doctoral students in the Doctoral Programme in Computer Science. His career spans academia and industry, including roles as Adjunct Professor at Aalto University (part-time, 2016-2021) and Principal Scientist at VTT (2016-2019). His research focuses on efficient software systems , particularly energy-efficient software , mobile cloud computing , and data-intensive systems . Recent work addresses AI system testing , ethical decision-making in software , and quantum computing software . His publications highlight trends in quantum algorithms , machine learning for edge computing , and ethical AI . Best Paper Award (2023) Nurminen has supervised 6 PhD theses, 48 MSc theses, and 21 BSc theses. He has secured over 1 MEUR in research funding, including projects like FrameQ and EM4QS for quantum middleware. His teaching innovations include hackathons and summer schools, with excellence recognized in tenure-track evaluation (2018) and adjunct professorship (2015).

• Industrial Automation
• Distributed Control Systems
• OPC-UA Integration
• +۳ مورد دیگر

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.

• Distributed Energy Resources
• Smart Grids
• Distribution Network Automation
• +۵ مورد دیگر

Sami Repo is a Professor in Electrical Engineering, focusing on power distribution systems and smart energy technologies. His work spans distribution network automation, flexibility services, and integration of distributed energy resources. Doctor of Science (Technology) in Electrical Engineering (2001) Master of Science (Technology) in Electrical Engineering (1996) His research interests include smart grids, congestion management, and cyber-physical energy systems. Recent publications address challenges in electric vehicle charging, green hydrogen regulation, and photovoltaic revenue optimization. He serves as an examiner and doctoral dissertation opponent, contributing to academic evaluation in electrical engineering programs. Key subtopics include EV charging control, EU energy policy, and renewable energy integration. Examiner for Wenlong Liao (2023): Modelling and optimization of active distribution networks Opponent for Etherden Nicholas (2012): Distributed energy resource hosting capacity

• Social Network Analysis
• Network Science
• Human Behavior
• +۳ مورد دیگر

Sara Heydari is a Visiting Professor in the Department of Computer Science at Aalto University , Finland. Her research focuses on analyzing egocentric social networks, human behavior through digital traces, and mobility patterns during disruptions, combining computational methods with social science perspectives.

Teemu Turunen-Saarestiمشاهده پروفایل

استاد

• Energy and Power Engineering
• Renewable Energy
• Sustainability and the Environment
• +۶ مورد دیگر

Teemu Turunen-Saaresti is a Tenured Professor at the School of Energy Systems , LUT University , Lappeenranta, Finland. His research focuses on energy technology, particularly supercritical CO2 cycles, Organic Rankine Cycles (ORC), turbomachinery, and heat pump design. PhD in Energy and Environmental Technology (2004), Lappeenranta University of Technology MSc in Energy and Environmental Technology (2001), Lappeenranta University of Technology His work spans Supercritical CO2 Power Cycles , Organic Rankine Cycle Systems , Turbomachinery Design , and Non-Equilibrium Condensation Modeling . Recent studies include printed circuit heat exchangers for transcritical cycles, high-temperature ORC thermal inertia, and centrifugal compressor design for large-scale CO2 heat pumps. Publications highlight trends in sCO2 Turbines , Tip Clearance Effects , and Multiphase Flow Simulation . Funding from the Academy of Finland and Business Finland supports his research on computational/experimental condensing flows, small-scale compressors, and green shipping energy solutions. He collaborates with international teams on projects like the International Wet Steam Modeling Project , contributing to guidelines for high-temperature heat pumps (IEA HPT Annex 58) and advancements in hydrogen compression strategies.

• Rock Mechanics
• Fracture Mechanics
• Tunneling
• +۴ مورد دیگر

Mikael Rinne serves as Associate Professor in Rock Mechanics within the Department of Civil Engineering at Aalto University, Finland. Holding a Doctor of Science in Technology (D.Sc. Tech.), he brings extensive industry experience from Finnish and Swedish consulting firms (1988-2008) where he specialized in rock engineering and project management for tunneling and geological disposal of radioactive waste. His research focuses on rock and fracture mechanics with direct applications to rock engineering, mining, and tunneling. Current investigations center on digital characterization methods including photogrammetry, videogrammetry, and virtual reality systems for both practical engineering solutions and educational advancement. His work addresses critical challenges in fracture hydro-mechanics, rock mass characterization, and sustainable mining practices. Analysis of his 15 most recent publications (2023-2025) reveals a strong emphasis on digital transformation in rock mechanics. Key trends include non-contact surveying techniques for rock mass characterization, scale effects in fracture properties, and virtual learning environments for engineering education. His research bridges theoretical modeling with field applications in tunneling, mining, and radioactive waste disposal, demonstrating consistent innovation in measurement technologies and computational methods. No scientific awards were mentioned in the source materials. While specific advising details and grant information were not provided, his leadership of the Mineral-based materials and mechanics research group indicates active supervision of graduate students and management of research projects. His industry background suggests strong connections with tunneling and mining sectors for applied research collaboration. He directs the Mineral-based materials and mechanics research group at Aalto University, which develops advanced methodologies for rock characterization and engineering applications. Current initiatives integrate digital tools like smartphone LiDAR, 360-degree cameras, and virtual reality systems to enhance both field practices and educational outcomes in rock engineering.

Henrikki Tenkanenمشاهده پروفایل

استادیار

• Geospatial Analysis
• Urban Planning
• Transportation Accessibility
• +۷ مورد دیگر

Henrikki Tenkanen is an Assistant Professor in the Department of Built Environment at Aalto University, specializing in Geoinformatics. His research focuses on geospatial analysis, urban planning, transportation accessibility, and open data applications for sustainable development. His primary research interests include Geospatial Analysis , Urban Planning , Transportation Accessibility , and Population Dynamics . Tenkanen's work integrates mobile phone data, social media, and open geospatial sources to understand urban environments, accessibility patterns, and carbon emissions. His research contributes significantly to UN Sustainable Development Goals related to sustainable cities and communities. Tenkanen's recent publications demonstrate strong trends in high-resolution spatial analysis of urban environments, with particular emphasis on transport equity , carbon emissions mapping , and rural population representation . His work combines advanced geocomputing techniques with practical urban planning applications, often developing open-source tools to enhance reproducibility and accessibility of geospatial research. As an active member of the academic community, Tenkanen serves as a peer reviewer for journals including Big Data & Society and Environment and Planning B, and participates in conference committees such as the International Conference on Location Based Services. His research has garnered significant attention, with multiple publications featured in news outlets and academic platforms. Tenkanen leads several major research projects including Geo-R2LLM (developing geographic large language models), Geoportti (open geospatial infrastructure), MAPICO (mapping commute-related carbon emissions), and LIH: Location Innovation Hub. His work bridges academic research with practical applications for urban planning and sustainable mobility.

• Software Engineering
• Cyber-Physical Systems
• Digital Ecosystems
• +۳ مورد دیگر

Tero Päivärinta is a Professor at the University of Oulu, Faculty of Information Technology and Electrical Engineering. His work focuses on software engineering, digital ecosystems, and cybersecurity. He specializes in empirical studies of software systems, digital twins, and autonomous driving technologies. His research explores hybrid intelligence systems, data-centric decision-making, and governance of collective ambidexterity in digital initiatives. Education: PhD holder with extensive experience in academic and industry collaborations. Key research domains include cyber-physical systems, DevSecOps automation, and IT governance in public sectors. He co-leads projects such as the NUVE Lab’s vehicle testing frameworks and contributes to initiatives like the Software-Defined Vehicle project. Research highlights include advancing knowledge graphs for manufacturing, cybersecurity compliance in DevOps pipelines, and evaluating data-driven decisions. His articles emphasize interoperability challenges, adaptive systems design, and sustainable digital transformation in public utilities. Professional contributions include organizing the TKTP Annual Symposium and co-editing volumes celebrating academic peers like Markku Oivo. His work bridges theoretical software engineering with practical applications in mobility, governance, and industrial systems.

• Machine Learning
• Bayesian Optimization
• Gaussian Processes
• +۴ مورد دیگر

Ti John is a Research Fellow at Aalto University's Department of Computer Science within the School of Science. He is affiliated with Professor Marttinen's research group and the Probabilistic Machine Learning group led by Professor Samuel Kaski. His work connects with the Finnish Center for Artificial Intelligence (FCAI) and the Helsinki Institute for Information Technology (HIIT). Dr. John's research focuses on machine learning, particularly Bayesian optimization, Gaussian processes, and point process models. His work spans theoretical developments in neural processes and practical applications in healthcare analytics and large language models. He has made significant contributions to equivariant neural processes, causal mediation analysis in healthcare, and interpretability of additive models. His publication record shows consistent output with 17 publications between 2021-2024, including multiple papers at top AI conferences like NeurIPS, ICML, and ICLR. His research demonstrates strong interdisciplinary connections between statistical modeling, artificial intelligence, and healthcare applications. Active reviewer for NeurIPS, ICLR, AISTATS Reviewer for Journal of Machine Learning Research Member of Finnish Center for Artificial Intelligence project Dr. John has been actively contributing to the machine learning community through peer review and conference participation, demonstrating expertise across multiple subfields of artificial intelligence and statistical modeling.

• Digital Transformation
• Responsible Artificial Intelligence
• Foresight Methods
• +۴ مورد دیگر

Matti Minkkinen is a Docent at the Turku School of Economics (University of Turku) and a Postdoctoral Researcher in Information Systems Science at the Department of Management and Entrepreneurship. His work bridges futures studies with ethics, privacy, and socio-technical systems in digital transformation. Recent roles focus on responsible AI governance and foresight methodologies. University: University of Turku School: Turku School of Economics Department: Department of Management and Entrepreneurship His research explores how digital technologies reshape organizational practices, emphasizing Futures Consciousness as a human capacity. Key themes include responsible AI , privacy protection , and causal layered analysis in scenario planning. Publications highlight ethical governance frameworks and EU policy debates. Recent articles address generative AI ethics , ML system integration , and AI auditing across journals like Communications of the Association for Information Systems and Information and Management . Topics cluster around socio-technical systems, digital ethics, and institutional adaptation to AI. Teaching and editorial roles include co-curating student research collections at Finland Futures Research Centre. No explicit scientific awards are listed, but his work contributes to foresight theory and practice.