جستجوی استاد راهنمای دانشگاهی

Dr. Arno Solin is a tenured Associate Professor in Machine Learning at Aalto University's Department of Computer Science and an Academy of Finland Research Fellow . He leads the Aalto machine learning research group and serves as Director of the Finnish Doctoral Program Network in AI (AI-DOC) . His work bridges probabilistic modeling with practical applications in sensor fusion and real-time inference. ELLIS Scholar (European Laboratory for Learning and Intelligent Systems) Adjunct Professor at Tampere University Member of Young Academy Finland (2021–2025) Research Interests focus on data-efficient machine learning with probabilistic methods for real-time inference and sensor fusion. Key areas include Gaussian processes, diffusion models, stochastic differential equations, and uncertainty quantification in deep learning. His group develops methods that combine structural constraints with adaptive learning for deployment on resource-limited hardware. Publication Trends show consistent output in top venues (NeurIPS, ICML, ICLR, AISTATS) with emphasis on diffusion models , 3D scene reconstruction , and real-time probabilistic modeling . Recent works explore physics-informed learning, heterophily-aware graph models, and compressed representations for world models in reinforcement learning. Scientific Recognition : Awarded AI Researcher of the Year 2024 by AI Finland Teacher of the Year 2023 at Aalto CS ISIF Jean-Pierre Le Cadre Best Paper Award (2018) MLSP Schizophrenia Classification Challenge Winner (2014) NeurIPS/ICML Reviewer Awards Research Leadership includes coordinating Finland's AI Center of Excellence program and directing the Finnish Doctoral Program Network in AI (AI-DOC). He supervises 15+ doctoral/postdoctoral researchers and has spun off Spectacular AI , a company commercializing sensor fusion technology.

• Machine Learning
• Signal Processing
• Sensor Fusion
• +۸ مورد دیگر

Mohamed Noureldin is an Assistant Professor at the Department of Civil Engineering, Aalto University , Finland, with prior academic roles at Sungkyunkwan University, South Korea (2015–2022). His expertise lies in integrating Artificial Intelligence (AI) with Structural Health Monitoring (SHM) , Structural Digital Twin , Predictive Maintenance , and Seismic Retrofitting . Research Focus : AI-powered sustainable structural design, smart retrofitting, predictive maintenance, structural material innovation, and next-generation performance-based seismic/wind design. Industrial Experience : 20+ years in offshore/onshore structural engineering (Hyundai Heavy Industries, Samsung Engineering, Arab-Swiss Engineering Company, Zuhair Fayez Partnership). Teaching : Courses in structural analysis, seismic design, dynamics, and reinforced concrete at Aalto and Sungkyunkwan Universities. Laboratory : Leads the Structural Design AI Lab (SDAI), focusing on AI-driven resilient infrastructure. Contact : mohamed.noureldin@aalto.fi , +358504544861. His publications explore cutting-edge applications of AI, ML, and DL in seismic retrofitting, structural durability, soil stabilization, and hybrid damping systems. Collaborative work emphasizes life-cycle cost assessment and augmented reality for predictive maintenance.

• Structural Engineering
• Artificial Intelligence in Civil Engineering
• Structural Health Monitoring
• +۵ مورد دیگر

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

• Wireless Communications
• Coding Theory
• Quantum Information Processing
• +۵ مورد دیگر

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

• Machine Learning
• Large Language Models
• Reinforcement Learning
• +۸ مورد دیگر

Jan Akmal is an Assistant Professor at Aalto University, holding dual affiliations in the Department of Energy and Mechanical Engineering and the Materials to Products group. His research specializes in additive manufacturing (AM), focusing on defect detection, smart materials, and 4D printing applications. He leads the AIM-Zero project (2023–2026), exploring AI-driven zero-defect AM processes. Akmal has received the Aalto Doctoral Incentive Scholarship (2023) and an Honorary Award (2023). He serves on editorial boards for Frontiers in Manufacturing Technology and Frontiers in Mechanical Engineering , and chairs the Finnish Rapid Prototyping Association (FIRPA). Key research areas include AI-based defect detection in metal AM, self-sensing components, and hybrid materials for dynamic displays. He collaborates globally on topics like optical tomography in powder bed fusion and medical AM applications. His work addresses sustainability, industrial adoption of AM, and legal frameworks for military logistics. Akmal has authored 24 publications and contributed to datasets on AM inaccuracies and defect classification, emphasizing practical applications and industry integration.

• Additive Manufacturing
• 3D Printing Technology
• Defect Detection
• +۵ مورد دیگر

Reza Ghabcheloo is a Professor at Tampere University, affiliated with the Faculty of Engineering and Natural Sciences and the Department of Automation Technology and Mechanical Engineering. He leads the Robotics major and the international Automation Engineering program. His research focuses on autonomous mobile machines, robotics, control systems, and safety engineering, with specific interests in construction robotics, sensor fusion, and hydraulic systems. He co-leads the Autonomous Mobile Machines Group and is associated with the Robotics and Intelligent Machines Lab and the Innovative Hydraulics and Automation Lab. His research emphasizes developing autonomous systems for off-road machinery, safe control strategies, and energy-efficient automation. He has published extensively on topics such as reinforcement learning for crane control, radar-based perception, and safety architectures for autonomous systems. His work bridges robotics, control theory, and industrial automation, addressing challenges in heavy-duty machinery and real-world robotic applications. Research Group: Autonomous Mobile Machines Group Labs: Robotics and Intelligent Machines Lab, Innovative Hydraulics and Automation Lab Key Projects: Safety of automated off-road machinery, machine learning for autonomous loading, and trajectory optimization

• Robotics
• Automation Engineering
• Control Systems
• +۷ مورد دیگر

Weiwei Lin is an Associate Professor in the Department of Civil Engineering at Aalto University, specializing in structural engineering with a focus on bridge systems, composite materials, and structural health monitoring. His research explores fatigue behavior of steel structures, seismic performance of composite systems, and innovative repair techniques. He holds a PhD from Waseda University (2012), MSc from Southeast University (2009), and BEng from Southwest Jiaotong University (2006). Key research areas include: steel-concrete composites, bridge redundancy evaluation, replaceable energy dissipaters, and AI-driven infrastructure diagnostics. Lin leads projects like CCU Structure (EU Horizon Europe) and RCF Mobility initiatives, focusing on sustainable construction and material recyclability. He has published 120+ peer-reviewed articles and secured 6 major grants. Lin has received prestigious awards including the IABMAS Young Award (2014) and Outstanding Reviewing Award (2017). His lab collaborates globally, hosting researchers from institutions like Israel Institute of Technology and Tsinghua University. Current work emphasizes crowdsourcing-based bridge monitoring and physics-guided AI frameworks for infrastructure diagnostics.

• Structural Engineering
• Civil Engineering
• Materials Science
• +۵ مورد دیگر

Jukka Manner is a Full Professor (tenured) of Networking Technology at Aalto University's Department of Communications and Networking (Comnet), School of Electrical Engineering. With a career spanning over two decades in internet technologies, he leads research in networking, wireless systems, and energy-efficient ICT solutions. Dr. Manner received his MSc (1999) and PhD (2004) degrees in computer science from the University of Helsinki. His academic journey has been marked by significant contributions to internet standardization through the IETF since 1999, where he served as co-chair of the NSIS working group. Professor Manner's research focuses on networking, software and distributed systems, with particular emphasis on wireless and mobile networks, transport protocols, energy efficient ICT and cyber security. His work bridges theoretical advancements with practical applications, addressing critical challenges in modern communication systems, sustainable networking practices, and security frameworks. His research group has made significant contributions to 5G technologies, UAV communications, and energy-efficient network design. His extensive publication record shows a clear evolution toward sustainability in networking technologies, with recent work focusing on energy efficiency in 5G systems, sustainable web technologies, and the environmental impact of digital infrastructure. The research demonstrates strong interdisciplinary connections between telecommunications engineering, computer science, and environmental science, with particular emphasis on reducing the carbon footprint of digital systems while maintaining performance. Cross of Merit, Signals (2014) Medal for Military Merits for contributions in national defence and C4 (2015) Professor Manner has supervised over 200 MSc theses and more than 20 doctoral dissertations, establishing himself as a dedicated mentor in the field. He has been principal investigator and project manager for over 15 national and international research projects, including serving as Academic Coordinator for the Finnish Future Internet research programme (2008-2012). His leadership extends to conference organization, having served as local co-chair of Sigcomm 2012 in Helsinki, and active participation as a peer reviewer and member of various Technical Program Committees. As an active contributor to internet standardization through the IETF, Professor Manner's work has practical impact on global networking technologies. His research group maintains strong connections with industry partners and participates in shaping future networking standards and practices, particularly in the areas of sustainable networking, 5G evolution, and security frameworks for emerging technologies.

• Networking
• Wireless and Mobile Networks
• Transport Protocols
• +۷ مورد دیگر

Yu Xiao is an Associate Professor at the Department of Information and Communications Engineering, Aalto University, specializing in edge computing, extended reality (XR), wearable computing, and crowdsensing. Their research contributes to the UN Sustainable Development Goals, particularly in education and technology innovation. Active in mobile cloud computing and decentralized systems Principal Investigator in EU-funded projects (EMIL, TUTL) Expert in 5G networks, autonomous systems, and human activity recognition Yu Xiao's work spans interdisciplinary domains, including healthcare (cardiovascular resuscitation devices) and urban mobility (autonomous vehicle interactions). They have received multiple awards, including Best Paper Awards and Nokia Foundation Scholarships. Focus on low-latency communication and multiagent reinforcement learning Developed frameworks like FediLive for decentralized social networks Contributed to 128+ publications and software tools Recent collaborations include institutions like Pontificia Universidad Católica de Chile and participation in IEEE committees. Their research integrates blockchain for secure IoT communication and advanced AR applications.

• Edge Computing
• Extended Reality (XR)
• Wearable Computing
• +۷ 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.

• Marine Engineering
• Structural Engineering
• Fatigue and Fracture Mechanics
• +۳ 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.

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

Gökhan Alcan is an Assistant Professor in Robotics and Machine Learning at the Automation Technology and Mechanical Engineering Unit of Tampere University, Finland. He leads the Advanced Learning, Control and AutomatioN (ALCAN) Research Group, focusing on safe model predictive control, constrained optimal control theory, reinforcement learning, and their applications to dynamical systems. His research addresses challenges in robotic manipulation, safe navigation, and human-robot collaboration through projects like the Aurora initiative on automated and connected machines. Education: B.Sc., M.Sc., and Ph.D. in Mechatronics Engineering from Sabanci University (2008–2019). Postdoctoral research at Sabanci University (2019) and Aalto University (2020–2024). Research Interests: Robotics, control theory, system identification, autonomous systems, and machine learning applied to robotic manipulation, autonomous vehicles, and safety-critical systems. Notable work includes trajectory optimization for hybrid systems, magnetic manipulation for medical applications, and sim-to-real gap analysis in cloth manipulation. Awards: Third Place in Aalto Open Science Award 2023, Elginkan Foundation Technology Award (2016), and multiple scholarships. Advised Ph.D. student David Blanco Mulero, who defended his thesis on robotic manipulation of deformable objects. Labs/Teams: ALCAN Research Group, former roles in Aalto University's Intelligent Robotics Group and Sabanci University's Control, Vision, and Robotics (CVR) Group.

• Robotics
• Machine Learning
• Control Theory
• +۵ مورد دیگر

Hamed Badihi is an Assistant Professor in Automation Technology and Dependable Systems at Tampere University , part of the Faculty of Engineering and Natural Sciences. He leads the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group within the Dependable Systems Cyber Laboratories . His research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control to advance sustainable, dependable cyber-physical systems. Research Interests include: Cybersecurity for industrial control systems Fault-tolerant control mechanisms Resilient control strategies for renewable energy systems Condition monitoring of wind turbines and microgrids Recent Contributions emphasize hybrid approaches combining machine learning and control theory for cyber-attack detection and system resilience in wind farms and microgrids. His work addresses challenges like real-time fault diagnosis and adaptive control under adversarial or environmental perturbations. Awards & Roles : Senior Member of IEEE, editor for International Transactions on Electrical Energy Systems , Advances in Fuzzy Systems , and Processes journals. Active in EU projects like StreamSTEP . Labs & Teams : Directs the DARES Group, collaborating on initiatives like the Dependable Systems Cyber Laboratories to pioneer innovations in cyber-physical system dependability.

• Condition Monitoring
• Fault-Tolerant Control
• Attack-Resilient Control
• +۳ مورد دیگر

Professor Jouni Mattila is a leading academic in Machine Automation at Tampere University's Faculty of Engineering and Natural Sciences, affiliated with the Automation Technology and Mechanical Engineering department. He is part of the IHA-Innovative Hydraulics and Automation research group. His expertise spans autonomous mobile working machines, nonlinear control engineering, and safety-critical systems like those in the ITER project. He holds a Technical Editor role in ASME/IEEE Transaction on Mechatronics (2015-2020). Research interests include real-world autonomous systems, whole-body motion control for rough-terrain robots, energy-efficient actuators, and teleoperation systems. His work integrates advanced control theory, AI, and robotics for heavy-industry applications. Recent publications focus on robust control frameworks, LiDAR-inertial SLAM navigation, and fault-tolerant systems for mobile robots. Publications highlight advancements in hydraulic/electromechanical actuator systems, visual-inertial feedback control, and energy-efficient robotics. Awards/recognitions are not explicitly listed, but his contributions are evident through collaborations with Finnish industry and big science projects. Advising focuses on MSc and Dr (Tech) students in robotics and automation, with a mission to bridge academia and industry for high-tech innovation. Labs/teams include the Intelligent Hydraulics and Automation (IHA) group, emphasizing practical R&D in cleantech and heavy-duty robotics. Ongoing projects address challenges in autonomous rock-breaking systems, exoskeleton control, and energy-efficient robotic actuators.

• Machine Automation
• Autonomous Mobile Working Machines
• Heavy-Duty Robotics
• +۴ مورد دیگر

Laura Albareda is a Full Professor of Sustainable Business and Entrepreneurship at LUT Business School, LUT University, Finland. She previously served as Assistant Professor at Deusto Business School (2011–2017) and remains a Visiting Professor there. Her research lies at the intersection of sustainable business, circular economy, and institutional governance, with a focus on collective action and polycentric systems. Her research interests include sustainable business models, corporate social responsibility (CSR), commons organizing (commoning), traceability, and sustainability-oriented innovation. She explores how businesses can regenerate natural ecosystems, particularly through collective stakeholder initiatives in sectors like mining, bioeconomy, and electric mobility. Her work integrates institutional theory and dynamic capabilities to analyze systemic change toward sustainability. The most recent articles reflect a strong trend in studying sustainability transitions through governance, innovation, and stakeholder networks. Key themes include circular economy as collective action, traceability in supply chains, democratic quality in multi-stakeholder governance, and dynamic capabilities for sustainability innovation. Her research spans disciplines such as business ethics, industrial marketing, technological forecasting, and cleaner production, highlighting interdisciplinary engagement. Dexter Award Best International Paper (2019) Best Business Ethics Paper (2019) at the Academy of Management Annual Meeting Distinguished Winner of Responsible Research in Management Award (2023) Laura leads the Academy of Finland-funded project ‘Action4Commons’ (2022–2025) on business and biodiversity in circular economy systems. She is also a principal researcher in EU Horizon Europe projects RELIEF and REINFORCE on sustainable mobility and circular battery models, and PRIMED on bioeconomy living labs. She advises and collaborates with multiple research teams and platforms, including SCI-MAT at LUT University, where she leads research on sustainable and circular business models and value chains. She is actively involved in academic service, including peer reviewing for journals such as Journal of Business Ethics and Humanistic Management Journal . Her work combines theoretical rigor with practical impact, aiming to transform business toward planetary and social well-being.

• Sustainable Business
• Corporate Social Responsibility
• Circular Economy
• +۱۲ مورد دیگر