جستجوی استاد راهنمای دانشگاهی

• Ambient Intelligence
• Radio Frequency Sensing
• 5G Networks
• +۳ مورد دیگر

Dariush Salami is a Postdoctoral Researcher at the Department of Information and Communications Engineering, Aalto University. With expertise in Radio Frequency Sensing and 5G Networks , his work bridges mmWave Radar applications with Ambient Intelligence systems. Research Focus: mmWave Radar Integration, 5G-NR, Reinforcement Learning Scientific Recognition: Nokia Foundation Scholarship , HPY Research Foundation Grants His recent publications demonstrate novel approaches to human-centric sensing , gesture recognition , and energy-efficient UAV communications . Current projects include radar-communication co-design and water quality monitoring using wireless sensing technologies. Contact: dariush.salami@aalto.fi

• Artificial Intelligence
• Machine Learning
• Collaborative Systems
• +۱ مورد دیگر

Jessica Rosenberg is a University Teacher (Lecturer) at Aalto University in Finland, specializing in technology-driven academic roles. Her contact email is jessica.rosenberg@aalto.fi, and she is associated with the U410 Joint Learning initiative. Her research centers on Artificial Intelligence and Machine Learning, particularly collaborative systems where multi-agent learning frameworks intersect with educational technology. The U410 Joint Learning project indicates active work in developing cooperative learning methodologies for complex system applications. No scientific awards, student advisement records, or laboratory affiliations are documented in the available profile.

Konstantina Olioumtsevitsمشاهده پروفایل

پژوهشگر

• Machine Learning
• Artificial Intelligence
• Computer Science

Konstantina Olioumtsevits is a Postdoctoral Researcher at the Department of Computer Science, Aalto University, affiliated with Professor Alexander Jung's research group. Her work focuses on machine learning and computational linguistics. Research Interests: Konstantina's research spans machine learning terminology, educational tools for AI, and interdisciplinary applications of artificial intelligence in computer science. She contributes to the Aalto Dictionary of Machine Learning project, aiming to standardize ML concepts. Publications: Her recent work includes the 2024 preprint 'The Aalto Dictionary of Machine Learning,' which addresses foundational challenges in ML by creating a standardized taxonomy. This publication reflects her interest in bridging theoretical and applied aspects of AI.

• Machine Learning
• Bioinformatics
• Precision Medicine
• +۳ مورد دیگر

Heli Julkunen is a Postdoctoral Researcher in the Department of Computer Science at Aalto University, Finland, specializing in machine learning applications for biomedical research. Her work bridges computational methods with healthcare challenges, particularly in precision medicine and drug discovery, with publications in high-impact journals including Nature Communications and Bioinformatics. Her research focuses on developing advanced computational models for disease risk prediction using large-scale biobank data, multi-way interaction modeling for drug combination effects, and scalable nonlinear regression techniques. She employs kernel methods, tensor reconstruction, and machine learning algorithms to analyze complex biological datasets, emphasizing predictive accuracy and computational efficiency in high-dimensional spaces. Analysis of her 2018-2025 publications reveals consistent innovation in biomedical machine learning, with significant contributions to precision medicine through UK Biobank-based disease prediction and to drug discovery via kernel-based bioactivity modeling. Her work demonstrates strong interdisciplinary collaboration with researchers like Juho Rousu and Tero Aittokallio, targeting real-world applications in healthcare analytics and therapeutic development.

• Computer Science
• Signal Processing
• Remote Sensing
• +۳ مورد دیگر

Luca Ferranti is a Visiting Doctoral Researcher at Aalto University's Department of Computer Science. His work focuses on signal processing, sensor networks, and navigation systems leveraging Low Earth Orbit (LEO) satellites. Research Interests: His studies address challenges in Visual localization and precision engineering LEO satellite-based positioning Sensor network calibration Time difference of arrival (TDOA) methods Confidence estimation in localization Homotopy continuation algorithms Publications Trends: His research spans 2020-2023 with emphasis on LEO satellite applications Acoustic and optical sensor networks Self-calibration techniques Dataset creation for localization Mathematical modeling for positioning Signal processing algorithms

• Industrial Engineering
• Education
• Personality Analysis
• +۳ مورد دیگر

Jaakko Korhonen is a Postdoctoral Researcher at the Department of Industrial Engineering and Management, Aalto University. His work spans interdisciplinary domains, focusing on education, personality analysis, and sentiment modeling. Affiliation: Aalto University Department: Industrial Engineering and Management Research Interests: Korhonen's research explores academic teaching methodologies, student well-being, and multidimensional sentiment analysis. He investigates learning environments and their impact on engineering education, while also contributing to philosophical education frameworks and telecommunications applications. Publication Trends: His recent articles emphasize educational innovation and psychological modeling, while older works address transportation safety and infrastructure economics. Collaborations with Esa Saarinen and Timo Honkela highlight his interdisciplinary approach.

• Microrobotics
• Acoustic Manipulation
• Machine Learning
• +۴ مورد دیگر

Artur Kopitca is a Researcher at the Department of Electrical Engineering and Automation of Aalto University, affiliated with the Robotic Instruments research group. His work focuses on advanced robotic manipulation techniques at micro and macro scales. Research interests include: Acoustic manipulation and programmable assembly Machine learning applications in robotics Stochastic force field control systems Jet-induced airflow dynamics for automation Recent publications highlight his contributions to integrating large language models with microrobotics, model-based learning control, and programmable particle assembly using Chladni plates. His work bridges robotics, control theory, and acoustic engineering. Email: artur.kopitca@aalto.fi

• Robotics
• Micromanipulation
• Biomedical Engineering
• +۲ مورد دیگر

Houari Bettahar serves as an Academy Research Fellow at Aalto University within the School of Electrical Engineering and Department of Electrical Engineering and Automation. His research profile is hosted by Aalto University, with contact details including email houari.bettahar@aalto.fi and phone +358504440301. Dr. Bettahar's research spans Robotics, Micromanipulation, and Biomedical Engineering , focusing on precision manipulation at micro/nano scales. Key areas include: Development of robotic systems for fiber fabrication and cell adhesion studies Creation of low-cost platforms like FilMBot for high-speed micromanipulation Integration of AI and computer vision for robotic control optimization Electromagnetic manipulation of particles for biomechanical analysis Biomimetic approaches to material property enhancement Analysis of his 15 most recent publications (2020-2025) reveals a dominant focus on robotic micromanipulation applied to fiber-based systems and biological interactions. His work consistently integrates electromagnetic actuation , soft robotics , and Bayesian optimization to solve challenges in material science and biomedical engineering, with notable emphasis on cost-effective instrumentation and real-time force control. No scientific awards were mentioned in the provided text. Information regarding student advising and research grants was not found in the provided materials. Dr. Bettahar is affiliated with the Robotic Instruments research group at Aalto University, which specializes in developing robotic solutions for microscale manipulation challenges across biomedical and industrial applications.

• Computational Chemistry
• Materials Science
• Surface Science
• +۳ مورد دیگر

Joakim Jestilä serves as a Postdoctoral Researcher at Aalto University within the Department of Chemistry and Materials, actively contributing to the Inorganic Materials Modelling research group. His work integrates computational and experimental approaches to investigate atomic-scale material behaviors, with emphasis on surface phenomena and molecular interactions. Research interests span computational chemistry, quantum physics, and machine learning applications in materials characterization. Key focus areas include carbohydrate self-assembly mechanisms, quantum spin systems in molecular rings, and lignocellulosic biomass adsorption. His methodologies combine scanning probe microscopy with deep learning for precise surface analysis, bridging theoretical modeling and experimental validation in nanoscale science. Recent publications demonstrate interdisciplinary impact across chemistry, physics, and computer science domains. Work on chirality transfer in carbohydrates reveals stereochemical principles governing self-assembly, while quantum ring studies uncover many-body degeneracy phenomena. Machine learning applications enable accelerated adsorption structure determination and precise chemical transformations, highlighting convergence of AI with experimental surface science. As part of Aalto University's Inorganic Materials Modelling group, Jestilä collaborates extensively with international researchers including Adam Foster and Peter Liljeroth. His work supports advanced materials design through fundamental insights into molecular interactions and surface processes, with implications for renewable energy and nanotechnology applications.

• Remote Sensing
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Florent Guiotte serves as a Lecturer and Postdoctoral Researcher within the Department of Computer Science at Aalto University's School of Science, holding formal status as a Visitor (Faculty). He is actively embedded in the Laaksonen Research Group, contributing to interdisciplinary projects at the intersection of computer vision and environmental science. His research spans Remote Sensing , Computer Vision , and Environmental Monitoring , with concentrated expertise in Hyperspectral Imaging and LiDAR Processing for forest ecosystems. Recent work develops advanced techniques for boreal forest analysis including super-resolution methods and individual tree detection algorithms, demonstrating strong technical innovation in geospatial data interpretation. Guiotte's 2024 publication output reveals consistent focus on applying computer vision to environmental challenges, with both IGARSS papers addressing critical forest monitoring needs through novel image processing approaches. His work shows clear progression in developing practical solutions for ecological assessment using remote sensing technologies. Collaborating closely with Professor Jorma Laaksonen's team, Guiotte contributes to Aalto's research ecosystem through joint publications with multidisciplinary co-authors. His position bridges academic instruction and active research, providing students exposure to cutting-edge environmental data analysis techniques. The Laaksonen Research Group offers a dynamic environment for geospatial AI development, with Guiotte's work strengthening the group's capabilities in environmental applications. His focus on boreal forest monitoring aligns with Finland's ecological priorities, creating opportunities for field-relevant research in forest management and climate change assessment.

• Operations Management
• Supply Chain Management
• Design Science
• +۵ مورد دیگر

Jan Holmström is a Professor in the Department of Industrial Engineering and Management at Aalto University, Finland. His research focuses on technology-enabled innovation in operations management through product modeling, direct digital manufacturing, and intelligent product technologies. He collaborates with computer scientists and engineers to develop novel supply chain approaches for industrial and healthcare contexts. Holmström's primary research spans Operations Management, Supply Chain Management, Design Science, and Future Industrial Services. His work investigates digital transformation in logistics, including tracking and tracing systems, Building Information Management, and intelligent products. Key applications include electronic grocery retailing, spare parts provision, and healthcare supply chains, with emphasis on how additive manufacturing reshapes service operations and supply chain resilience. His recent publications (2024-2025) reveal strong trends in healthcare-focused additive manufacturing, digital service ecosystems for spare parts, and machine learning applications in production planning. Critical themes include co-evolution of digital service providers, product-service systems for homecare medication, and uncertainty modeling using possibility theory in volatile supply chains. Holmström's accolades include: Associate Editor Service Award, Journal of Operations Management (2020) Honorable Mention for Best Paper ('Improving home care'), Journal of Operations Management (2017) Honorable Mention for Reviewing Service, Journal of Operations Management (2018) Invited to Best Paper Proceedings, Academy of Management Annual Meeting (2006) Emerald Literati Club Highly Commended Award (2003) Schenker's Best Paper Award, Nofoma (2004) Citation of Excellence Award, Emerald Management Review Board (2005) While specific student supervision details are unreported, his editorial roles at the Journal of Operations Management and extensive publication record indicate active PhD mentoring and successful grant acquisition for interdisciplinary projects involving computer science and engineering collaborations. Holmström leads cross-disciplinary teams with construction/mechanical engineers and computer scientists, particularly in additive manufacturing and digital supply chain initiatives, though formal lab structures aren't specified in source materials.

• Machine Learning
• Deep Reinforcement Learning
• Autonomous Driving
• +۳ مورد دیگر

Vesa Hirvisalo is a Senior Lecturer in the Department of Computer Science at Aalto University. His professional profile shows active involvement in research related to computing systems and artificial intelligence. Research Focus: His work primarily addresses machine learning applications in autonomous systems, real-time processing, and heterogeneous computing environments. Publications highlight expertise in deep reinforcement learning, computer vision, and industrial informatics. Recent Publication Trends: His research output demonstrates a strong focus on deep reinforcement learning for task scheduling, autonomous driving environments, and optimizing convolutional neural networks for mobile applications. Collaborations span academic and industrial domains. Professional Contact: Email: vesa.hirvisalo@aalto.fi

• Machine Learning
• Health Informatics
• Transportation Modeling
• +۴ مورد دیگر

Jaakko Hollmen serves as a Senior University Lecturer in the Department of Computer Science at Aalto University, affiliated with the Helsinki Institute for Information Technology (HIIT) and the Computer Science Lecturers research group. His interdisciplinary work bridges machine learning with critical applications in healthcare, transportation systems, and environmental science. His research focuses on advanced machine learning methodologies including Bayesian optimization, random forests, and principal component analysis. Key application areas span neonatal healthcare (mortality prediction, brain injury analysis), transportation modeling (activity-based model calibration), and environmental data science (weather-crop relationships, drug-environment interactions). His approach emphasizes practical implementations of complex algorithms for real-world problems. Hollmen's recent publications (2018-2023) reveal a consistent trajectory in developing machine learning solutions for high-dimensional data challenges, with increasing emphasis on medical applications. His work demonstrates strong cross-domain collaboration, particularly with medical researchers at Helsinki University Hospital. His notable recognition includes: Best paper finalist and runner-up award (Computer Track) at the first IEEE Life Sciences Conference (LSC) for research on predicting complications in very low birth weight infants (2017) As a core member of HIIT, Hollmen contributes to Finland's national information technology research infrastructure while maintaining active collaborations with medical and agricultural research groups. His current projects focus on optimizing transportation models and advancing clinical prediction systems through novel machine learning techniques.

• Biochemistry
• Biomedical Engineering
• Materials Science
• +۳ مورد دیگر

Janne Laine is a Researcher at Aalto University's Department of Bioproducts and Biosystems. They received the Aalto Research Impact Award in 2022 for their work at the Aalto University Bioinnovation Center, which focuses on advancing bio and circular economy through technologies like Ioncell® and eco-sustainable textiles. Research Interests: Their work spans interdisciplinary areas including nanomaterials for drug delivery, biopolymer composites, oxidative stress in neurodegenerative diseases, and sustainable materials engineering. Recent studies involve cancer therapy, biofuel feedstock production, and environmental remediation. Scientific Awards: Aalto Research Impact Award (2022)

• Robotics
• Computer Vision
• Machine Learning
• +۴ مورد دیگر

Francesco Verdoja is a Research Fellow at Aalto University's Department of Electrical Engineering and Automation, specializing in robotics and computer vision. His work focuses on safe trajectory generation, localization in dynamic environments, and visual-language semantic mapping. He actively contributes to the Intelligent Robotics research group and has received multiple accolades for his research. Research Interests : Robotics, Computer Vision, Machine Learning, Human-Robot Interaction Key Contributions : Visual-language maps, Dynamic environment modeling, Safer robot navigation frameworks Scientific Achievements : 2024 IEEE/RSJ IROS Best Safety Paper finalist 2022 Best Paper Award PhD scholarship from Sisvel Technology Academic GPU Grant (NVIDIA Titan Xp) Recent publications demonstrate strong emphasis on robotic perception and autonomous navigation , with applications in UAV localization, deformable object manipulation, and people flow prediction. Collaborations include work with Prof. Ville Kyrki and other robotics experts at Aalto University.