جستجوی استاد راهنمای دانشگاهی

Tomasz Kucnerمشاهده پروفایل

استادیار

• Robotics
• Autonomous Systems
• Machine Learning
• +۵ مورد دیگر

Dr. Tomasz Kucner is an Assistant Professor in the Department of Electrical Engineering and Automation at Aalto University, specializing in robotics and autonomous systems. His research focuses on enabling robots to operate safely and intelligently in human-robot shared environments through contextual learning, self-assessment, and understanding human behavior dynamics. His work emphasizes multi-modal perception, trajectory prediction, and human-aware navigation. Key projects include the ILIAD Safety Stack for industrial mobile robots and development of datasets like THÖR-MAGNI for motion capture analysis. He collaborates with institutions globally and leads the Mobile Robotics research group. Publications highlight advancements in radar-lidar fusion, pedestrian intent prediction, and generative terrain modeling. His work bridges theoretical robotics research with practical applications in autonomous driving and service robotics. Research Group: Mobile Robotics Key Focus Areas: Human-Robot Interaction, Autonomous Systems, Motion Prediction

Kalle Alaluusuaمشاهده پروفایل

پژوهشگر

• Network Analysis
• Machine Learning
• Data Science
• +۵ مورد دیگر

Kalle Alaluusua is a Doctoral Researcher at the Department of Mathematics and Systems Analysis within the School of Science at Aalto University. His research focuses on network analysis, hypergraph clustering, and Bayesian methods for multilayer networks. He has contributed to advancements in stochastic block models and similarity matrix techniques. Education details are not explicitly listed, but his doctoral work aligns with the university's mathematical statistics and data science programs. His recent publications include work on multilayer hypergraph clustering and Bayesian community recovery in networks, presented at conferences like WAW and IEEE International Symposium on Information Theory. He is affiliated with the Mathematical Statistics and Data Science research group and can be contacted via email . His ORCID identifier is 0009-0009-9136-5649 .

Kai Virtanenمشاهده پروفایل

استاد مدعو

• Operations Research
• Decision Analysis
• Discrete-Event Simulation
• +۵ مورد دیگر

Kai Virtanen is an Adjunct Professor in the Department of Mathematics and Systems Analysis at Aalto University's School of Science. He also serves as a Senior Scientist in Operations Research and Systems Analysis. His research focuses on dynamic multi-objective decision making under uncertainty, human performance in complex systems, and applications in military and aviation contexts. He holds a Doctoral degree in Engineering from Helsinki University of Technology. Research interests include optimization, decision analysis, simulation, Bayesian networks, and game theory applications. He has led projects involving air combat simulation, radar defense systems, and maintenance scheduling. Virtanen has received awards such as the Operations Researcher of the Year (2015) and Teacher of the Year honors (2007-2008, 2011). Key contributions span over 90 publications in journals like Journal of Defense Modeling and Simulation and European Journal of Operational Research . His work addresses challenges in air combat tactics, pilot decision-making, and system reliability. Current projects involve federated learning applications in military coalition operations and unmanned systems optimization. Academic service includes chairing the Systems Analysis Section of Finland's Scientific Advisory Board for Defense. Teaching focuses on systems analysis, simulation, and optimization methods.

• Mechanical Engineering
• Nonlinear Dynamics
• Fluid-Structure Interaction
• +۳ مورد دیگر

Seyedmorteza Khoshroo serves as a Postdoctoral Researcher (Research Fellow) in Automation and Mechanical Engineering, focusing on nonlinear dynamics of mechanical systems with emphasis on drill string mechanics and fluid-structure interaction. His research bridges theoretical mechanics with practical engineering challenges in drilling operations. Dr. Khoshroo's core expertise spans Mechanical Engineering, Nonlinear Dynamics, and Fluid-Structure Interaction, with specialized work in Drill String Dynamics and Structural Dynamics. His methodological approach combines perturbation techniques (including multiple-scale analysis), probabilistic modeling, and numerical integration to analyze complex behaviors under supercritical flow regimes, axial loads, and uncertain conditions. Between 2018-2022, he published four significant articles demonstrating evolving research focus: starting with reinforcement learning control of inverted pendulums (2018), progressing to nonlinear behaviors of spinning pipes with pulsation (2021), and culminating in two 2022 studies on drill string dynamics under axial loads and probabilistic uncertainty analysis. This trajectory shows increasing specialization in drilling mechanics with growing methodological sophistication. Collaborating primarily with M. Eftekhari, Dr. Khoshroo maintains active research output with practical applications in oil/gas extraction. While no dedicated laboratory is specified, his computational research requires advanced numerical modeling capabilities. His work contributes to improving drill string reliability through predictive modeling of failure mechanisms under complex operational conditions.

Tomi Janhunenمشاهده پروفایل

استاد

• Knowledge Representation and Reasoning
• Answer Set Programming
• Satisfiability Checking
• +۶ مورد دیگر

Tomi Janhunen is a Professor in Computing Sciences at Tampere University, specializing in knowledge representation, automated reasoning, and logic programming. He previously served as Adjunct Professor at Aalto University (2019–2024) and maintains a Doctor of Science (Tech.) degree. His research spans answer set programming, satisfiability checking, optimization, and distributed computation. PhD, Aalto University (Doctor of Science (Tech.)) Adjunct Professor of Computer Science (Aalto University, 2019–2024) His research focuses on Answer Set Programming (modularity, verification, optimization), Satisfiability Modulo Theories , Nonmonotonic Logics , and Computational Complexity . He integrates logic programming into real-world applications like preventive maintenance scheduling and AI security systems. Recent work includes translating logic programs into integer programming, developing probabilistic reasoning systems (Plingo), and creating interpretable classifiers for tabular data. His publications emphasize stable model semantics , optimization techniques , and constraint networks . He supervises M.Sc., Lic.Sc., and Ph.D. theses and has completed pedagogical studies. Janhunen actively reviews for journals like Artificial Intelligence Journal and ACM Transactions on Computational Logic .

• Signal Processing
• Machine Learning
• Graph Signal Processing
• +۳ مورد دیگر

Xinjue Wang is a Doctoral Researcher at the Department of Information and Communications Engineering, Aalto University, affiliated with the Esa Ollila Group. Research Interests: Her work focuses on signal processing, machine learning, and wireless communication, with emphasis on robust algorithms for massive access, graph neural networks, and tensor regression models. Publications Trends: Recent publications include studies on covariance-based matching pursuit, graph neural network sensitivity, and millimeter wave tracking, presented at top conferences like ICASSP and EUSIPCO, and published in journals such as IEEE Transactions on Signal and Information Processing over Networks. Collaborations: Collaborates with researchers including Esa Ollila, Sergiy A. Vorobyov, and Jari Miettinen.

• Machine Learning
• Autonomous Driving
• Natural Language Processing
• +۴ مورد دیگر

Tsvetomila Mihaylova is a Postdoctoral Researcher in the Department of Computer Science at Aalto University , specializing in machine learning and human-robot interaction. Her work bridges theoretical advancements in neural networks with practical applications in autonomous systems. Fields of Interest : Latent structure learning, autonomous driving, visual-language models, and natural language processing Email : tsvetomila.mihaylova@aalto.fi Research Focus : • Latent structure modeling using discrete and undirected neural networks • Autonomous driving safety through conflict simulation and trajectory prediction • Cross-modal integration in robotic vision-language systems Publication Trends : Recent work explores 2025 in structured neural architectures for autonomous vehicles and 2024 in human-robot interaction quality evaluation, with foundational contributions to natural language processing fact-checking systems since 2019 .

• Machine Learning
• Differential Privacy
• Bayesian Statistics
• +۳ مورد دیگر

Antti Honkela serves as a Visitor at Aalto University's Department of Computer Science and is deeply affiliated with the Helsinki Institute for Information Technology (HIIT), a joint research institute of Aalto University and the University of Helsinki. Within HIIT, he actively contributes to the Myllymäki Petri research group and leads the Probabilistic Machine Learning research group, focusing on advanced statistical methodologies. His research centers on machine learning with rigorous emphasis on differential privacy, Bayesian statistics, and probabilistic modeling. Honkela bridges theoretical innovation with biomedical applications, particularly in drug sensitivity prediction, genomic analysis, and privacy-preserving data sharing. His work addresses critical challenges in maintaining data utility while ensuring mathematical privacy guarantees for sensitive health information. Recent publications reveal a clear trajectory from foundational privacy mechanisms (e.g., FFT-based accounting) toward efficient biomedical implementations. His 10 publications between 2016-2021 demonstrate consistent output in top venues like Nature Communications and NeurIPS, with growing emphasis on transfer learning and distributed frameworks for real-world healthcare data. Scientific recognition includes: 2001 Year-End Thesis Award from CMCM, Center for Mathematical and Computational Modeling, University of Jyväskylä While specific student counts aren't public, his active research profile suggests ongoing supervision opportunities. Funding appears sustained through HIIT's infrastructure and competitive Nordic research grants, enabling work on privacy-preserving algorithms for genomic and clinical datasets. The Probabilistic Machine Learning group provides a collaborative environment leveraging Aalto University's computational resources and HIIT's interdisciplinary network. Lab activities focus on developing theoretically sound privacy mechanisms with practical biomedical impact, particularly in drug response modeling and genomic data analysis where privacy constraints are critical.

• data mining
• machine learning
• artificial intelligence
• +۳ مورد دیگر

Kai Puolamäki is a Professor at the Department of Computer Science, Aalto University. He holds a permanent position and focuses on data mining, machine learning, and computational methods. University: Aalto University Department: Department of Computer Science Academic Rank: Professor Research Interests: Explorative data analysis, randomization, machine learning, and their interdisciplinary applications. Publication Trends: His recent work spans chemistry, neuroscience, linguistics, and paleontology, emphasizing algorithmic innovation for heterogeneous data analysis and visualization in cross-domain contexts. Topics include computational chemistry modeling, wearable biosignal interpretation, subgroup discovery with subjective feedback, and network randomization.

• 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

• Probabilistic Machine Learning
• Machine Learning
• Computer Science

Anna Elisabeth Riha is a Doctoral Researcher at Aalto University's Department of Computer Science, affiliated with the Probabilistic Machine Learning research group. Role: Doctoral Researcher Institution: Aalto University Department: Department of Computer Science Research Group: Probabilistic Machine Learning Her research focuses on probabilistic machine learning methodologies, aligning with her affiliation under the supervision of Professor Aki Vehtari. Contact details include email anna.riha@aalto.fi and phone number +358504644317.

• 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.

Petri Myllymakiمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Probabilistic Modeling
• +۶ مورد دیگر

Petri Myllymäki is a Professor of Artificial Intelligence and Machine Learning at the Department of Computer Science, University of Helsinki. He serves as Director of the Helsinki Institute for Information Technology (HIIT), Vice-Director of the Finnish Center for Artificial Intelligence (FCAI), and Director of the Helsinki Doctoral Education Network in ICT (HICT). His work bridges theoretical machine learning research with industrial applications, spanning probabilistic modeling, clustering, and data visualization. Current affiliations include: University of Helsinki, HIIT, FCAI, HICT, and ELLIS Executive Committee Global roles: UN High-Level Advisory Body on AI, AI/Robotics PPP (ADRA) for EU, and World Summit AI editorial board His research interests focus on Bayesian network structure learning, algorithm selection, and data science. Recent work emphasizes empirical evaluation of computational complexity and hybrid systems combining hashing with probabilistic models. Earlier studies include exploratory search intent modeling and genomic motif analysis. Notable scientific achievements include 37 Google Scholar h-index, 6700+ citations, and Ellis Fellowship. He has been recognized for contributions to theoretical machine learning and practical AI applications in Finland. As a founder of AI startups like Sprint.ai and Ekahau, Myllymäki has driven commercialization of machine learning technologies, resulting in fielded applications and patents across diverse sectors.

Toni Karvonenمشاهده پروفایل

استادیار

• Statistics and Probability
• Applied Mathematics
• Numerical Analysis
• +۱۰ مورد دیگر

Toni Karvonen is an Assistant Professor of Applied Mathematics at LUT University's Computational Engineering Department, School of Engineering Sciences, since September 2024. His research focuses on statistics, applied mathematics, and computational methods with emphasis on Gaussian processes, uncertainty quantification, and kernel-based approximation. He has held postdoctoral positions at the Alan Turing Institute (2020–21) and the University of Helsinki (2021–24). Research Areas: Statistics and Probability, Applied Mathematics, Numerical Analysis, Gaussian Processes, Positive Definite Kernels Key Trends: His recent work explores probabilistic numerics, Bayesian quadrature, kernel methods for uncertainty quantification, and approximation theory in reproducing kernel Hilbert spaces. Email: Toni.Karvonen@lut.fi

• Machine Learning
• Medical Imaging
• Computer Science
• +۳ مورد دیگر

Aleksei Tiulpin is a Visiting Professor affiliated with the Department of Electrical Engineering and Automation and Sensor Informatics and Medical Technology . His research focuses on applying machine learning and deep learning to medical imaging and biomedical engineering , particularly for osteoarthritis diagnosis and progression prediction. His work includes automating histopathological grading using micro-CT , multi-modal imaging data fusion , and segmentation of chest X-rays . Recent publications highlight trends in Bayesian decision-making , tidemark segmentation , and clinical decision support systems .