Find Academic Supervisors

Juho KannalaView profile

Associate Professor

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +5 more

Juho Kannala is an Associate Professor of Computer Vision at Aalto University and an Adjunct Professor at the University of Oulu. He co-founded Spectacular AI, a company focused on spatial AI and sensor fusion solutions. His primary affiliation is with the Department of Computer Science at Aalto University, where he leads research in computer vision, machine learning, and robotics. Education: PhD in Computer Science, University of Oulu (2010) Master's Thesis: 'Measuring the Shape of Sewer Pipes from Video,' Helsinki University of Technology (2004) Research Interests: Juho's work spans 3D reconstruction , visual localization , deep learning , and robotics applications . His research emphasizes practical systems like real-time visual-inertial odometry (HybVIO) and large-scale datasets (TBPos). He explores interdisciplinary areas such as medical imaging and atomic force microscopy automated analysis. Key Projects: Co-developed the ADVIO dataset for visual-inertial odometry Advanced multi-view stereo techniques with Gaussian splatting Co-founded Spectacular AI for spatial AI solutions Teaching: Responsible for the Computer Vision (CS-E4850) course at Aalto University. Advises on bachelor/master/doctoral thesis topics in computer vision and machine learning.

Topias TerhoView profile

Researcher

• Operations Research
• Mathematical Optimization
• Probability and Statistics
• +3 more

Topias Terho is a Doctoral researcher at Aalto University's Department of Mathematics and Systems Analysis, School of Science. His research focuses on operations research, decision analysis, and mathematical optimization, with applications in transportation systems and financial mathematics. He contributes to the department's research groups in Mathematical Physics and Systems & Operations Research. Key research interests include influence diagrams, computational optimization, and probabilistic modeling. His recent work addresses risk-averse decision strategies, public transport optimization, and covariance matrix estimation in portfolio theory. He holds no recorded scientific awards but actively engages in academic collaborations within his field. Topias is based at Aalto's Otakaari campus in Espoo, Finland, and can be reached via email .

Tomi JanhunenView profile

Professor

• Knowledge Representation and Reasoning
• Answer Set Programming
• Satisfiability Checking
• +6 more

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 .

Juha SorvaView profile

Senior Lecturer

• Education
• Educational Psychology
• Learning to Program
• +8 more

Juha Sorva is a Senior Lecturer at Aalto University's School of Science and a leading researcher in computing education. His work focuses on introductory programming education , software visualization , and cognitive load theory in learning contexts. Research Themes: Educational Technology, Learning Analytics, Notional Machines, Visual Program Simulation, Instructional Design, and Media Computation. Leadership: Developed Aalto University's first MOOC, received multiple teaching awards, and pioneered tools like UUhistle for program visualization. His recent publications highlight graphics-based programming instruction , LLM applications in programming support , and fine-grained analysis of learning behaviors . Key awards include the CICERO Best Doctoral Dissertation Award (2013) , Aalto High 5 Award (2015) , and Teaching Development Award (2014) . Scientific Awards: CICERO Best Doctoral Dissertation Award (2013) Aalto High 5 Award for Education (2015) Teaching Development Award (2014) Teacher of the Year (2007)

• Biomechanical Simulation
• 3D Target Inference
• Human-Computer Interaction
• +3 more

Chenyu Li is a Doctoral Researcher at Aalto University's Department of Computer Science in Espoo, Finland. Their work focuses on real-time 3D target inference through biomechanical simulation, combining computer science with human factors research. Their research interests span biomechanical simulation, 3D modeling, and human-computer interaction, with particular emphasis on real-time systems and machine learning applications in computer graphics. Recent publications highlight interdisciplinary work merging computational modeling with biomechanics. Current output includes one notable article presented at the CHI Conference on Human Factors in Computing Systems (CHI '24).

• Human-Computer Interaction
• User Interface Design
• AI in UI/UX Development
• +1 more

Yue Jiang is a Doctoral Researcher at the Department of Information and Communications Engineering at Aalto University. Specializing in User Interface Design and Human-Computer Interaction , Jiang's research explores computational methodologies for modeling, automating, and evaluating graphical user interfaces using artificial intelligence and machine learning techniques. Primary affiliation: Aalto University Research focus: UI/UX automation, AI integration, scanpath modeling Recent work investigates language-vision modeling of UIs, graph neural networks for GUI representation, and personalized scanpath prediction through transformer-guided reinforcement learning. Jiang collaborates with researchers across machine learning and human-computer interaction domains, contributing to conferences like IUI, CHI, and VL/HCC.

• Machine Learning
• Autonomous Driving
• Natural Language Processing
• +4 more

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 .

• Photogrammetry
• Laser scanning
• Remote Sensing
• +3 more

Petri Rönnholm serves as a Senior University Lecturer in the Department of Built Environment at Aalto University's School of Engineering. His expertise encompasses photogrammetry, laser scanning, remote sensing, and digital image processing for built environment applications. His research centers on geoinformatics, particularly 3D modeling and mapping of built environments using advanced techniques like SLAM and terrestrial laser scanning. He investigates drift correction in indoor mapping, photogrammetry for cultural heritage, and open data solutions for urban planning. Key projects include watershed analysis visualizations and methane flux studies in ecological systems. Recent publications (2021-2025) reveal a focus on integrating geospatial technologies with machine learning and game engines for environmental analysis. Major contributions span indoor mapping automation, archaeological photogrammetry, and NoSQL query systems for spatial data, demonstrating strong interdisciplinary collaboration in environmental and construction engineering. He actively participates in Aalto University's Geoinformatics research group, developing methodologies for point cloud processing and change detection in built environments through partnerships with leading researchers in the field.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +3 more

Heikki Oskari Timonen is a Doctoral Researcher in the Department of Computer Science at Aalto University, affiliated with Professor Jaakko Lehtinen's research group. His research focuses on the intersection of computer vision and generative artificial intelligence, with specific expertise in: Generative Models Deep Learning architectures Image synthesis techniques Invertible neural networks Hierarchical modeling Computer vision applications His 2023 publication in Transactions on Machine Learning Research introduced novel hierarchical generative frameworks for image processing, demonstrating significant contributions to generative AI methodology. He operates within Aalto University's computer graphics and machine learning research ecosystem under Professor Lehtinen's supervision.

• Nonlinear Systems
• Control Theory
• Reachability Analysis
• +3 more

Jianqiang Ding is a Doctoral Researcher at Aalto University's School of Engineering, Department of Electrical Engineering and Automation. His work focuses on nonlinear systems and control theory, particularly in reachability analysis for dynamical systems verification and controller synthesis. His research interests include: Reachability analysis for safety-critical systems Formal verification of nonlinear control systems Developing computational tools like PyBDR for set-boundary based analysis Controller synthesis for multi-input multi-output systems Image processing techniques for discernible mosaics Recent publications demonstrate expertise in: Formal methods for system verification Control theory applications in engineering Computational tool development for control systems His collaborative work appears in venues like Formal Methods Symposium and Computer Aided Verification Conference, with particular emphasis on mathematical rigor in control design.

• Generative Adversarial Networks
• Machine Learning
• Image Processing
• +3 more

Erik Härkönen is a Doctoral Researcher in the Department of Computer Science at Aalto University , focusing on machine learning, generative adversarial networks (GANs), and computational imaging. His research explores latent space manipulation, anti-aliasing techniques, and high-resolution image synthesis. University: Aalto University Department: Department of Computer Science Academic Rank: Researcher His work has been published in venues like ACM Transactions on Graphics and NeurIPS, covering areas from gradient-domain rendering to robust perceptual metrics. Recent research includes disentangling temporal patterns in time-lapse sequences and improving GAN interpretability through latent space controls.

• 3D Modeling
• Photorealism
• Built Environment
• +3 more

Markus Sarlin is a Doctoral Researcher at the Department of Built Environment, Aalto University. His work focuses on photorealism and 3D modeling applications in environmental analysis. Research Group: MeMo Affiliation: Aalto University Research Interests : Markus specializes in 3D modeling, photorealism, and computer vision within the built environment context. His projects include geospatial analysis and architectural visualization. Publication Trends : His research spans photorealism in digital art (2021) and consumer-grade 3D modeling systems (2024), emphasizing interdisciplinary applications in technology and environmental design. Labs & Teams : Markus collaborates with the MeMo research group, contributing to advancements in 3D modeling and photorealistic rendering.

Juho Tuomas VepsäläinenView profile

Lecturer

• Web Development
• JavaScript Programming
• Static Site Generation
• +5 more

Dr. Juho Tuomas Vepsäläinen is a Lecturer at the Department of Computer Science, Aalto University, specializing in web development technologies. His work focuses on modern web application architectures and optimization techniques. Research interests include: Hybrid rendering models JavaScript ecosystems and standardization Serverless edge computing Static site generation Framework evolution Web performance optimization Recent publications (2022-2025) analyze emerging trends in web development, with particular emphasis on hybrid architectures, edge computing, and disappearing frameworks. His work appears in venues like IEEE Access, Web Engineering, and Web Information Systems and Technologies conferences. Dr. Vepsäläinen collaborates with colleagues including Arto Hellas and Petri Vuorimaa on next-generation web technologies. He maintains expertise in tools such as Node.js, Deno, and React.js.

Maarit Korpi-LaggView profile

Associate Professor

• High-Performance Computing
• Numerical Modelling
• Astroinformatics
• +3 more

Dr. Maarit Korpi-Lagg is an Associate Professor in the Department of Computer Science at Aalto University's School of Science. She specializes in High-Performance Computing (HPC), numerical modelling, and astroinformatics, with a focus on solar magnetic activity and dynamo theory. Her work bridges computational methods with astrophysical phenomena. External Positions: Corresponding Fellow, Nordic Institute for Theoretical Physics (2020–2025) Independent Max Planck Research Group Leader, Max Planck Institute for Solar System Research (2016–) Research interests include: High-Performance Computing for astrophysical simulations Solar magnetic field dynamics and sunspot analysis GPU-accelerated code development Stellar convection zones and atmospheric modeling Her recent publications highlight advancements in exascale astrophysics data analysis, solar dynamo simulations, and cross-disciplinary applications like epidemic modeling via computational methods. Key collaborations span Europe and global institutions. Scientific Awards: Grand Challenge Award (2018) for galactic dynamo research Nordita Corresponding Fellowship (2020) She leads multiple projects, including ERC UniSDyn and NEOSC, focusing on cosmic magnetism and GPU-based stencil computations. Her work contributes to UN Sustainable Development Goals, particularly quality education and planetary science.

• Computer Graphics
• Computer Vision
• Machine Learning
• +5 more

Jaakko Lehtinen is a Professor in the Department of Computer Science at Aalto University, affiliated with the School of Science. His research group focuses on computer graphics, computer vision, and machine learning, particularly in generative modeling, realistic image synthesis, and appearance acquisition. They explore combining machine learning with physical simulators to develop robust and interpretable AI systems. Their work contributes to Visual Computing and Human-Computer Interaction. Lehtinen has supervised doctoral researchers including Erik Härkönen and Tuomas Kynkäänniemi. Notable awards include the Best MSc Thesis Award (2020) and Best PhD Thesis Awards (2017). He has contributed to high-impact publications in venues like NeurIPS and Neural Computation, addressing topics like diffusion models, EEG forecasting, and generative adversarial networks. Key Collaborations: International partnerships in machine learning and visual computing. Media Engagement: Regular commentary on AI trends in Finnish and global media. Professional Activities: Served as a PhD thesis committee member for institutions like UC Berkeley and MIT. His research extends to medical imaging, environmental modeling, and neural rendering, with applications in tomography, audio processing, and dynamic scene generation. Lehtinen’s group actively publishes datasets (e.g., for gradient-domain rendering) and engages in open-source software contributions.