Find Academic Supervisors

• Computer Science
• Information Systems
• Formal Methods
• +5 more

Keijo Tapio Heljanko is a Professor in the Department of Computer Science at the University of Helsinki, affiliated with the Helsinki Institute for Information Technology and the EUROFusion Advanced Computing Hub. He previously held an Associate Professor position at Aalto University (2008–2018) and currently serves as Principal Investigator at HIIT. His research focuses on formal methods, parallel computing systems, machine learning applications, and GPU architecture optimization. He leads the LUMI AI Factory project (2025–2028), an EU-funded initiative for AI infrastructure development. Education details are not explicitly listed in the provided text. His work spans theoretical computer science and applied machine learning, with notable contributions to bike-sharing optimization, GPU consistency analysis, and boreal ecosystem modeling. Media highlights include collaborations with NVIDIA on AI technology centers and innovations in search engine and disinformation detection systems. Professional roles include supervising the Doctoral Programme in Computer Science and managing multi-institutional research projects. He has collaborated internationally on topics ranging from exascale computing to environmental data analysis. His research outputs total 131 publications and 9 press engagements, emphasizing both foundational and applied computational challenges.

• Optimization
• Quantum Computing
• User Interface Design
• +3 more

Niraj Dayama is an Associate Professor in the Department of Information Technology at Arcada University of Applied Sciences, affiliated with the School of Engineering, Culture and Wellbeing. He holds a Doctor of Philosophy. His research focuses on optimization techniques, quantum computing applications, user interface design, and algorithm development for interactive systems. Dr. Dayama's work bridges computational methods with human-centric design challenges. Educational Background: Doctor of Philosophy (PhD), details of academic programs not explicitly stated in provided texts. Affiliations include Arcada UAS with a primary role in Information Technology education and research. Research Interests: Dr. Dayama explores optimization in diverse domains such as quantum computing ecosystems, user interface layout generation, and scheduling problems. His contributions span algorithm design for grid-based layouts, real-time adaptive interfaces, and combinatorial solutions for UI/UX challenges. Recent work emphasizes leveraging quantum computing for problem decomposition and full-stack quantum software development. Publications reflect a shift toward quantum computing and optimization since 2020, complemented by longstanding engagement with layout design and scheduling algorithms. Notable trends include cross-disciplinary approaches merging computational methods with human interaction principles. No scientific awards or grants are explicitly mentioned in the provided texts. Advising roles or student supervision details are not listed.

• Media Technology
• Journalism Studies
• Public Policy
• +3 more

John Grönvall is a Lecturer in Media Technology at Arcada University of Applied Sciences, affiliated with the School of Engineering, Culture and Wellbeing. He holds an M.Sc. in Computer Graphics. His research focuses on media technology, public service media, journalism's role in democracy, platformization impacts, Nordic media policies, and fact-checking mechanisms. Recent work examines Nordic public service media discourses, platform effects on Finnish media, and strategies to counter commercial pressures in newsrooms. Grönvall has contributed over two decades to media studies, with early work in distributed computing for logistics. Research interests emphasize the intersection of technology and societal structures, particularly how digital platforms reshape media ecosystems and democratic processes. He investigates how Nordic countries balance public broadcasting mandates with emerging challenges like disinformation and resource constraints. His studies often adopt a comparative Nordic perspective, analyzing policy frameworks and journalistic practices across Scandinavia. Publications highlight themes such as pandemic-era journalism, media platform monopolies, and the decoupling of journalism from democratic functions. His work bridges technical innovations (e.g., parcel tracking systems) with sociocultural analysis of media landscapes, reflecting his interdisciplinary background in computer science and media studies.

• 3D Animation
• 3D Graphics
• Animation
• +6 more

Jaro Lehtonen is a Senior Lecturer at Metropolia University of Applied Sciences, specializing in 3D animation, visualization, and game design. He holds an M.Sc. in Architecture and is affiliated with the Design Team. Contact details include +358 40 508 7454 and Jaro.Lehtonen@metropolia.fi. His expertise spans 3D graphics, game production, and fine arts. Responsibilities include teaching and research in digital media and game design. Language skills: Finnish (native), English (excellent), Swedish and Spanish (advanced). Key interests focus on 3D character rigging, game graphics, and architectural visualization. No specific grants, labs, or advising roles are detailed in the provided information.

• 3D Computer Graphics
• XR Technology
• Interactive Media Design
• +3 more

Ale Torkkel serves as a Senior Lecturer at Metropolia University of Applied Sciences, specializing in XR Design Projects within the Conservation and Media Team. His work spans Augmented Urbans initiatives, Finnish Design Academy programs, Creathon, and AgileXR development. Ale Torkkel's educational background includes: Master of Culture and Arts from Helsinki Metropolia of Applied Sciences (2013) in Media Production and Management Bachelor of Culture and Arts from EVTEK University of Applied Sciences (2005) in 3D Visualisation and Animation Architectural studies at Tampere University of Technology (1983-, 140/180 credits completed) Torkkel's research focuses on the intersection of immersive technologies and cultural applications. His expertise spans 3D computer graphics, interactive 3D applications, XR content creation, real-time architectural visualization, and XR implementation in cultural heritage preservation. With competences in 3D Animation, AR, VR, Digital learning environments, and Multimedia production, he bridges traditional media techniques with cutting-edge immersive technologies. He maintains professional proficiency across multiple languages: English: Excellent Swedish: Advanced Italian: Beginner German: Beginner

• Video Streaming
• Virtual Reality
• Multi-Access Edge Computing
• +3 more

Matti Siekkinen is a Lecturer in the Department of Computer Science at Aalto University. He is also affiliated with the Helsinki Institute for Information Technology (HIIT), the Professorship Di Francesco Mario, and the Computer Science Lecturers group. His research focuses on latency-critical mobile multimedia services, cloud-based virtual reality (VR), and edge computing solutions to optimize network performance and user experience. Education: Doctoral degree in Engineering and Technology (2007) from Université Côte d'Azur Master's degree in Engineering and Technology (2003) from Helsinki University of Technology Research Interests: His work emphasizes improving Quality-of-Experience (QoE) in mobile and cloud gaming, optimizing video streaming for VR applications, and deploying edge computing to reduce latency. Key topics include foveated rendering, dynamic resource allocation, and energy-efficient mobile service delivery. He has led projects such as CloudVR (2019–2020) and Latency-Critical Mobile Multimedia Services (2016–2019), which investigate network architecture and latency reduction strategies. Recent Research Trends: Recent publications highlight advancements in foveated compression techniques, head-pose prediction for remote VR, and neural network-based depth map packing. His work often bridges theoretical models with practical implementations in edge and cloud environments. Grants & Projects: Principal Investigator for CloudVR: High-Quality Mobile VR Using Cloud Acceleration (Business Finland) Principal Investigator for Latency-Critical Mobile Multimedia Services (Academy of Finland) Labs & Groups: He leads the Siekkinen Matti group, focusing on innovative solutions for mobile and cloud-based multimedia systems. Collaborations include Tsinghua University and industry partners like Elisa.

• Computational Fluid Dynamics
• Atomic Layer Deposition
• Deposition Process Engineering
• +3 more

Gizem Ersavas Isitman is a Visitor (Faculty) and Doctoral Student in the Department of Energy and Mechanical Engineering at the School of Engineering. She holds a Master's degree in Engineering and Technology from Izmir Institute of Technology (2019). Her research focuses on advanced computational methods in material science and fluid dynamics, particularly Atomic Layer Deposition (ALD) process optimization and GPU-accelerated simulations for airflow and virus transmission modeling. Research interests include: Computational Fluid Dynamics (CFD) for industrial and health applications ALD process dynamics in nanoscale environments Knudsen number effects on material deposition GPU-based high-performance computing Recent work emphasizes CFD modeling of indoor airflow patterns to assess virus transmission risks, along with ALD process simulations around cylindrical structures. These studies bridge material science and engineering through advanced numerical methods. Collaborative research involves international teams working on thin film technology and fluid dynamics applications. No scientific awards have been explicitly mentioned in the provided data. Her doctoral research appears focused on advancing computational methodologies for material deposition and environmental fluid dynamics. No advising or grant information is available in the current dataset.

• Deep Reinforcement Learning
• Motion Control
• Image Synthesis
• +7 more

Nam Hee Kim is a doctoral researcher in the Department of Computer Science at the School of Science , focusing on interdisciplinary research at the intersection of Deep Reinforcement Learning , Image Synthesis , and Physics-Based Animation . He contributes to advancements in Virtual Character Animation and Motion Control using Machine Learning techniques, with recent work on fatigued movements and controllable face synthesis. Research Interests : His work spans Deep Reinforcement Learning , Motion Capture , and Neural Network Optimization , addressing challenges in Computer Graphics , Robotics , and Bioinformatics . Key themes include Realism in Animation , Controllable Generative Models , and Epigenomic Analysis . Publications Trends : Kim's recent contributions (2021–2023) emphasize Motion Control and Face Synthesis , leveraging Reinforcement Learning and Generative Adversarial Networks . Earlier work (2020–2021) explores Stepping Stone Skills , Dynamical Systems Correspondence , and Epigenomic Data Analysis .

• Computing Education Research
• Educational Technology
• Large Language Models in Education
• +3 more

Arto Hellas is a Senior Lecturer at the Department of Computer Science, University of Helsinki, where he leads the Lecturer Hellas Arto group. His work focuses on computing education research (CER) and educational technology, particularly leveraging large language models (LLMs) to enhance programming education and automated assessment tools. He also explores web development optimization through edge computing and serverless architectures. Research Interests: Hellas's research spans the integration of AI into education, programming pedagogy, and educational technology. He investigates how LLMs can generate feedback, analogies, and exercises for students, as well as their impact on MOOCs and classroom dynamics. His work addresses challenges in student performance analysis, synthetic data generation for educational purposes, and the ethical implications of AI in learning environments. His studies on web development emphasize distributed systems and edge computing applications to improve web service delivery. Scientific Awards: ICER 2022 Best Paper Award for work on LLM-generated programming exercises SIGCSE TS 2022 Best Paper Award in Computing Education Research UKICER 2023 Best Paper Award Advising & Grants: Hellas currently leads the CoCoAI: Human-Centered AI for Computer Science Education project (2025–2027), focusing on personalized learning through LLMs. He has supervised 2 theses but no student names were explicitly provided. His grants and projects highlight contributions to educational technology, including datasets like the IDE Action Log Dataset and Morning or Evening? circadian rhythm study. Labs & Teams: Active within the Lecturer Hellas Arto group, his collaborations span computing education, AI ethics, and web development. His team's work has been featured in media, such as a 2023 article discussing AI's role in developing a chess website in days.

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

Petri Myllymäki is a Director at Helsinki Institute for Information Technology (HIIT) , Computer Science Adjunct Professors , and Finnish Center for Artificial Intelligence (FCAI) within Aalto University's School of Science, Department of Computer Science . His research focuses on Bayesian networks, information discovery, and interactive intent modeling . Active in ACM Transactions on Information Systems and SIGIR Conference publications Recipient of 2016 CPHC/BCS Academy of Computing Distinguished Dissertation runner-up and 2017 Kone Foundation Rajapinta award Collaborated with institutions like Stockholm University and researchers including Giulio Jacucci and Samuel Kaski His 15 most recent publications (2025-2015) span decision-making under conflicting objectives, machine learning applications in social science, Bayesian network structure learning algorithms , and cognitive modeling for exploratory search . Key technical subfields include hashing techniques, two-dimensional representation, computational efficiency, and user experience optimization . Scientific awards : 2016 CPHC/BCS Academy of Computing Distinguished Dissertation runner-up 2017 Kone Foundation Rajapinta award As an information discovery expert , he has contributed to open-access research through Interactive Visualization and Scinet frameworks, impacting Sustainable Development Goals related to digital innovation and knowledge dissemination.

Kari KoskinenView profile

Professor

• Robotics Engineering
• Autonomous Underwater Vehicles
• Control Systems
• +3 more

Dr. Kari Koskinen is Professor in Automation Technology and Mechanical Engineering at Tampere University, specializing in robotics, autonomous systems, and industrial digitalization. He holds a Doctor of Science in Automation Engineering and Licentiate of Science in Mechanical Engineering. Research domains include: Robotics and autonomous underwater vehicle systems Control architecture design and optimization Physics-based simulation modeling and digital twin implementation Predictive maintenance through machine learning Industrial process optimization using empirical and computational models His publications focus on industrial applications of simulation technologies, predictive maintenance algorithms, and optimization of manufacturing processes. Recent work demonstrates strong integration of physical modeling with machine learning approaches for industrial diagnostics.

Juho HirvonenView profile

Research Fellow

• Distributed Algorithms
• Graph Theory
• Network Computing
• +2 more

Juho Hirvonen is a Research Fellow at Aalto University's School of Science , Department of Computer Science. His work focuses on distributed algorithms, network computing, and algorithmic game theory. Education: Master's degree in Engineering and Technology from University of Helsinki (2012) Research Interests: Active in Distributed Algorithms , with a focus on locality-sensitive approaches, fault-tolerant systems, and convergence complexity in graphical games. Key subfields include sparse matrix operations, static fast rerouting, and distributed stable matching. Scientific Recognition: Recipient of the Best Paper Award at FOCS 2019 for foundational work in distributed network computing. Projects: Led the Academy of Finland-funded project Towards a Complexity Theory of Distributed Network Computing (2018-2021) Collaborations: Engaged with institutions like Université Paris Diderot and international conferences (OPODIS, SIROCCO)

Matti KurkelaView profile

Researcher

• Terrestrial Laser Scanning
• Mobile Mapping
• Photogrammetry
• +3 more

Matti Kurkela serves as a Staff Scientist at Aalto University's Department of Built Environment, specializing in advanced 3D measurement technologies and geospatial applications. His work integrates laser scanning, photogrammetry, and mobile mapping systems for environmental and built environment analysis. His educational background includes a Doctoral degree in Engineering and Technology from Aalto University (awarded December 30, 2022), a Licentiate degree from the same institution (December 17, 2013), and a Master's degree in Arts and Design from the University of Lapland (December 17, 2007). Research focuses on terrestrial laser scanning (100% fingerprint match), mobile mapping (50%), photogrammetry (37%), point cloud processing (34%), and vegetation analysis (31%). His work contributes to UN Sustainable Development Goals through environmental monitoring and sustainable development applications. Recent publications show strong emphasis on photorealistic visualization, educational technology, and infrastructure analysis. National Open Science Award (2019) for collaborative open data initiatives Key contributor to EU-funded projects including RADIAL (construction digitalization) and Co-creation of Autonomous Future Active in organizing academic workshops on 3D measurement technologies and has participated in international collaborations including University College London visits. His datasets on Zenodo demonstrate practical applications in lighting analysis and pavement measurement. Current research integrates laser scanning with emerging technologies for urban and environmental challenges.

Gantugs AtarsaikhanView profile

Researcher

• Computer Science
• Artificial Intelligence
• Cancer Biology
• +3 more

Gantugs Atarsaikhan is a Postdoctoral Researcher at the Finnish Institute of Molecular Medicine (University of Helsinki), focusing on artificial intelligence applied to biomedical imaging and cancer research. His work bridges computer science with clinical applications through advanced deep learning techniques. Research Interests : Cancer microenvironment spatial profiling Self-supervised learning for biomedical images Deep metric learning for time series Neural style transfer in design Computer vision in pathology Recent article trends show expertise in applying computer vision (vision transformers, time warping algorithms) to multiplexed microscopy images and typographic design generation. His publications (2018–2024) emphasize deep learning, image analysis, and biomedical applications. Projects : iCAN-DIP (2021–2026): AI-driven deep image profiling of pan-cancer microenvironment Uncovering patterns in cancer cells (2022–2026): Visual representation learning Academy of Finland grants (2024–2028) for cellular-level cancer profiling Activities : Poster presentations at EMBO/EMBL Symposium (2024) and FCI Symposium (2024) Oral presentation at AI-Driven Imaging Conference (2023)