Model Checking Professors and Supervisors in Finland

Debasish Palمشاهده پروفایل

پژوهشگر ارشد

University of OuluFinland

Debasish Pal is a Research Fellow at the University of Oulu's Faculty of Technology within the Water, Energy and Environmental Engineering unit. His work focuses on developing hydrological decision-support systems through digital twin frameworks for river basins and optimizing peatland restoration strategies to improve water quality using spatiotemporal analysis and multi-objective optimization. His core research areas include: Digital twin applications for river basin management Peatland restoration and water quality control Check-dam system design for soil erosion mitigation Nature-based solutions in watershed management Sediment-laden open channel hydraulics Automated GIS and spatiotemporal data analysis Genetic algorithms and high-performance computing for optimization Pal integrates physics-based and data-driven modeling approaches to address critical environmental challenges, contributing to sustainability goals through the Hydrology and Water Quality research group. His methodology combines hydrological modeling, computational optimization, and nature-based interventions for real-world environmental problem-solving.

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Tomi Janhunenمشاهده پروفایل

استاد

Aalto UniversityFinland

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 .

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Tsvetomila Mihaylovaمشاهده پروفایل

پژوهشگر

Aalto UniversityFinland

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 .

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Mehedi Hasan Bijoyمشاهده پروفایل

پژوهشگر

Aalto UniversityFinland

Mehedi Hasan Bijoy is a Doctoral Researcher at the Department of Information and Communications Engineering, Aalto University. His research focuses on interdisciplinary applications of AI in speech recognition, natural language processing, and agricultural technology. Research interests include Developing transformer-based models for resource-scarce Indic languages Multimodal analysis of humor and social perception Deep learning applications in sustainable agriculture The 2025 publication in Computer Speech and Language highlights his work on Bangla spelling correction using transformers. Two 2024 articles in MuSe and IEEE Access explore multimodal sentiment analysis and rice leaf disease detection with dCNN, demonstrating his cross-domain application of machine learning.

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Keijo Tapio Heljankoمشاهده پروفایل

استاد

University of HelsinkiFinland

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.

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John Grönvallمشاهده پروفایل

مدرس

Arcada University of Applied SciencesFinland

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.

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Marina Waldenمشاهده پروفایل

مدرس ارشد

Abo Akademi UniversityFinland

Marina Walden serves as a Senior Lecturer in Information Technology at Åbo Akademi University's Faculty of Natural Sciences and Engineering. Her research focuses on formal methods and software engineering with applications to autonomous systems, particularly in maritime contexts. She leads significant research projects including the Cyber security training cooperation network (2023-2025) and previously served as Principal Investigator for ADVICeS and Digihybrid projects. Dr. Walden's research interests span formal verification, Event-B modeling, autonomous ship navigation, distributed systems, and safety-critical systems development. Her work demonstrates a strong focus on applying rigorous formal methods to real-world engineering challenges, particularly in maritime autonomous systems where safety and compliance with international regulations (COLREGs) are critical. She has developed expertise in multi-vessel navigation systems, role-based workflow modeling, and agile development methods. Her publication record shows consistent output with 125 publications spanning from 1988 to 2024, with recent work focusing on autonomous vessels, formal verification techniques, and workflow modeling. The research trends indicate a progression from foundational work in formal methods toward increasingly complex applications in maritime autonomous systems and cyber security. Dr. Walden actively supervises research, with Yevheniia Yehorova being one documented advisee with whom she co-authored a 2024 publication. She has secured significant research funding through Academy of Finland projects and collaborations with government agencies. Her current research activities include hosting academic visitors and leading the active Cyber security training cooperation network project that runs through 2025, demonstrating continued engagement in both research and academic community building.

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