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Björn JohanssonView profile

Professor

• Cognitive Science
• Human-Computer Interaction
• Complex Systems
• +4 more

Björn Johansson is a Professor at Linköping University in the Department of Computer Science (IDA) , affiliated with the Human-Centered Systems (HCS) division. His research focuses on human interaction with complex systems, particularly in energy systems, crisis management, and autonomous systems, using simulation and game-based methods. Leading the "Att vända strömmen" project (funded by Swedish Energy Agency) to address sustainability challenges in energy systems Co-developing "megagames" for understanding societal polarization and climate change Collaborating with Saab on aviation interface design and autonomy research His recent publications span AI in smart grids, ERP cloud migration, and resilience in autonomous systems. He teaches courses in Cognitive Systems Engineering and Crisis Management, and co-leads the SkyLab research environment for future aviation concepts. Current grants include SEK 24.5 million from the Swedish Energy Agency and SEK 33.4 million from the Kamprad Family Foundation.

Juliette GriffiéView profile

Research Fellow

• Light Microscopy
• Image Analysis
• Immunology
• +4 more

Juliette Griffié is a DDLS Fellow at Stockholm University, affiliated with the Computational Microscopy for Cell Biology (CMCB) laboratory. Her research focuses on developing advanced image analysis strategies and machine learning tools to address fundamental questions in cell biology using light microscopy. Research Interests include: Advanced light microscopy techniques Machine learning applications in image analysis Immunology, particularly autoimmune diseases and immune cell interactions Generative models for dynamic cellular imaging Bayesian statistical methods in microscopy data analysis Her work spans molecular-level studies, computational modeling, and software development for super-resolution and single-molecule localization microscopy (SMLM). Key publications appear in Nature Methods , Cell Reports , and Nature Protocols . Scientific Awards : Wallenberg National Program for Data-Driven Life Science (DDLS) Fellow

• Cyber-Physical Systems
• Embedded Control Systems
• System Reliability
• +5 more

Martin Törngren is a Professor of Embedded Control Systems at the Department of Mechatronics and Department of Mechanical Engineering at KTH Royal Institute of Technology. He is actively engaged in research and teaching within Embedded Systems , Mechatronics , and Cyber-Physical Systems , focusing on architecture, model-based development, and system integration. His work bridges control systems and embedded systems, emphasizing reliability and safety in industrial applications. Research Leadership: Technical coordinator of the Artemis project iFEST, focusing on functional safety for automated systems. Education: Teaches courses like Cyber-physical Systems (MF2140) , Mechatronics Higher Course , and doctoral-level courses in embedded systems. Research Interests: Törngren's work spans model-based systems engineering , distributed control systems , co-design of control and computer systems , and system safety . He emphasizes industry-university collaboration , particularly with the automotive and automation sectors. His publications highlight trends in automated driving safety , edge computing , and toolchain integration . Collaborative Initiatives: He co-founded the Innovative Centre for Embedded Systems (ICES) and participates in networks like Artist2 and ArtistDesign. His research projects often involve partnerships with global companies and academic institutions.

• Digitalization
• Healthcare Informatics
• Artificial Intelligence
• +5 more

Magnus Bergquist is a Professor of Informatics at Halmstad University, affiliated with the School of Information Technology. He joined the university in 2013 as a visiting researcher and became a full professor in 2015. He also serves as Program Director for Halmstad University’s Knowledge Foundation Environment – Research for Innovation, leading initiatives like the OSMaaS project on sustainable mobility and the Sharging initiative for electric vehicle charging platforms. His research spans digitalization’s societal impacts, organizational agility, and AI-driven healthcare innovations. Key areas include the open-source model’s role in innovation, digital radiology workflows, and cultural dimensions of digital transformation. Bergquist holds an ethnology background, employing ethnographic methods to study collaborative practices in digital contexts. Bergquist’s work emphasizes stakeholder-centric approaches, as seen in his analysis of AI integration in clinical radiology and climate-conscious information systems. His contributions include frameworks for Mobility as a Service (MaaS) and studies on organizational adaptability in startups. He has led projects such as ‘Designing Open and Self-Organising Mechanisms for Sustainable Mobility as a Service’ and ‘Sharging’, addressing mobility and energy challenges. His recent focus includes AI’s ethical implications in healthcare decision-making and sustainable service ecosystems. He collaborates actively with industry partners to bridge academic research and practical innovation, fostering interdisciplinary solutions for societal and environmental challenges.

Oleg SysoevView profile

Academic

• Monotonic Regression
• Data Mining
• Machine Learning
• +4 more

Oleg Sysoev is a Senior Associate Professor in the Department of Computer and Information Science (IDA) at Linköping University, Sweden. He specializes in Statistics and Machine Learning, contributing to the Master's program 'Statistics and Machine Learning'. His academic background includes a Master's in Applied Mathematics from Russia and a doctoral thesis in Statistics at Linköping University (2010), focusing on monotonic regression for large datasets. Research Interests: Monotonic regression and interpolation Machine learning methods (decision trees, kernel smoothing, neural networks) Data mining in public health Bootstrap methods and computational statistics Optimization techniques Grants & Collaborations: Lead researcher in a SEK 13 million project (Swedish Research Council) applying AI to forensic analysis for solving murders. Member of the Wallenberg AI, Autonomous Systems and Software Program (WASP), a major Swedish research initiative. Associated with the Division of Statistics and Machine Learning (STIMA), focusing on data-driven methodologies. Teaching & Academic Leadership: Responsible for teaching at undergraduate and graduate levels in statistics and machine learning. Supports curriculum development for the Master's program in Statistics and Data Mining.

• Cloud Computing
• Big Data Pipelines
• Machine Learning
• +4 more

Mihhail Matskin is a Professor at the Royal Institute of Technology (KTH) within the Department of Software Logic & Computer Systems. He specializes in cloud computing, big data pipelines, machine learning, and distributed systems. His work emphasizes optimizing cloud resource allocation, developing graph-based cost models, and advancing AI-driven systems like SQL recommendation engines and relation extraction frameworks. He actively contributes to KTH's educational mission through roles as examiner and course manager in advanced computer science and engineering courses, including Distributed AI, Cloud Storage Optimization, and Big Data Workflow Design. His research spans over two decades, focusing on scalable data management solutions, edge computing applications in healthcare, and semantic analysis of social media. Notable projects include the DataCloud initiative for big data pipeline orchestration and the DEF-PIPE DSL visualization framework. Matskin’s work bridges theoretical advancements with practical implementations, addressing challenges in reproducibility of LLM-based systems, containerized edge computing, and constraint programming for robotics. His academic contributions include pioneering studies on cloud cost modeling, rule-based storage tiering, and contrastive learning for NER tasks. He has advised numerous advanced-level degree projects across computer science, embedded systems, and communication technologies. Matskin’s lab focuses on innovative solutions at the intersection of distributed systems, AI, and data engineering.

Sanjay SomanathView profile

Research Fellow

• Social Sustainability
• Computational Design
• Geographic Information Systems
• +3 more

Sanjay Somanath is a Research Fellow at Chalmers University of Technology's Department of Architecture and Civil Engineering. His research focuses on computational approaches to urban social sustainability, specializing in activity-based accessibility modeling, GIS applications, and digital tool development for neighborhood planning. He collaborates with sustainable building researchers including Alexander Hollberg and Holger Wallbaum. Education PhD (2024) - Chalmers University of Technology: 'Instruments of Inquiry for Urban Social Sustainability' M.Arch Digital Architecture and Tectonics (2018) - University of Nottingham B.Arch (2017) - BMS College of Engineering, Bangalore Research Focus Somanath's work centers on operationalizing urban social sustainability through digital frameworks. He develops computational instruments like activity-based accessibility models that simulate resident behaviors to evaluate neighborhood equity. His research bridges social theory with technical implementation, creating tools for participatory urban planning and sustainability assessment. Recent work explores digital twins for multi-domain urban simulation, machine learning for urban quality inference, and procedural generation of 3D city models. These contributions advance data-driven approaches for evaluating social infrastructure coverage and environmental impacts. Projects & Collaborations Developed Twinable: Interactive tool for socially sustainable neighborhood planning Contributed to DecarbonAIte: AI-based urban modeling for energy and environmental factors Collaborates with Sustainable Building research group at Chalmers

Daniel JönssonView profile

Associate Professor

• Visualization
• Machine Learning
• Medical Imaging
• +3 more

Associate Professor Daniel Jönsson works at the intersection of visualization and machine learning at Linköping University's Department of Science and Technology (ITN) and Media and Information Technology (MIT) division. He leads research in transforming complex datasets into intuitive visual representations, with applications in medical imaging and neuroscience. As a core developer of the Inviwo visualization software, he emphasizes interdisciplinary collaboration across fields like AI and radiology. His work includes developing tools like VisualNeuro for brain cohort studies and exploring neural network interpretability. Research focuses on visualization techniques for high-dimensional data, including fMRI analysis and neural network exploration. Notable achievements include an honorable mention at the IEEE VIS conference (2016) for brain imaging visualization work. Collaborations with CMIV (Center for Medical Image Science and Visualization) highlight his commitment to clinical and medical research applications. Publications emphasize combining visualization with machine learning, addressing challenges in data readiness for AI projects and improving neural network analysis. His contributions span software development, algorithm design, and cross-disciplinary methodological advancements in data-driven decision-making.

Anita ÖstView profile

Professor

• Epigenetics
• Metabolic Disorders
• Obesity Research
• +6 more

Anita Öst is a Professor and Head of Division at Linköping University's Department of Biomedical and Clinical Sciences within the Faculty of Medicine and Health Sciences. She leads The Division of Cell and Neurobiology (CNB), where her research bridges molecular biology, epigenetics, and metabolic disease. Her work has significant implications for understanding how parental lifestyle factors influence offspring health. Dr. Öst's research focuses on epigenetic mechanisms of metabolic disease inheritance, particularly how paternal diet affects sperm composition and subsequent embryo development. Her groundbreaking work has demonstrated that human sperm rapidly responds to dietary changes, especially sugar intake, with alterations in mitochondrial metabolism and small RNA profiles. She investigates how these sperm modifications may program offspring for obesity and type 2 diabetes, drawing connections to historical observations like the Dutch Hunger Winter effects. Her publication record shows a clear progression from studying adipocyte insulin resistance in type 2 diabetes patients during her PhD to her current focus on intergenerational epigenetic transmission. Recent work emphasizes small RNA in sperm as key mediators of paternal effects on offspring metabolism, with applications in understanding obesity and metabolic disorders across generations. Wallenberg Academy Fellow Rosalind Franklin Society Award (2023) Recipient of funding from Swedish Research Council (SEK 49 million for collaborative projects) Professor Öst mentors several PhD students and collaborates with researchers across disciplines. Her lab has secured significant research funding, including from the Swedish Research Council, to investigate epigenetic inheritance mechanisms. Current projects examine diet-driven sperm modifications across species, small RNA roles in male fertility, and how sperm RNA influences embryonic development. Her research group operates within The Division of Cell and Neurobiology, utilizing fruit fly models alongside human studies to unravel the molecular basis of metabolic disease inheritance. The team combines molecular biology, bioinformatics, and clinical approaches to investigate how parental lifestyle choices create metabolic 'memories' that affect future generations.

Einav Peretz AnderssonView profile

Lecturer

• AI Transformation
• Organizational Change
• Digital Transformation
• +3 more

Einav Peretz Andersson is a Lecturer at the Department of Computer Science and Informatics, School of Engineering, Jönköping University, Sweden. She serves as program manager for the AI Engineering Master of Science program. Her research focuses on AI transformation and organizational change, with ongoing interdisciplinary collaborations involving Norwegian University of Technology and Luleå University of Technology. Education: MBA from Jönköping University and Master in Public Policy and Economics from Tel Aviv University, Israel Research emphasizes AI implementation in public sectors and SMEs, leveraging digital transformation frameworks. Her work bridges organizational adaptation, resource orchestration, and policy-driven innovation. Collaborations include international projects on AI governance in public institutions. No specific grants or awards are listed, though her role in program management highlights active involvement in academic administration.

Peter JohanssonView profile

Professor

• Digital Health
• Chronic Disease Management
• Mental Health
• +3 more

Peter Johansson is a Professor at the Department of Nursing and Reproductive Health (Avdelningen för omvårdnad och reproduktiv hälsa), part of the Faculty of Medicine (Medicinska Fakulteten) at Linköping University. He also serves as Research Director at Närsjukvården i Öster, RegionÖstergötland. His roles combine academic leadership with clinical research and education. Education & Career: PhD in Medicine from Linköping University (2008) Guest Researcher at University Medical Center Groningen, Netherlands (2009) Docent in Medical and Health Sciences (2012) Associate Professor (2017) and Professor (2018) at Linköping University Research Interests: Johansson’s work focuses on digital interventions for chronic disease patients, particularly cardiovascular patients, and informal caregivers. His group, Gruppen för digital hälsa och vård , develops internet-based cognitive behavioral therapy (iCBT) programs tailored for depression management in heart disease patients. He also studies stress reduction strategies for healthcare workers via massage and mindfulness, and caregiver support systems leveraging digital tools. Key areas include: Psychological well-being in chronic illness Telemedicine and digital health Healthcare workforce resilience Public health innovations Key Projects: DOHART 2: Evaluates personalized iCBT for cardiac patients. INSERT: Designs support programs for kidney transplant candidates. IKSIT: Targets anxiety in non-cardiac chest pain patients. Digital Support Programs: Pilot studies for informal caregivers. Labs/Teams: Leads the transdisciplinary Forskningsgruppen för digital hälsa och vård , collaborating with nurses, psychologists, and clinicians to advance digital health solutions. Future Work: Expanding caregiver support programs, optimizing iCBT personalization, and exploring AI-driven health monitoring in primary care settings.

• Artificial Intelligence
• Machine Learning
• Blockchain Technology
• +4 more

Zeinab Shahbazi is a Senior Lecturer in the Department of Computer Science at the Faculty of Natural Science. With nine years of expertise, her research focuses on AI-driven solutions for complex data challenges, including machine learning, blockchain, and natural language processing. Current role: Senior Lecturer in Computer Science Research affiliations: Faculty of Natural Science Her work integrates advanced AI techniques to address real-world problems such as climate misinformation detection, security patch optimization, and healthcare data security. She leads collaborative projects like the 2024-2025 International Staff Exchange in Emerging Technologies. Recent research emphasizes interdisciplinary applications, spanning climate informatics, cybersecurity, and recommendation systems. Over 38 publications highlight her contributions to machine learning frameworks and blockchain-based solutions.

• Software Quality Characteristics
• Self-Adaptive Systems
• Model-Based Analysis
• +4 more

Diego Perez-Palacin is a Senior Lecturer in the Department of Computer Science and Media Technology at Linnaeus University, Sweden. He holds a PhD in Computer Science from the University of Zaragoza, Spain. Previously, he served as a postdoctoral researcher at Politecnico di Milano (2013-2016) and a Senior Researcher at the University of Zaragoza (2017), contributing to European (FP7/H2020) and Spanish national research projects. Research Interests: His work focuses on software quality properties, self-adaptive systems, model-based analysis using formal methods, and resilience engineering. Key areas include cyber-physical systems, digital twins, and uncertainty management in adaptive systems. His research groups include AdaptWise (self-adaptive software), Cyber-Physical Systems (CPS), and Engineering Resilient Systems (EReS). Projects: Current projects include developing Digital Twins of Organizations (DTO) and aligning architectures for DTO (Aladino). Completed projects include Smart-Troubleshooting in the Connected Society. His work often involves collaboration with interdisciplinary teams in data-intensive applications and smart industry. Publications: Over 30 peer-reviewed articles in journals like ACM Transactions on Autonomous and Adaptive Systems, IEEE Access, and Journal of Systems and Software. Recent work emphasizes digital twin frameworks, antifragile systems, and uncertainty propagation in adaptive systems.

• MedTech Innovation
• Business Model Innovation
• Entrepreneurship
• +5 more

Professor Jeaneth Johansson holds a dual role as a Professor of Business Administration specializing in Accounting and Financial Decision-Making, and as Vice Dean for Research at Halmstad University's School of Business, Innovation and Sustainability. She leads research initiatives in MedTech innovation, sustainability, and entrepreneurial decision-making processes. Her work bridges theoretical frameworks with practical business development guidance, particularly in healthcare commercialization and environmental measures in agricultural sectors. Johansson contributes to interdisciplinary programs such as the mandatory Supervisory course for Associate Professors and manages the Information-Driven Care research program. Her research spans institutional logics, digital health technologies, and the nexus between sustainability practices and financial performance. Key collaborations include the EU Taxonomy alignment in real estate markets and biogas-based industrial symbiosis projects. She has published extensively in journals like Entrepreneurship Theory and Practice, Journal of Management Studies, and Technovation, focusing on themes like venture capital decision-making biases, rural entrepreneurship, and crisis-driven business model adaptations.

• Data Science
• Machine Learning
• Machine Vision
• +8 more

Roger G Nyberg is a Senior Lecturer at Dalarna University's School of Information and Engineering, Department of Information Science. He holds a PhD from Edinburgh Napier University (2016) and teaches courses in artificial intelligence, data science, software engineering, and project management. As head of the Informatics main field of studies, he oversees programs in Systems Science, Graphic Design and Web Development, and Digital Services. His research focuses on Data Science, Machine Learning, Machine Vision, and Monitoring, with applications in transportation, healthcare, and e-commerce. Key areas include automating decision-making processes, analyzing road conditions using acoustic and visual data, and studying hygrothermal transfer in building materials. Recent publications highlight work on gravel road condition evaluation using multimodal deep learning, CO2 emissions in parking systems, and exercise interventions for musculoskeletal pain. Nyberg supervises undergraduate and advanced theses and actively contributes to academic boards and committees at Dalarna University.