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Jan-Åke LarssonView profile

Professor

• Quantum Technology
• Quantum Information Theory
• Foundations of Quantum Mechanics
• +4 more

Jan-Åke Larsson is a Professor and Head of Department at the Department of Electrical Engineering (ISY) at Linköping University, Sweden. His academic career spans over two decades, with positions progressing from PhD student to Professor and department leadership. He has made significant contributions to quantum information science, particularly in quantum cryptography, quantum computing foundations, and Bell inequality tests. PhD in Applied Mathematics, Linköping University (2000) Docent in Applied Mathematics, Linköping University (2003) Professor Larsson's research primarily focuses on quantum technology, quantum information theory, and the foundations of quantum mechanics. His work explores the resources available to quantum computers that enable quantum advantage, the security of quantum cryptography systems (particularly classical subsystems), and fundamental questions of locality and contextuality in quantum mechanics. He has pioneered research in loophole-free Bell tests and developed theoretical frameworks for understanding quantum contextuality. His recent publications demonstrate a continued focus on foundational aspects of quantum mechanics while expanding into quantum computing algorithms and resource optimization. There's a clear trend toward addressing practical challenges in quantum computing implementation while maintaining a strong theoretical foundation in quantum information science. Contributed to Nobel Prize-winning research on quantum entanglement (2022 Physics Nobel) Key contributor to the "Big Bell Test" experiment published in Nature (2018) Significant contributions to loophole-free Bell inequality tests Professor Larsson has supervised multiple PhD students to completion, including Niklas Johansson (2022), Jonathan Jogenfors (2017), and Aysajan Abidin (2013), with Christoffer Hindlycke currently completing his PhD. His research has been supported by grants from the Swedish Research Council and other national and international funding bodies. He has collaborated extensively with leading quantum research groups worldwide, including those led by Nobel Laureate Anton Zeilinger. As Head of Department at ISY, Professor Larsson oversees one of Sweden's leading electrical engineering research and education units. He is actively involved in the Information Coding (ICG) research group, which focuses on quantum information, cryptography, and communication theory.

• Network Security
• Cybersecurity
• Privacy-Preserving Technologies
• +3 more

Cihan Eryonucu is a Ph.D. student and researcher at the KTH Royal Institute of Technology , affiliated with the Networked Systems Security (NSS) Group and the WASP - Autonomous Systems and Software track . He is supervised by Professor Panos Papadimitratos . Research Focus: Security and privacy in participatory sensing systems, Sybil attack detection, and privacy-preserving protocols for location-based services. Teaching: Assistant roles in courses like Advanced Networked Systems Security (EP2510) and Building Networked Systems Security (EP2520) , and a teacher in Communication System Design (IK2200) . Expertise: His work addresses vulnerabilities in crowdsourced systems (e.g., Google Maps manipulation) and develops cryptographic methods for secure data aggregation. Publications: Recent works explore Sybil attack mitigation via presence verification, privacy-enhancing frameworks for urban sensing, and applications of homomorphic encryption to genomic and location data. Contact: Email eryonucu@kth.se | Room 4444, Kistagången 16, KTH Royal Institute of Technology.

Fredrik WahlbergView profile

Assistant Professor

• Computational Linguistics
• Historical Document Analysis
• Handwriting Recognition
• +3 more

Fredrik Wahlberg serves as Assistant Professor in Computational Linguistics at Uppsala University's Department of Linguistics and Philology, where he develops computational methods for historical manuscript analysis. His work bridges computer science and humanities through machine learning applications in paleography and digital archives. His research encompasses: Computational Linguistics for historical texts Handwriting recognition and word spotting in medieval manuscripts Deep learning for scribal attribution and dating Neural networks for archival image restoration AI-driven metadata enrichment in cultural heritage Analysis of his 2011-2022 publications reveals consistent innovation in combining image processing and language modeling for large-scale manuscript analysis. Key trends include advancing convolutional neural networks for dating accuracy, developing quill-curvature features for writer identification, and extending into critical AI applications for gender-inclusive historical collections. His methodologies significantly enhance accessibility of pre-modern documents through computational approaches.

Piotr RudolView profile

Researcher

• Artificial Intelligence
• Robotics
• Computer Vision
• +5 more

Piotr Rudol is a Researcher at Linköping University's Department of Computer and Information Science (IDA), part of the Artificial Intelligence and Integrated Computer Systems (AIICS) division. His work focuses on advancing artificial intelligence, robotics, and their applications in collaborative systems, autonomous navigation, and UAV technology. Research interests include: Robotics mission planning and coordination Unmanned aerial vehicle (UAV) systems for search and rescue RDF graph synchronization for collaborative robotics Computer vision for object detection and geolocation Multi-agent systems integration His recent articles emphasize autonomous systems, sensor fusion, and distributed robotics frameworks. Notable contributions include frameworks for UAV-based human detection and collaborative mission planning systems. Piotr collaborates with senior researchers like Patrick Doherty and Mariusz Wzorek, contributing to projects funded through institutional research programs. He is actively involved in the IDA department's research initiatives, bridging theoretical AI advancements with practical robotic implementations.

• Ontology Engineering
• Semantic Web
• Data Stream Processing
• +3 more

Robin Keskisärkkä is a Researcher at the Department of Computer and Information Science at Linköping University. His work focuses on ontology engineering, semantic web technologies, data stream processing, and their applications in areas like circular economy, healthcare informatics, and sustainability. He has contributed to advancing methods for handling uncertainty in real-time data streams and developing domain-specific ontologies for diverse fields such as ice hockey and criminal investigations. Key research interests include RDF stream processing, semantic complex event processing (CEP), and the integration of large language models for ontology generation. His recent work explores digital product passports for circular economy frameworks and longitudinal health outcomes analysis in oncology. He has also conducted studies on text simplification techniques for Swedish language. His technical contributions span query languages for streaming data (e.g., RSP-QL*), semantic event boundary detection, and cross-domain ontology networks. His research bridges theoretical computer science with practical applications in environmental sustainability, public health, and criminal justice systems.

• Health Informatics
• Biomedical Informatics
• Electronic Health Records
• +6 more

Erik Sundvall is an Adjunct Associate Professor at the Department of Biomedical Engineering (IMT), Linköping University, Sweden. He is affiliated with the Division of Biomedical Engineering (MT), a national center for research and innovation in biomedical engineering. His work is primarily focused on health informatics, especially electronic health records and openEHR standards. Research Interests: Erik Sundvall's research lies at the intersection of healthcare and information technology. He investigates methods for improving the accessibility, reliability, and performance of electronic health record systems. His work emphasizes openEHR-based modeling, querying large-scale clinical data using distributed systems like Hadoop, and developing benchmark datasets such as ORBDA to evaluate EHR server performance. These efforts contribute to safer, more interoperable, and scalable digital health infrastructures. The recent publications reflect a consistent focus on health informatics, particularly in advancing openEHR adoption, optimizing query mechanisms, and advocating for strategic investment in e-health at national and international levels. His collaborative work spans technical innovation and policy-oriented discourse. Scientific Contributions: Developed ORBDA, a benchmark dataset for evaluating EHR server performance. Explored Dewey-encoded querying of openEHR models using Hadoop for scalability. Contributed to educational strategies for learning openEHR standards. Advocated for international collaboration and national investment in e-health. Advising and Grants: While no formal students or grants are listed in the provided materials, his active research output and leadership in publications suggest involvement in research projects and potential supervision within the biomedical engineering domain at Linköping University. Further details on funding sources or mentored students are not available in the current text. Labs and Teams: Erik Sundvall is part of the Division of Biomedical Engineering (MT) at Linköping University, which functions as a national hub for research, PhD training, and innovation in biomedical engineering. His work likely involves collaboration within interdisciplinary teams focused on health informatics and digital healthcare solutions.

Nikolaos PappasView profile

Associate Professor

• Semantic Wireless Communications
• Age of Information
• Stochastic Modelling
• +7 more

Nikolaos Pappas is an Associate Professor and Docent at Linköping University's Department of Computer and Information Science (IDA), within the Database and Information Techniques (ADIT) division. His research focuses on semantic wireless communications, age of information, stochastic modeling of communication networks, and wireless energy harvesting systems. He leads the Communications for Networked Intelligent Systems Group and serves as an editor for several IEEE journals, including the IEEE Transactions on Machine Learning in Communications and Networking. Education: B.Sc./M.Sc./Ph.D. in Computer Science and Mathematics from the University of Crete (2005–2012). Postdoctoral roles at Supélec (France) and Linköping University (2012–2016). Marie Curie Fellow (2014–2016). Research Interests: Includes semantic communication, tactile internet, IoT, queueing theory, and 6G network architectures. He is a voting member of the IEEE Tactile Internet Working Group and Principal Investigator for projects like 'Semantics-Empowered Communication for Networked Intelligent Systems' (Swedish Research Council, 2022–2025). Awards: Recognized in the Top 2% Scientists List (2020–2023) for Networking and Telecommunications. Leading Horizon Europe projects such as ROBUST-6G and ETHER, focusing on 6G security and hybrid terrestrial/satellite networks. Teaching: Courses on Age of Information, Statistical Learning, and Network Virtualization. Supervises a large team of PhD students and postdocs in ADIT.

Kristina LundqvistView profile

Professor

• Formal Verification
• Autonomous Systems
• Safety-Critical Systems
• +3 more

Kristina Lundqvist is a Professor at Mälardalen University, affiliated with the School of Innovation, Design and Engineering and the Division of Computer Science and Software Engineering. Her work focuses on formal verification, autonomous systems, and safety-critical systems. She holds a Professorship position and contributes to both academic research and industry-relevant solutions. Her research interests emphasize the intersection of formal methods, autonomous systems, and ontology-driven approaches for safety and security. She explores topics such as mission planning for multi-agent systems, hazard analysis, and assurance strategies for cyber-physical systems. Her work bridges theoretical frameworks with practical applications in automotive, aerospace, and industrial automation domains. Dr. Lundqvist’s publications span over two decades, with a strong focus on formal verification techniques, safety-critical software assurance, and ontology development for security and safety domains. Her recent work highlights advancements in scalable strategy synthesis for autonomous systems and the integration of safety and security ontologies for complex systems analysis. Her contributions include frameworks like ACICS for industrial CPS assurance and AQAF for architecture quality assurance in embedded systems. She collaborates on initiatives such as SafeML for training autonomous vehicles and has published extensively in top-tier venues.

Patrick DohertyView profile

Professor

• Artificial Intelligence
• Autonomous Systems
• Knowledge Representation
• +6 more

Patrick Doherty is a Professor and Head of the Artificial Intelligence Laboratory (AILAB) at Linköping University's Department of Computer and Information Science (IDA). His research focuses on knowledge representation, automated planning, and intelligent autonomous systems, with applications in UAV-based emergency rescue and disaster informatics. He leads the AIICS division, emphasizing collaborative robotics and multi-agent systems. He holds a EURAI (ECCAI) fellowship and serves as Editor-in-Chief of the Artificial Intelligence Journal. His work includes developing UAV systems for alpine rescue, real-time mission planning frameworks, and robust robotic collaboration protocols. Notable contributions include the SHERPA project and the RGS RDF graph synchronization system. Doherty's research also addresses human-robot collaboration, safety-critical decision-making, and resilient autonomous systems within the Wallenberg AI, Autonomous Systems and Software Program (WASP). His research group has won international competitions in UAV and automated planning domains, demonstrating advanced UAV deployment in emergency scenarios. Key areas include geolocated object detection, distributed situation awareness, and efficient wireless mesh network configurations for disaster response. Doherty frequently delivers keynote speeches at conferences such as IJCAI, KR, and ECAI, emphasizing practical applications of AI in safety-critical systems. Key Projects: SHERPA (human-robot collaboration in alpine rescue), WASP public safety arena, UAV navigation systems Awards/Fellowships: EURAI Fellow, Editor-in-Chief of Artificial Intelligence Journal Labs/Teams: AILAB, Unmanned Aircraft Systems Technology Laboratory (UASTECH) Publications span foundational AI theory (e.g., forgetting policies, rough set reasoning) to applied robotics (e.g., UAV navigation, real-time search algorithms). His work bridges high-level mission planning with low-level control, ensuring robustness and autonomy in dynamic environments.

Daniel de LengView profile

Assistant Professor

• Applied Human-Centered AI
• Explainable AI
• Autonomous Systems
• +5 more

Daniel de Leng is an Assistant Professor at Linköping University (Sweden), affiliated with the Department of Computer and Information Science (IDA) and the Human-Centered Systems (HCS) division. He is part of the Semantic Web group and focuses on applied human-centered AI, particularly in autonomous systems and explainable AI. His work integrates symbolic and subsymbolic methods to address challenges in real-world AI deployment. Education: PhD (2019) and Licentiate (2017) in Computer Science from Linköping University, and MSc/BSc (2013/2011) from Utrecht University (Netherlands). Research Interests: Stream reasoning under uncertainty, autonomous system safety, and semantic integration in robotics. He developed the DyKnow-ROS framework for robot stream reasoning and contributed to the Stellar AIOps environment for AI research. His work emphasizes human-understandable explanations for AI decisions. Awards: Recipient of the SAIS Master's Thesis Award. Advising & Grants: Managed the AI Academy initiative, part of the AIOps ELLIIT Infrastructure and AI Academy management teams. Previously served as Saab Aeronautics' first Point of Contact for AI (until 2022). Labs & Teams: Active in the Reasoning and Learning Lab (ReaL), Semantic Web group, and Human-Centered Systems division. Collaborates on projects like Urdarbrunnen (AI for combat search and rescue) and multi-agent robotics systems.

Huanyu LiView profile

Assistant Professor

• Semantic Web
• Ontology Engineering
• Data Integration
• +4 more

Huanyu Li is an Assistant Professor at the Department of Computer and Information Science (IDA) of Linköping University, Sweden, within the Human-Centered Systems (HCS) division. His research focuses on Semantic Web and Ontologies, particularly ontology engineering, ontology-driven data integration, and applications in materials design and circular economy domains. Education : PhD in Computer Science, Linköping University (2022) MEng in Software Engineering, Harbin Institute of Technology (2016) BEng in Software Engineering, Harbin Institute of Technology (2014) Research Interests : Ontology engineering and alignment methodologies Domain-specific ontology development (materials science, semiconductor technologies) Interoperability frameworks for heterogeneous data sources Circular economy applications through ontology networks Service Roles : Co-chair of VOILA!, OM, and SeMatS workshops Program committee member for ESWC, ISWC, and other conferences Management committee member of EU COST Action EuMINe Reviewer for journals like Nature Scientific Data and Advanced Engineering Materials Awards : Recipient of the Lawson Stipendium (2022) for contributions to ontology matching and materials science communities Collaborations : Swedish e-Science Research Centre (SeRC) - DCMD group OPTIMADE discussion group on ontologies

Timotheus KampikView profile

Assistant Professor

• Intelligent Systems
• Automated Reasoning
• Formal Argumentation
• +5 more

Timotheus Kampik is a Tenure-Track Assistant Professor at the Department of Computing Science , Umeå University , Sweden. He combines his academic work with an industry role as Principal Scientist at SAP , focusing on strategic research engagement related to intelligent processes, decisions, and transformation. Kampik's research centers on principle-based automated reasoning and the engineering of intelligent systems with applications in multi-agent systems, formal argumentation, and business process management. Kampik is a WASP Fellow supported by the Wallenberg AI, Autonomous Systems and Software Program. His work often bridges theoretical foundations with practical implementations, reflected in both his academic publications and industry contributions. He has served as co-chair for the International Workshop on Argumentation for eXplainable AI (ArgXAI) and organized sessions at major conferences like AAMAS and ECAI. Research Interests: Abstract and Quantitative Bipolar Argumentation Multi-Agent Systems Engineering Explainable AI and Human-AI Interaction Business Process Intelligence Formal Reasoning and Decision Theory Key Publications: Disagree and Commit (2025) - Argumentation-based agreements Kettle Logic in Abstract Argumentation (2024) Change in Quantitative Bipolar Argumentation (2024) Business Process Improvement with AB Testing (2024) Scientific Recognition: Best Paper Award, ICPM 2024 Best Program Committee Member Award, AAMAS 2022 Best Post-Graduate Student Paper Award, WESAAC 2020 WASP Fellowship recipient Teaching & Supervision: Lecturer for courses including Software Engineering and Artificial Intelligence at Umeå University Supervised multiple Master's and Bachelor's theses on topics like machine learning integration, human-aware planning, and deception detection Co-developed open-source agent programming libraries like JS-son

Henny AdmoniView profile

Associate Professor

• Human-Robot Interaction
• Assistive Robotics
• Machine Learning
• +7 more

Henny Admoni is an Associate Professor at the Robotics Institute, Carnegie Mellon University . She leads the Human And Robot Partners (HARP) Lab and is currently a Digital Futures Scholar in Residence at KTH Royal Institute of Technology through August 2025. Her research focuses on human-robot interaction, assistive robotics, and modeling human behavior to develop intelligent systems that collaborate seamlessly with humans. PhD in Computer Science, Yale University MS in Computer Science, Yale University BA/MA joint degree in Computer Science, Wesleyan University Her work integrates methodologies from robotics, machine learning, artificial intelligence, computer perception, and cognitive science , with applications in physical support for daily living, driving assistance, social support networks, and collaborative tasks like household cleanup . She develops algorithms for proactive, fluent, and interpretable robot behavior , leveraging human mental state modeling and eye-gaze analysis. Recent publications include studies on driver situational awareness, robot self-assessment, and human-AI teaming , primarily in venues like IROS, HRI, CoRL, and RSS . Her research has evolved from eye-gaze-based intent prediction to proactive robot learning and strategic human-AI collaboration . Scientific recognition includes: NSF CAREER grant Okawa Research Grant A. Nico Habermann Career Development Professorship Her research is funded by NSF, ONR, Paralyzed Veterans of America Foundation, Google, Meta, and Sony AI . She emphasizes interdisciplinary collaboration and student engagement through weekly lab meetings and structured research opportunities. The HARP Lab explores human-robot shared manipulation, social support AI, and driver assistance systems , with a focus on human psychology and agency in robotic interactions.

Hazem TorfahView profile

Assistant Professor

• cyber-physical systems
• formal verification
• runtime monitoring
• +5 more

Hazem Torfah is a tenure-track Assistant Professor at the Computer Science and Engineering Department at Chalmers University of Technology, where he leads the Safe and Trustworthy Autonomous Reasoning lab (STARlab). Previously, he was a postdoctoral researcher in the EECS Department at UC Berkeley, USA, and obtained his Ph.D. in 2019 from Saarland University, Germany. His research focuses on developing theoretical foundations and techniques for constructing safe and reliable autonomous cyber-physical systems. Hazem earned his Ph.D. from Saarland University in 2019, followed by postdoctoral research at UC Berkeley. His educational background has positioned him at the forefront of formal methods research for autonomous systems. His research interests center on the formal specification, verification, and synthesis of cyber-physical systems, with a particular focus on quantitative approaches for verifying and explaining system behavior. He investigates methods to ensure safety and reliability in autonomous systems through runtime monitoring, specification mining, and assurance frameworks. His work bridges theoretical computer science with practical applications in autonomous driving and robotics. An analysis of his recent publications reveals a strong focus on runtime monitoring techniques for operational design domains, specification mining for predictive safety, and frameworks for runtime assurance of cyber-physical systems. His work frequently combines formal methods with machine learning to address safety challenges in autonomous systems, with applications primarily in autonomous driving. Hazem's research is funded by the Wallenberg AI, Autonomous Systems, and Software Program, reflecting the significance and potential impact of his work in the field of assured autonomy. He has supervised several Master's students, including Samuel Collier Ryder and Johannes Holmgren (2025), and Lucas Karlsson and George Kayembe (2024). His teaching includes courses on Formal Methods for Security, Oracle-Guided Inductive Synthesis, and Data Structures and Algorithms. As the leader of STARlab, Hazem directs research on safe and trustworthy autonomous reasoning, focusing on developing methods to ensure the reliability and explainability of autonomous cyber-physical systems through formal verification techniques.

• 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.