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Franziska KlüglView profile

Professor

• Multi-Agent Systems
• Agent-Based Simulation
• Artificial Intelligence
• +4 more

Franziska Klügl is a Professor in Computer Science at Örebro University's Faculty of Business, Science and Engineering, affiliated with the Center for Applied Autonomous Sensor Systems (AASS). She currently leads the KKS-funded TeamRob project on Human-Robot Teamwork and serves as Deputy Dean of the faculty since January 2023, chairing the academic appointment committee. Previously, she headed the Computer Science department (2020-2022) and served on the faculty board (2019-2022). Her research focuses on: Multi-agent systems : Development of languages, processes, and tools for agent-based simulation Interdisciplinary applications : Transportation, economics, epidemics, production, and mining simulations Simulation engineering : Integrating AI, machine learning, and formal methods to create accessible modeling tools for domain experts She created SeSAm , a visual programming tool for agent-based simulation that enables rapid prototyping of complex models. Analysis of her recent publications reveals three dominant themes: Human-robot collaboration frameworks and intention recognition systems Economic impacts of automation on labor markets and engineering services Advanced simulation methodologies using affordance theory and reinforcement learning She teaches software engineering, multi-agent systems, and agent-based modeling across multiple programs, including the WASP AI&ML PhD course. She leads research groups at the Machine Perception and Interaction Lab and oversees the TeamRob human-robot teamwork project.

Zebo PengView profile

Professor

• Embedded Systems
• Electronic Design Automation
• SoC Testing
• +6 more

Zebo Peng is a Professor and Deputy Head of Department at Linköping University's Department of Computer and Information Science (IDA), leading the Software and Systems (SAS) division. His research focuses on embedded systems design, electronic design automation, SoC testing, and real-time systems with emphasis on fault tolerance and hardware/software co-design. He has contributed to projects like the ASTECC initiative, funded by the Swedish Foundation for Strategic Research, addressing adaptive software in edge-cloud continuum systems. Key research interests include cyber-physical systems security, time-sensitive networking (TSN), and optimization techniques using genetic algorithms. Recent work explores thermal-aware design for reliability, security-aware scheduling, and stability guarantees in control systems. His publications span journals like IEEE TPDS and ACM TECS, alongside conference contributions on topics like resource management and fault detection in distributed systems. Prof. Peng collaborates extensively within the SAS division, which bridges academic and industrial research in software engineering and computer systems. His team's projects address challenges in real-time systems, embedded security, and parallel computing architectures.

Daniel EdlerView profile

Researcher

• Network Science
• Biodiversity
• Ecological Modeling
• +3 more

Daniel Edler is a Researcher and Postdoctoral Fellow at the Department of Physics, Umeå University. His work focuses on network science, biodiversity analysis, and ecological modeling, with a particular emphasis on developing computational tools for community detection and biogeographical mapping. He contributes to interdisciplinary research, integrating methods from computer science, ecology, and information theory. Edler leads the development of Infomap Bioregions, a tool for mapping biogeographical regions using species distribution data, and CoordinateCleaner, which standardizes biological occurrence records. His research also explores threats to Madagascar’s biodiversity and the interplay between socio-political factors and biodiversity data availability through tools like Bio-Dem. He has co-developed raxmlGUI 2.0, a phylogenetic analysis interface, and contributes to the Infomap software package for network analysis. Edler’s publications highlight themes in higher-order network flows, multilayer community detection, and ecological network modules. His work appears in journals such as Science , American Journal of Botany , and Methods in Ecology and Evolution . He is an active member of the Complex Systems research group at Umeå University.

• Space Robotics
• Control Theory
• Computer Vision
• +4 more

Pedro Roque is a Postdoctoral Researcher at KTH Royal Institute of Technology in Stockholm, affiliated with the Wallenberg AI, Autonomous Systems and Software Program (WASP) and associated with the Division of Decision and Control Systems (DCS). He obtained his Ph.D. in 2024 from the same division under the supervision of Prof. Dimos Dimarogonas, Prof. Mikael Johansson, and Prof. Jana Tumova. His research focuses on practically applicable theoretical results in robotics and control, with emphasis on space and aerial systems. Dr. Roque is particularly interested in developing algorithms that directly contribute to system performance and enhanced capabilities. He currently leads the setup of a Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project. He is an advocate for open-source software and hardware, contributing to NASA Astrobee and PX4 projects, with his research tested on the International Space Station and indoor flight arenas. Dr. Roque's work demonstrates a clear progression from theoretical foundations to practical implementation in space environments. His recent publications show an increasing focus on multi-agent coordination in microgravity, with significant contributions to model predictive control for space robotics applications. The research spans from fundamental control theory to complete system implementation, reflecting his commitment to bridging theory and practice. ICRA 2022 Outstanding Coordination Award for work on decentralized model predictive control for collaborative UAV bar transportation Dr. Roque actively mentors Master's students in Space Robotics, Control, and Vision, with supervision details available on his personal website. He has collaborated extensively with NASA Astrobee and PX4 projects, and his DISCOWER project involves collaboration with 3 Ph.D. students, 2 Master's students, 6 Professors, and one Post-doc. He also completed a 4-month internship at JPL within the Maritime and Multi-Agent Systems group. He leads the Space Robotics Laboratory at KTH, associated with the Space Center and the WASP NEST DISCOWER project, which has already demonstrated capabilities to Digital Futures, SAAB AB, SAAB Inc., and Purdue scholars. The laboratory focuses on weightless robotics, collaborative robotics (Space Cobot), and exploration robotics (MoonHopper), with practical testing on the International Space Station.

Gerardo SchneiderView profile

Professor

• Formal Specification and Analysis of Contracts
• Formalization of Privacy Policies
• Model Checking
• +5 more

Gerardo Schneider is a Full Professor in Computer Science at the University of Gothenburg, Sweden, and holds a joint appointment at Chalmers University of Technology. He serves as Head of the Data Science and Artificial Intelligence (DSAI) Division and has previously led the Formal Methods Division and acted as Director of Graduate Studies. University of Gothenburg: 2009–present Chalmers University of Technology: 2009–present Uppsala University: 2002–2003 University of Oslo: 2005–2009 His research focuses on formal methods for software engineering, including contract specification and analysis , privacy policy formalization , model checking , and runtime verification . He works on verification of real-time systems, embedded systems (e.g., smart Java cards), and blockchain-based smart contracts. Key projects include: X-LEGAL (2020–2023): Smart Legal Contracts (Swedish Research Council) PolUser (2016–2019): User-Controlled Privacy Policies (Swedish Research Council) ARVI (2014–2018): Runtime Verification Beyond Monitoring (ICT COST Action) ReMU (2013–2017): Reliable Multilingual Digital Communication (Swedish Research Council) He has supervised numerous PhD and Master’s students in formal methods, blockchain security, and privacy compliance. His tools include SPeeDI (Polygonal Hybrid Systems Verification), CLAN (Contract Normative Conflict Detection), and AnaCon (Controlled Natural Language Analysis).

Tran Duc MuoiView profile

Assistant Professor

• Network Security
• Blockchain Security
• Internet Routing
• +2 more

Muoi Tran is an Assistant Professor at Chalmers University of Technology and leads the Secura Lab , affiliated with the Department of Computer Science and Engineering. His research focuses on network security , blockchain security , and Internet routing , particularly addressing vulnerabilities in cryptocurrency systems and distributed networks. He earned a Ph.D. in Computer Science from the National University of Singapore (2022), supervised by Zhenkai Liang and Min Suk Kang, and completed a postdoc at ETH Zurich under Laurent Vanbever. His work spans novel attacks on network infrastructure, blockchain peer-to-peer networks, and countermeasures for secure Internet routing. Recent publications highlight his expertise in Automated analysis of proxy smart contracts (ICDCS '25) Differential fuzzing for blockchain consensus (ICSE '25) Privacy attacks in the Lightning Network (IEEE SP '24) Partitioning attacks on Bitcoin (EuroS&P '23) His research has been recognized by grants such as the WASP Academic Doctoral Student Projects funding . Secura Lab collaborates with institutions like ETH Zurich and NTU (Taiwan), focusing on network security for AI systems, proxy contract vulnerabilities, and distributed resilience. Muoi actively mentors and recruits students for projects at the intersection of AI and network security.

Andreas J. KasslerView profile

Professor

• Software Defined Networking
• Programmable Dataplanes
• Network Virtualization
• +7 more

Andreas J. Kassler is a Full Professor of Computer Science at Karlstad University, Sweden, where he has been since 2005. He co-chairs the Distributed Systems and Communication (DISCO) group and focuses on networking, cloud computing, and wireless networks. His research includes software-defined networking, future internet architectures, and network optimization. He has authored/co-authored over 130 peer-reviewed publications, holds 6 patents, and serves on editorial boards of journals like Journal of Internet Engineering . Education : Ph.D. in Computer Science, Universität Ulm (2002) Docent (Habilitation), Karlstad University (2007) M.Sc. in Mathematics/Computer Science, Universität Augsburg (1995) Research Interests : Software Defined Networking (SDN) Programmable Dataplanes Wireless Mesh Networks Time-Sensitive Networking (TSN) Edge Computing Machine Learning for Network Optimization Recent Directions : His work spans TSN scheduling, hybrid P4 solutions for 5G, and explainable AI in energy communities. He explores network resilience, latency optimization, and multi-objective control in microgrids. Service Contributions : Track co-chair for VTC 2015 General chair for Wired/Wireless Internet Communications (WWIC) 2013 Editor-in-Chief of IARIA Journal on Advances in Internet Technology Labs/Teams : Leads DISCO group at Karlstad University. Collaborates with global teams on projects like mmWave backhaul networks and SDN-enabled industrial control systems.

Anna BrunströmView profile

Professor

• Computer Networking
• Internet Architectures
• 5G/6G Mobile Systems
• +3 more

Anna Brunström is a Full Professor and Head of the Distributed Intelligent Systems and Communications Research Group (DISCO) at Karlstad University's Department of Computer Science. She holds a part-time role as a Researcher at the University of Malaga's Institute of Software Engineering and Technologies (ITIS). Her research focuses on computer networking, Internet architectures, low latency communication, and 5G/6G mobile systems. She leads the nationally funded DRIVE initiative and collaborates on European projects like 6G-PATH. She actively contributes to IETF standardization, notably as a former rmcat WG chair. Her work spans over 200 publications, emphasizing network measurement, latency optimization, and multipath protocols. Education: Ph.D. (1996) and M.Sc. (1993) from College of William & Mary, B.Sc. (1991) from Pepperdine University. Research Interests: Distributed systems, IoT networking (NB-IoT), satellite communication (Starlink), machine learning for positioning, and transport protocols (QUIC, MPTCP). Recent work includes latency-aware scheduling, 5G/6G performance analysis, and edge computing frameworks. Publications highlight trends in: 1) Satellite network throughput modeling, 2) 5G/6G architecture validation, 3) Machine learning applications for positioning and network analysis, 4) Cross-layer optimization of latency-critical services. Collaborations with industry and academia drive applied research in smart grids, healthcare, and automotive communication. Labs/Teams: DISCO group at Karlstad University, leading the DRIVE research profile and 6G-PATH consortium involvement.

• Forecasting
• Time Series Analysis
• Inventory Management
• +5 more

Nikolaos Kourentzes is a Professor of Informatics at the University of Skövde , specializing in forecasting and operations research. His work bridges theoretical advancements in time series analysis with practical applications in supply chain management, tourism demand, and renewable energy forecasting. Academic Rank: Professor Department: Department of Information Technology Research Interests: His research focuses on hierarchical and temporal forecasting methodologies, integrating macroeconomic indicators into demand planning, inventory optimization, and machine learning applications. He explores forecast reconciliation, shrinkage estimators, and the role of expert judgment in predictive analytics. Recent Publications: Highlights include advances in hierarchical forecasting with leading indicators, probabilistic forecasts during crises like the pandemic, and complex smoothing techniques. His work spans journals such as Omega , International Journal of Forecasting , and European Journal of Operational Research . Collaborations: Kourentzes collaborates with researchers globally, including George Athanasopoulos, Rob Hyndman, and Robert Fildes, across domains like tourism analytics, tire industry forecasting, and public health modeling.

• Program Verification
• Proof Engineering
• Formal Methods
• +4 more

Karl Palmskog is a Lecturer at KTH Royal Institute of Technology in the Division of Theoretical Computer Science and the STEP research group. His work focuses on program verification and proof engineering, with particular emphasis on developing techniques and tools based on proof assistants for constructing functionally correct and secure software systems. Palmskog received his Ph.D. in Computer Science in 2014 from KTH, advised by Mads Dam, and his M.Sc. in Computer Science and Engineering from KTH in 2007. Prior to his current position, he was a postdoc at The University of Texas at Austin and University of Illinois at Urbana-Champaign. His research interests span programming languages, software engineering, and formal verification, with a particular focus on developing techniques and tools based on proof assistants. He is an avid user of the Coq proof assistant for both proving and programming, often complemented by OCaml, and also utilizes HOL4 and other ML family dialects. His work bridges theoretical foundations with practical applications, particularly in the domains of blockchain systems, distributed systems, and automotive software verification. Analysis of his recent publications reveals a strong focus on Coq-based verification, with significant contributions to proof engineering tools and methodologies. His work includes developing tools for regression proving, change impact analysis, mutation testing for Coq projects, and lemma name suggestion using deep learning. There's also a growing trend toward applying formal methods to real-world systems like blockchain protocols and automotive software. Palmskog has been involved in several research projects, including Coq-community Proof Engineering and Distributed Components. His past projects include Trustfull (SSF), Model-based Event Driven Scalable Programming for the Mobile Cloud (NSF), Highly Adaptable and Trustworthy Software (EU FP7), and 4WARD Future Internet (EU FP7). As an educator, Palmskog has served as examiner, course responsible, teacher, and assistant for various courses including Algorithms, Data Structures and Complexity; Degree Projects; Game Theory; Parallel and Distributed Computing; and Programming Paradigms. His work on Chip, a Coq formalization of change impact analysis, demonstrates his commitment to creating practical, certified tools that bridge formal methods with software engineering practice.

Vladimir VlassovView profile

Professor

• Machine Learning
• Data-intensive computing
• Cloud computing
• +7 more

Dr. Vladimir Vlassov is a full Professor in Computer Systems at the Division of Software and Computer Systems (SCS) , Department of Computer Science (CS) , School of Electrical Engineering and Computer Science (EECS) , KTH Royal Institute of Technology , Stockholm, Sweden. He leads the AVA project in ALEC2, an AI-powered system for mental health care. He is a member of the Distributed Computing research group (DC@KTH) . Education & Roles: Holds a PhD and is a member of ACM and IEEE. Previously visited MIT (1998) and UMass Amherst (2004). Teaches courses on Data Mining , Distributed Systems , and Concurrent Programming . Research Interests: Focus on scalable AI, Cloud computing, distributed systems, and NLP for mental health. Projects include ExtremeEarth (Copernicus data analytics) and EMJD-DC (distributed computing PhD program). Grants & Projects: Principal Investigator in ALEC2 (adaptive mental health care) and ExtremeEarth (EU H2020). Led EU projects like ENCORE (manycore systems) and PaPP (embedded systems). Labs & Teams: Directs the Distributed Computing group, contributing to Hopsworks (machine learning feature store) and Maggy (hyperparameter optimization).

• Control Systems
• Real-Time Systems
• Cloud Computing
• +3 more

Anton Cervin is a Senior Lecturer (on Leave of Absence) at the Department of Automatic Control, Lund University. He is affiliated with the LTH Profile Area: AI and Digitalization. His roles include Director of First and Second Cycle Studies, Deputy Head of the Department (2019–2022), and Director of the China Profile at LTH (2008–2012). Research focuses on real-time systems, control over cloud platforms, event-based control, and cyber-physical systems. Key projects include the Swedish Research Council-funded 'Event-Based Control of Stochastic Systems' and WASP-supported 'Event-Based Information Fusion for Self-Adaptive Cloud'. Developed software tools: TrueTime (real-time simulator), JitterTime, Jitterbug, and TinyRealTime. Recognized with multiple Best Paper Awards at ECRTS, RTNS, and RTCSA conferences. Supervised over 5 PhD students in real-time control and embedded systems. Teaching includes advanced courses on automatic control, systems engineering, and real-time systems. His work aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) through contributions to smart infrastructure and cloud-based control systems.

Elena TroubitsynaView profile

Professor

• Autonomous Systems
• Software Engineering
• Formal Verification
• +3 more

Elena Troubitsyna is a Professor of Computer Science with specialization in Software Engineering at KTH Royal Institute of Technology. Her research focuses on developing dependable, autonomous systems that ensure safety and reliability, particularly in complex environments like self-driving cars and drones. She employs rigorous mathematical modeling and verification techniques to address system complexity and real-time adaptability challenges. Her work emphasizes the co-engineering of safety and security in cyber-physical systems, integrating formal methods such as Event-B modeling with AI-driven solutions. Key research areas include cybersecurity for embedded systems, formal analysis of safety-security interactions, and resilient multi-agent systems. Elena has contributed to advancing methods for autonomous system navigation, fault tolerance, and privacy-preserving microservices architectures. Elena has organized international workshops like SENSEI (Safety-Security Interaction) and published extensively on topics such as model-driven engineering, formal verification of critical systems, and optimizing scheduling for distributed computing. Her research bridges theoretical foundations with practical applications, aiming to enhance societal trust in autonomous technologies.

• Scientific Computing
• Computational Fluid Dynamics
• Finite Element Methods
• +3 more

Johan Jansson is an Associate Professor in Scientific Computing at KTH Royal Institute of Technology and BCAM (Basque Center for Applied Mathematics). He leads research in predictive Direct FEM Simulation (DFS) for aerodynamics and multiphase flows, and co-founded Icarus Digital Math as CEO. His work includes the FEniCS open-source finite element software project and MOOC-HPFEM educational initiatives. He holds roles as Director of the Center for Digital Math and collaborates internationally in computational science. Research focuses on high-performance computing (HPC), fluid-structure interaction (FSI), biomedical modeling, and renewable energy systems. Notable contributions include adaptive FEM frameworks for turbulent flow, vocal fold simulations, and wave energy converter modeling. His work bridges academic research with industrial applications, leveraging FEniCS-HPC and Unicorn solvers. Key achievements include election to the IVA Royal Swedish Academy of Sciences 100-list and securing the Severo Ochoa Center of Excellence Award. He has pioneered open-source tools like SimTek and contributed to major projects like the Salter Sink and vocal production modeling. Teaching responsibilities include courses on database technology, computational fluid mechanics, and research methodology. He actively engages in large-scale simulation projects involving marine energy, cardiac ablation protocols, and aerodynamic optimization.

• Distributed/Parallel Computing
• Information Visualization
• Fault-Tolerant Communication Mechanisms
• +4 more

Philippas Tsigas is a Professor at the Department of Computer Science and Engineering at Chalmers University of Technology. He leads the Distributed Computing and Systems Research Group and has held roles as co-leader of research initiatives such as the PEPPHER project. His research spans distributed/parallel computing, information visualization, and fault-tolerant communication mechanisms. He has supervised numerous PhD students, including Yi Zhang, Håkan Sundell, and Farnaz Moradi. Research interests include lock-free data structures, multicore algorithms, secure network services, and visualization tools like Lydian and DataMeadow. Notable awards include Best Paper Awards at IPDPS 2003 and SNS 2012. His work has been published in top venues like IEEE Transactions on Parallel and Distributed Systems and ACM Journal of Experimental Algorithmics. Awards highlight contributions to lock-free algorithms and network modeling. Students have contributed to projects like NBmalloc (memory reclamation) and GPU Quicksort. Collaborations with institutions like SSF and VR have supported his research. Tsigas is also involved in teaching distributed systems and mentoring early-career researchers.