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Andrea BurattinView profile

Associate Professor

• Process Mining
• Business Process Management
• Petri Nets
• +6 more

Andrea Burattin is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark. His work bridges formal methods and practical process analysis, focusing on process mining, business process management, and hybrid modeling techniques. He actively contributes to research in healthcare process optimization, streaming data analysis, and system verification through Petri nets and CCS transformations. UN Sustainable Development Goals: Poverty eradication, environmental protection, and prosperity for all (via process optimization) Active projects: Immersive Process Mining (2024-2027), Usability and Understandability of Hybrid Process Models (2018-2021) His research explores large language model integration with process mining, proposing frameworks like Tiramisù for multi-faceted process visualization and PN2CCS for formal model translation. Recent work emphasizes real-time monitoring, conformance checking, and IoT-driven process analytics. Key trends in his publications include: 1) Streaming process mining pipelines (2022-2025); 2) LLM-plan generation frameworks (2024); 3) Formal verification techniques (Petri nets, CCS); 4) Healthcare process modeling (2019-2023); 5) Behavioral pattern analysis in process compliance. Scientific Awards Best Demo Award (2022, 2016) Best Process Mining Dissertation Award (2014) Best Workshop Paper (EDBA and PODS4H, 2023) As advisor, he supervises PhD projects on process mining and hybrid modeling. His editorial roles include Information Systems reviewer (2024-2025) and past editor for Engineering Applications of AI (2022-2023). Collaborations span Denmark, Italy, and the Netherlands.

• Business Process Management
• Declarative Process Modeling
• Hybrid Process Notations
• +5 more

Tijs Slaats is an Associate Professor in the Software, Data, People & Society section at the Department of Computer Science, University of Copenhagen. His research focuses on Business Process Management with particular emphasis on declarative and hybrid process notations to provide flexible workflow support for knowledge workers, funded by the Danish Council for Independent Research. His educational background includes: M.Sc. in Information Technology from IT University of Copenhagen Ph.D. in Computer Science from IT University of Copenhagen (supervised by Thomas Hildebrandt) Dr. Slaats specializes in declarative process modeling, particularly Dynamic Condition Response (DCR) graphs which enable flexible workflow systems. His work bridges theoretical foundations with practical applications in cross-organizational settings. Recent research extends into blockchain technologies, smart contracts, and applications in sensitive domains like asylum processing and refugee law. He combines formal methods with empirical evaluation to ensure both correctness and usability of workflow systems. His publication pattern shows increasing application of process mining techniques to blockchain technologies and socially impactful domains, while maintaining core research in Business Process Management. Notable trends include integration of DCR graphs with smart contracts, privacy-preserving techniques for asylum data, and object-centric approaches to process discovery. Research funding includes: Hybrid Business Process Management Technologies project (Danish Council for Independent Research) Technologies for Flexible Cross-organizational Case Management Systems (FLExCMS) industrial Ph.D. project Alongside his academic work, Dr. Slaats maintains strong industry connections through Exformatics A/S where he developed the DCR Graphs workflow solution (www.dcrgraphs.net), and previously worked as a software engineer in the Dutch e-commerce sector. His dual expertise in academia and industry ensures his research addresses real-world workflow challenges while maintaining theoretical rigor.

Alvaro TorralbaView profile

Associate Professor

• Symbolic Search
• Artificial Intelligence
• Machine Learning
• +3 more

Alvaro Torralba is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with the Technical Faculty of IT and Design. His research focuses on symbolic search, heuristic functions, and planning algorithms within artificial intelligence and machine learning. Notable projects include the ConAn initiative exploring contrastive analysis for state-space exploration. He has contributed extensively to classical planning, probabilistic planning, and automated planning competitions, earning awards such as the First Prize in the Agile Track of the 10th International Planning Competition (IPC’23). His work often bridges theoretical advancements with practical applications, including game-based network update synthesis and believable non-player character development. Research outputs include over 60 publications since 2011, with a focus on optimizing search algorithms and enhancing planning efficiency through techniques like operator-potential heuristics and bidirectional search strategies. His scientific contributions span algorithmic innovation, verification methodologies, and large-scale abstraction evaluation. Collaborations and datasets include foundational work on PDDL generators and pattern databases, with open-access resources available via Zenodo. As a program committee member and award-winning researcher, Torralba actively contributes to advancing the frontiers of AI planning and decision-making systems.

• Declarative Process Modeling
• Process Mining
• Formal Verification
• +4 more

Paul Cosma is a Postdoctoral Researcher at the Department of Computer Science (DIKU), University of Copenhagen, specializing in the Software, Data, People & Society (SDPS) section. His work focuses on declarative process modeling, formal verification, and explainable AI systems, with strong connections to process mining and Petri net theory. He completed his PhD at the University of Copenhagen's Faculty of Science in 2024 with a thesis on declarative process models as verifiable AI. His research interests center on declarative process modeling and formal verification of complex systems. Cosma develops techniques for improving model simplicity through nested group discovery and creates frameworks like BERMUDA for participatory mapping of domain activities to event data. His work bridges theoretical computer science with practical applications in business process management and AI explainability, emphasizing human-centered design principles where software systems are developed with societal impact in mind. Cosma's publication record shows a clear trajectory in process modeling research, with recent work focusing on transforming Dynamic Condition Response Graphs to Safe Petri Nets (2023) and improving declarative model simplicity (2024). His research demonstrates strong interdisciplinary connections between formal methods, AI verification, and human-computer interaction, particularly in making complex process models accessible and verifiable. Cosma actively collaborates with researchers including Thomas Hildebrandt, Tijs Slaats, and Axel Christfort, primarily within the SDPS section at DIKU. His work receives consistent citations in process mining literature, with his 2023 PETRI NETS paper accumulating 1 citation and his CAiSE 2024 paper gaining 2 Scopus citations. He maintains an ORCID profile (0000-0001-8022-6402) and contributes to open-access research through the university's Pure repository. Based in Sigurdsgade 41, Copenhagen N, Cosma operates within DIKU's collaborative research environment that emphasizes industry partnerships and interdisciplinary work. His recent PhD defense (June 13, 2024) marks his transition from doctoral candidate to postdoctoral researcher, positioning him to expand his contributions to process-aware information systems and verifiable AI.

• Distributed Systems
• Embedded Systems
• Real-Time Systems
• +3 more

Brian Nielsen is an Associate Professor at Aalborg University's Department of Computer Science, under The Technical Faculty of IT and Design. His research focuses on Distributed Systems, Embedded Systems, Real-Time Systems, Model Checking, IoT Networks, and Autonomous Vehicles. He has been actively involved in projects such as domOS (operating system for smart buildings), FED (Flexible Energy Denmark), and compositional verification of multicore avionics systems. His work emphasizes model-based validation, formal methods, and industrial applications, particularly in safety-critical systems. Recent research highlights include energy-efficient motion planning for autonomous vehicles, comparative analysis of network simulators, and sigfox-based IoT modeling. He has received awards including the Application Coordinator Pool and START funds (both in 2007). Key Projects: domOS, FED, compositional verification of multicore systems Grants: Multiple EU-funded projects (e.g., Horizon Europe) and industry collaborations Awards: Application Coordinator Pool (2007), START funds (2007) His publications span over 80 articles, with a focus on real-time systems, IoT interoperability, and model-driven development. He has advised two PhD students and has been actively involved in organizing international conferences and workshops.

Andreas PavlogiannisView profile

Associate Professor

• formal methods
• algorithmic verification
• automata theory
• +6 more

Andreas Pavlogiannis is an Associate Professor in the Department of Computer Science at Aarhus University. His research focuses on formal methods , algorithmic verification , automata theory , concurrency , static and dynamic program analysis , network diffusion , evolutionary graph theory , and evolutionary game theory . Teaching courses: Programming Languages (Bachelor) , Algorithmic Model Checking (Master) , and Program Analysis (Master) Service: Program committee member for POPL, ESOP, AAAI, IJCAI, CONCUR, OOPSLA, and organizer of CONFEST'25 His research has been supported by the Austrian Science Fund (FWF), VILLUM Foundation, Stibo Foundation, and Danish Council for Independent Research (DFF). He is actively recruiting PhD and PostDoc researchers. Recent publications span quantum computing , concurrent systems , evolutionary dynamics , and network science , with particular emphasis on symbolic algorithms , dynamic analysis , and graph-based models .

Anders MøllerView profile

Professor

• Programming Languages
• Software Engineering
• Static Program Analysis
• +4 more

Anders Møller is a Professor and Vice Head of Department at the Department of Computer Science, Aarhus University, Denmark. He is a leading researcher in programming languages and software engineering, with a primary focus on static and dynamic program analysis. He serves as Chairman of the PhD Committee and holds leadership roles in the international research community, including Vice-Chair of ACM SIGPLAN and Associate Editor for ACM TOPLAS and ACM TOSEM. His research interests include programming languages, software engineering, static and dynamic analysis, program verification, and security. His work bridges theoretical foundations and practical applications, particularly in improving software reliability and security through advanced analysis techniques. The trends in his recent publications reflect a strong emphasis on static analysis for security, scalability, and real-world impact—especially in web applications, smart contracts, and open-source software supply chains. His research has evolved toward practical deployment, demonstrated by the founding and acquisition of Coana by Socket in 2025 for enhanced vulnerability detection. Recipient of the Danish Elite Research Prize 2020 ACM Distinguished Member He actively mentors students and contributes to the academic community through conference leadership (e.g., OOPSLA, PLDI, ICSE). He also co-authored the widely used textbook Static Program Analysis with Michael I. Schwartzbach. His work is deeply integrated into both academic and industrial advancements in software analysis and security.

• Programming Languages
• Reversible Computing
• Software Systems
• +2 more

Robert Glück is a Professor at the Department of Computer Science under the Faculty of Science , University of Copenhagen. He also served as a Visiting Professor at the National Institute of Informatics, Tokyo . His research spans programming languages , reversible computing , and metaprogramming , with a focus on energy-efficient computation. Email: glueck@di.ku.dk Phone: +45 29611655 Address: Universitetsparken 5, Building B, 2100 Copenhagen Ø Glück's research interests center on reversible computing , program generation , and metaprogramming , particularly for low-energy systems. His work includes developing reversible logic circuits, invertible interpreters, and tools for program inversion via term rewriting systems. Recent publications highlight advancements in reversible flowchart languages , partial evaluation techniques , and compiler design . Key themes include garbage-free reversibility, memory-efficient algorithms, and formal verification of reversible systems. Scientific Awards: Japan Society for the Promotion of Science (JSPS) Fellowship Grants & Projects: Presto Basic Research Grant (JST) Danish Council for Strategic Research (DSF) project Danish Council for Independent Research (FNU) project Administrative Roles: Current member of the Study Board for Mathematics and Computer Science Former Head of Studies for the Master in Computer Science Professional Activities: IFIP Technical Committee WG 2.11 member (2004–) Steering Committee roles at LOPSTR 2024, FLOPS 2024, HCVS 2024, RC 2024 Editorial Board member for New Generation Computing (2005–)

• Software Testing and Verification
• Reinforcement Learning
• Program Repair
• +5 more

Mahsa Varshosaz is an Associate Professor in Software Engineering at the IT University of Copenhagen, specializing in AI safety, formal verification, and program repair. Her work bridges theoretical research with practical applications in autonomous systems, particularly marine robotics. Current research focuses on model-based testing and formal specification for reinforcement learning systems Active in program repair techniques for concurrency bugs Collaborates with European Commission-funded initiatives in AI safety Recent publications highlight her expertise in autonomous underwater vehicle safety analysis and static program analysis for locking bugs. Her work intersects software engineering, artificial intelligence, and systems validation. Key projects include REMARO (Reliable AI for Marine Robotics) and DIREC (Verifiable and Safe AI), funded by major research foundations. She contributes to open-access datasets and peer-reviewed research through collaborations.

• Software Engineering
• Process Modeling
• Business Process Management
• +5 more

Thomas Troels Hildebrandt is a Professor in the Department of Computer Science at the University of Copenhagen, where he heads the Software, Data, People & Society research section. His work focuses on developing reliable and flexible software systems that adapt to user needs and legislative changes, with applications in digital law, workflows, and business processes. His educational background includes: PhD in Computer Science from Aarhus University (awarded February 23, 2000) Professor Hildebrandt's research spans Software Engineering , Process Modeling , and Business Process Management , with a focus on declarative approaches like Dynamic Condition Response (DCR) graphs. His work integrates formal methods to ensure system reliability in contexts ranging from smart contracts to public governance. He actively explores societal implications of AI, advocating for transparency and user-centered design in digital systems. Recent publications demonstrate a strong trend toward declarative process modeling applied to smart contracts and public governance . Key developments include DCR graphs for dynamic behavior modeling, cross-chain business logic monitoring, and digital compliance frameworks. His interdisciplinary approach bridges computer science with real-world societal challenges, particularly in adapting systems to evolving legislation and user requirements. No specific scientific awards are mentioned in the provided information. Professor Hildebrandt leads interdisciplinary research projects and serves on advisory boards for digitalization and AI. His work has fostered industry collaboration, including founding DCR Solutions based on his research. He acts as an independent consultant and speaker in digital transformation, with recent projects focusing on blockchain integration and public sector AI ethics. He directs the Software, Data, People & Society research section, which develops human-centered methods for adaptable digital systems. Current initiatives include DCR graph applications for GDPR compliance, smart contract security, and transparent AI in public services, with strong industry and government partnerships.

• Machine Learning
• Probabilistic Inference and Reasoning
• Stochastic Processes
• +1 more

Christoffer Olling Back is a Postdoctoral Researcher at the Department of Computer Science (Faculty of Science, University of Copenhagen) specializing in Human-Centred Computing . His work bridges applied and theoretical machine learning, focusing on probabilistic inference, stochastic processes, and computability theory. Education PhD in Computer Science (2017-2020) - University of Copenhagen MSc in Artificial Intelligence (2010-2011) - University of Edinburgh BA in Psychology (w/ Computer Science) (2004-2008) - Lewis and Clark College Current research explores predictive workflow models using location data through the iAware project (collaboration with Systematic, PowerNet, and Bispebjerg Hospital). Previous work investigated ERP system datasets in the DIREC consortium. His publications span topics in process mining, probabilistic modeling, and healthcare informatics. Recent achievements include 15 research outputs (2024-2016) covering process discovery, workflow simulation, and entropy-based log analysis. Collaborations with institutions like Roskilde University and industry partners demonstrate interdisciplinary impact. Scientific Awards Dean's List (2007) Nordea Fonden Scholarship (2010) As an educator, he serves as guest lecturer, assistant teacher, and tutor in computer science, machine learning, and software engineering. His professional background includes industry roles at ServiceNow Denmark ApS (2021-2024) and Gekkobrain (2020-2021).

Danny Bøgsted PoulsenView profile

Associate Professor

• Formal Methods
• Model Checking
• Cyber-Physical Systems
• +3 more

Danny Bøgsted Poulsen is an Associate Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on formal methods, model checking, and cyber-physical systems with applications in security analysis and programming languages. He contributes to projects like BEO-COVID (2020–2020) and IDEA4CPS (2011–2015), which explore decision support tools and foundational cyber-physical systems. His academic background includes advanced work in formal verification and statistical model checking. Key research interests include: Formal methods for string constraints and SMT solvers Statistical analysis of security-critical systems Modelling protocols like DTLS and attack-defense scenarios Applications of formal methods in education and public health Recent work highlights include developing SMTQuery for benchmark analysis, statistical evaluation of bit-flip vulnerabilities, and leveraging large language models for educational feedback. His research outputs span over 36 publications across journals and conferences, with active contributions to UPPAAL tool development and open datasets for reproducibility. Poulsen collaborates internationally on projects involving formal verification of embedded systems and cybersecurity protocols. His work bridges theoretical computer science with practical applications in safety-critical systems.

Frederik ZahleView profile

Researcher

• Wind Turbine Engineering
• Aerodynamics
• Aeroelasticity
• +4 more

Frederik Zahle is a Senior Research Scientist at the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His work focuses on Wind Turbine Engineering , Computational Fluid Dynamics (CFD) , and Aeroelastic Stability Analysis , particularly in airfoil optimization, vortex shedding, and multi-fidelity modeling. He contributes to international collaborations such as the IEA Wind Tasks and leads projects on boundary layer control and large-scale turbine design. Key Research Areas : Aerodynamics, CFD, aeroelasticity, airfoil design. Supervision : He supervises PhD students like Sina Habibzadeh and Felipe Cespedes Moreno. Projects : Involved in initiatives like the Tip and Root Vortex Generators for Boundary Layer Control and the IEA 22-MW Reference Wind Turbine . Zahle's recent articles emphasize high-fidelity CFD , stabilized solvers , and offshore turbine optimization , reflecting trends in computational modeling and system engineering for wind energy. He actively participates in conferences and workshops, advancing aerodynamic design tools and validating complex flow simulations.

Ekkart KindlerView profile

Associate Professor

• Model-Based Software Engineering
• Process Mining
• Petri Nets
• +4 more

Ekkart Kindler is an Associate Professor in the Department of Applied Mathematics and Computer Science at DTU Compute, Technical University of Denmark. His research focuses on model-based software engineering, process mining, and road condition assessment using vehicle sensor data. He leads the Competence Centre for Model-Based Software Engineering, supporting industry adoption of advanced software development methodologies. Education: M.Sc. (1990), Ph.D. (1995) from Technische Universität München; Habilitation in Computer Science (2001) from Humboldt-Universität zu Berlin. He held visiting professorships at German universities (2000–2007) and has extensive experience in formal methods, business process modeling, and Petri nets. Research interests include declarative process modeling, complexity metrics for cognitive load assessment, and the integration of formal methods into industrial software development. His work contributes to UN Sustainable Development Goals related to sustainable infrastructure (SDG 9) and innovation (SDG 9). Notable collaborations include road condition assessment projects using vehicle sensor data (LiRA-CD dataset) and contributions to Petri net standards (PNML). He has supervised PhD students such as K. I. Simonsen (protocol software) and A. Skar (road assessment). Grants and projects: Live Road Assessment with Vehicle Sensors (2019–2022), Model Transformation Tools (2013–2016), and waste management modeling (2012–2016). Active in open-source datasets and tool development for indoor climate control (climify.org).

Christoph SeidlView profile

Associate Professor

• Software Engineering
• Virtual Reality
• Software Visualization
• +5 more

Christoph Seidl is an Associate Professor in the Department of Software Engineering at the IT University of Copenhagen. His research focuses on software visualization, software archaeology, and the application of virtual reality in software engineering tasks. He leads the Immersive Software Archaeology project, exploring collaborative systems and legacy system analysis in virtual environments. Key research areas include software product lines, feature modeling, and model-driven development. Seidl has received awards such as the SoSyM Best Reviewer Award (2018) and SPLC'19 Distinguished Reviewer Award (2019). His work emphasizes innovative tools for software exploration, including immersive 3D visualization and collaborative note-taking systems in VR. He has published extensively on topics like variability management, configuration testing, and domain-specific languages. Research trends in his articles highlight advancements in using VR for software archaeology, collaborative software exploration, and methodologies for managing software evolution. His projects address challenges in legacy system understanding, feature model synthesis, and automated testing for configurable systems. Seidl collaborates internationally, with projects funded by the Independent Research Fund Denmark. His contributions span academic publications, datasets (e.g., VaMoS 2022 artifacts), and tool development for software product line engineering.