Bissan Ghaddar is a Professor in the Department of Technology, Management and Economics at Technical University of Denmark (DTU). Her work focuses on robust optimization, edge computing, and sustainable energy systems, contributing to UN Sustainable Development Goals related to affordable and clean energy. She supervises PhD projects on sector coupling in energy models and quantum computations for power systems. Her research interests include optimizing energy consumption in electric vehicle routing and application placement in edge computing under uncertainty. She has published influential papers in journals like Transportation Research Part C and Omega , addressing latency and efficiency challenges in dynamic systems. Current projects include modeling large-scale sectoral energy systems using smart-linking approaches (2024–2027) and secure power system operation leveraging quantum computations (2021–ongoing). She collaborates internationally with experts in operations research and telecommunications.
Martin Nordal Petersen is an Associate Professor at the Department of Electrical and Photonics Engineering , Technical University of Denmark (DTU) . His work spans Internet of Things (IoT) , optical networking , and wireless communication systems, with notable contributions to LoRa , NB-IoT , and LPWAN technologies. He actively supervises PhD projects on topics such as machine learning in IoT edge devices , secure 5G communication , and smart community architectures . Active projects (2024–2027): Machine Learning in IoT Edge Devices , Deterministic and Secure 5G Communication Finished projects (2021–2024; 2018–2021; 2015–2018): Reliable M2M/IoT Communication , Smart Communities , IoT 100% , Network Slicing His research explores: IoT Reliability : Multi-RAT communication, backup systems, and signal propagation Optical Networks : Alien wavelength integration, SDN control, and network emulation platforms Wireless Innovation : GPS-free geolocation, maritime NB-IoT use cases, and multimode fiber distribution Current collaborations emphasize cross-disciplinary applications of IoT in healthcare , industrial ergonomics , and smart environments .
Matias Thuen Jørgensen is an Associate Professor and head of the Center for Tourism Research at Roskilde University, Denmark, within the Department of Social Sciences and Business. His interdisciplinary research bridges business studies, sociology, and human geography to examine tourism's societal impacts, with empirical focus on Chinese tourism markets and Nordic destinations. He holds a PhD in Tourism Management from The Hong Kong Polytechnic University (2017), awarded through the competitive Hong Kong PhD Fellowship Scheme. His educational foundation combines rigorous academic training with field expertise in tourism phenomena. The PhD research at Hong Kong Polytechnic University established his methodological approach to analyzing tourism distribution systems through Activity Theory and Actor-Network Theory frameworks. Jørgensen's research critically examines tourism's role in sustainable community development, emphasizing how mundane everyday experiences create destination value in Nordic contexts. His work explores social value creation through tourist-resident interactions, regenerative tourism models like CopenPay, and the socio-economic implications of tourism transitions in peri-urban areas. Key themes include the ethical dimensions of tourism development, community mobilization through social entrepreneurship, and the complex interplay between tourism policy and local realities. Analysis of his 15 most recent publications reveals dominant trends in regenerative tourism frameworks, micro-level host-guest interactions, and policy responses to overtourism challenges. His scholarship increasingly focuses on climate-responsive tourism models, ethical pricing mechanisms in aviation, and regulatory approaches to short-term rentals, demonstrating consistent evolution toward solution-oriented sustainability research. Notable recognitions include: Hong Kong PhD Fellowship Scheme (2014) Nomination for Danish National University Teaching Award (2023) Peter Keller Award (2022) Roskilde University Teaching Prize (2022) Teacher of the Year Award, Roskilde University (2022) As principal investigator on seven research projects totaling over 3 million DKK in funding, Jørgensen has secured grants from diverse sources including industry partnerships and public research councils. Current projects include the SeNSE initiative on sustainable nature-based tourism entrepreneurship and the Tourism Business Model Tool development. He actively supervises doctoral research on social value creation in urban tourism encounters while contributing to policy formulation through UNWTO engagements and frequent media commentary. Leading the Center for Tourism Research (CFTR), he fosters cross-disciplinary collaboration between academics, industry stakeholders, and policymakers. His recent activities include organizing the 2025 Academy of Management symposium on tourism transitions and establishing the 'Tourism and Everyday Life in Cities' research network, positioning CFTR at the forefront of contemporary tourism scholarship.
Sneha Das is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), specializing in Speech and Language Technology, Machine Learning, and Privacy-Preserving AI. Her research bridges technical innovation with applications in mental health and physiological signal analysis. Her work focuses on Speech Emotion Recognition , Distributed Speech Processing , and Explainable AI , with recent publications exploring model interpretability, speaker anonymization, and physiological data analysis for emotion detection. She actively supervises PhD students in projects involving AI for mental health and hydroacoustic modeling of fish behavior. Key Research Areas: Speech Emotion Recognition (SER) Privacy and Fairness in Speech Processing Transfer Learning with Physiological Time Series AI Applications in Health and Aquaculture Notable achievements include earning a DSc (Tech) degree for her thesis on robust distributed speech processing. She also contributes to educational activities, including teaching applied statistics and R programming to PhD students.
Anne Elisabeth Haxthausen is an Associate Professor at the Software Systems Engineering section within DTU Compute , Technical University of Denmark . Her work focuses on formal methods, railway control systems, and safety-critical software engineering. Founder and leader of the DTU Railway Verification Group Member of European Technical Working Group on Formal Methods in Railway Control Editorial board member for Springer Formal Aspects of Computing Journal Active in the Overture Language Board Her research emphasizes formal verification of railway interlocking systems, particularly through compositional approaches and automated tools. She has contributed to projects like RobustRailS, Overture, and RAISE, focusing on model-based development and verification. She serves as a tutor for bachelor students and contributes to the advisory committee for DTU's Computer Science and Engineering MSc program. Her recent publications explore challenges in verifying autonomous and AI-driven railway technologies.
Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications
Pernille Bjørn is a Professor in Computer Supported Cooperative Work (CSCW) at the Department of Computer Science , University of Copenhagen (DIKU), where she has been since May 2015. Her research investigates collaborative work practices to design cooperative technologies, focusing on domains like healthcare, global software development, startup companies, and digital fabrication. Faculty of Science, University of Copenhagen Human-Centred Computing Section Research Interests : Bjørn’s work spans CSCW , Human-Computer Interaction , and Digital Fabrication , with applications in healthcare systems, cross-cultural software development, and inclusive technology design. She explores collaborative virtual reality training, FemTech, and crisis computing. ACM Distinguished Member (2024) Publications : Published in top venues like ACM Transactions on Computer-Human Interaction , CSCW , and CHI , her recent work examines hybrid work asymmetry, neurodiverse accessibility, and art-driven collaborative research.
Giulio Cimini is Associate Professor of Theoretical Physics in the Department of Physics at the University of Rome Tor Vergata and a Research Associate at the 'Enrico Fermi' Research Center. He is a statistical physicist with a strong interdisciplinary focus on complex networks and their applications in socio-economic systems. His research interests include: Statistical Physics of Complex Networks Reconstruction and Validation of Economic Networks Social Network Interactions and Financial Markets Systemic Risk and Financial Contagion Scientific Success, Fitness, and Complexity Adaptive Social Recommendation Codon Usage Bias and Protein Interaction Networks His recent publications reveal a strong trend in applying statistical physics to real-world networks, particularly in finance and social systems. Key themes include the modeling of systemic risk in supply chains and financial networks, the dynamics of collective action on platforms like Reddit (e.g., the GameStop short squeeze), and the development of network reconstruction methods using maximum entropy and optimal transport frameworks. His work often combines empirical analysis with theoretical modeling. Scientific awards and recognitions include: Associate Editor, Frontiers in Physics – Interdisciplinary Physics Board Member, Network Science Society Member, Council of the Complex Systems Society Steering Committee, CCS/Italy He has advised or collaborated with numerous researchers, particularly in projects related to economic networks and complex systems. His work has been supported by Italian national grants such as PRIN and PNRR. He leads or co-leads research projects including RENet and C2T. His research is conducted within interdisciplinary teams involving physicists, economists, and computer scientists, often in collaboration with institutions like ISC-CNR, IMT Lucca, and the Network Science community.
Susanne Ditlevsen is a Professor at the Department of Mathematical Sciences , University of Copenhagen. Her research focuses on statistical inference for stochastic processes , mathematical modeling of physiological systems , nonlinear dynamics , neuroscience , and biomathematics . Research : She develops statistical methods for diffusion processes, hidden Markov models, and stochastic differential equations, with applications in biomedical data and marine mammal behavior. Teaching : Covers basic statistics, probability, stochastic processes, regression, and generalized linear models. Publications highlight her work on climate tipping points (2023, Nature Communications ), nonlinear neuronal systems (2017), and statistical ecology (2020). Her collaborations span Denmark, France, and international institutions.
Giovanni Pantuso is an Associate Professor at the Department of Mathematical Sciences, University of Copenhagen, specializing in stochastic programming and optimization under uncertainty . His work bridges mathematical methods with practical applications in transportation, logistics, and production planning. Education : PhD in Operations Analysis from the Norwegian University of Science and Technology (Feb 2014) Research Focus : Developing mathematical frameworks for decision-making under risk, with applications to maritime fleet renewal, car-sharing systems, and ride-sharing logistics. Teaching : Courses in Advanced Operations Research: Stochastic Programming, Risk Optimization, and Introduction to Numerical Analysis. His methodological contributions include novel algorithms for stochastic programming and decomposition methods, while applied work spans electric car-sharing systems, first-mile transportation challenges, and production planning under uncertainty. Current research explores dynamic fleet management and cost-service tradeoffs in shared mobility.
Alfred Taudes is a Full Professor at the Department of Information Systems and Operations, Institute for Production Management, Vienna University of Economics and Business (WU Vienna). He holds a doctoral degree and a Habilitation from WU Vienna in Business Administration and Management Information Systems, and a Magister degree from Vienna University. He has held assistant professorships at WU and visiting professorships at Augsburg, Münster, Essen, and Tsukuba University, Japan. He joined WU permanently in 1993 and served as head of the Department of Information Systems and Operations from 2010 to 2016. His research spans Operations and Supply Chain Management , Marketing Engineering , Knowledge Management , and the impact of Big Data and Blockchain on production systems. Using Complexity Science and Cryptoeconomics , he investigates digital production, integrated value chains, and market designs. He teaches undergraduate and graduate courses including Operations Strategy, Data Science, and IT seminars in WU’s International Supply Chain Master program, and has also taught at Japanese universities. His recent publications focus on blockchain privacy (e.g., CoinJoin analysis), CBDCs, MiCAR regulation, decentralized federated learning, and digital custody, reflecting a strong trend toward cryptoeconomics and blockchain-based systems in operations and finance. These works appear in top journals and conferences in information systems, security, and operations research. Cooperation Officer of the Year 2013/14 Distinguished Paper Award WI 2009 VHB Best Paper Award Nomination VHB Best Paper Award Dr. Wolfgang Houska - Recognition Award Alfred Taudes has coordinated major research projects such as the WWTF-project “Integrated Demand and Supply Chain Management” and the Special Research Area Adaptive Models in Economics and Management Science. He currently leads the research group on Cryptoeconomics at WU and chairs the scientific board of the Austrian Internet Offensive . His leadership extends to project management in initiatives like the Austrian Blockchain Center and research on decentralized finance and digital assets. He is actively involved in academic service, including organizing conferences like DEXA 2022, serving on editorial boards, and advising on research policy. His lab and research group focus on blockchain applications, digital transformation in operations, and the societal implications of big data.
Shuang Ma Andersen is a Full Professor at the Department of Green Technology (IGT) and SDU Chemical Engineering, specializing in electrocatalysis, fuel cell technologies, and sustainable resource recovery. Her research focuses on oxygen evolution reaction (OER) catalysts, membrane electrode assemblies, and innovative synthesis methods for iridium/platinum-based systems.
Kristian Sevdari is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Technical University of Denmark (DTU). He was born in Kucove, Albania, in 1995, and holds a B.Sc in electrical engineering from the Polytechnic University of Tirana (2016), an M.Sc from UiT Norges arktiske universitet, Norway (2020), and a Ph.D. from DTU (February 2024). Since 2020, he has been working at DTU on multiple projects including Solar-Move, AHEAD, FLOW, EV4EU, ACDC, and FUSE. His research focuses on renewable energy integration and electric vehicle grid integration, with specific expertise in vehicle-to-grid systems, power system dynamics and stability, prosumers and flexible demand, wind power integration, and smart grid technologies. His work contributes to UN Sustainable Development Goals related to sustainable energy and climate action. Dr. Sevdari's recent publications demonstrate a strong trend toward solving practical challenges in EV-grid integration, with emphasis on bidirectional charging technologies, harmonics analysis, battery second-life applications, and smart charging strategies for residential and urban environments. His research bridges theoretical control approaches with experimental validation across multiple European contexts. Best paper award at 2024 IEEE Transportation Electrification Conference & Expo Best paper award of the IEEE PES ISGT-Europe 2021 conference As a supervisor, he has guided multiple Master's theses on topics including telematics integration for EV cost reduction, open charge point protocol implementation, vehicle-to-grid testing, and compatibility testing for EV ecosystems. He is actively involved in the IEEE PES Task Force on electric vehicle grid integration and IEA Task 53, and is the founder of IEEE REST conferences, Qendra SUSALB, and EkoVolt.
Jan Engelhardt serves as Assistant Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specializing in e-mobility and prosumer integration within power and energy systems. His work directly contributes to UN Sustainable Development Goals through grid modernization and renewable energy integration. His research focuses on electric vehicle-grid integration , with core expertise in battery energy storage systems, DC microgrids, and virtual power plants. Key investigation areas include smart charging architectures for EV clusters, frequency response services, phase balancing techniques, and V2X management strategies. His experimental approach combines theoretical modeling with real-world validation of control systems for enhanced grid stability. Recent publications demonstrate a clear trend toward distributed control solutions for electric vehicle clusters, emphasizing user-centric scheduling while providing grid services. His work increasingly incorporates experimental validation of frequency control architectures and explores high-power reconfigurable battery applications for fast-charging infrastructure. Dr. Engelhardt actively supervises PhD candidates on projects including Hybrid Energy Solutions (EV charging and battery storage synergies) and Provision of Grid Services through EV Aggregation. He participates in major EU initiatives like EV4EU (Electric Vehicles Management for Carbon Neutrality in Europe) and GREAT (GRid Enhancement for Ancillaries in Tomorrow’s power systems), securing substantial research funding through Horizon Europe frameworks.
Bo Markussen is a Professor at the University of Copenhagen within the Department of Mathematical Sciences . He is also a member of the Data Science Laboratory , where he contributes to statistical methodology and interdisciplinary collaborations. His academic journey began with a Cand.Scient (MSc) and PhD in Statistics from the University of Copenhagen, awarded in 1998 and 2002 respectively. 2012–present: Professor, Department of Mathematical Sciences, University of Copenhagen 2009–2012: Associate Professor, Department of Basic Sciences and Environment, University of Copenhagen 2006–2009: Assistant Professor, Department of Basic Sciences and Environment, University of Copenhagen Bo Markussen's research focuses on applied statistics , particularly in functional data analysis and multiple testing corrections in genetics . His work spans diverse domains including environmental science, agriculture, and public health. Recent research output highlights applications in Arctic climate data analysis, fire risk modeling, plant stress phenotyping, and nutritional biomarker prediction. His recent publications demonstrate a strong trend toward machine learning integration with statistical modeling , addressing challenges in high-dimensional data analysis and environmental risk assessment. Collaborations span institutions in Denmark and internationally, reflecting his engagement in pan-Arctic climate studies and tropical agricultural research. 2018–present: Associate Editor, Scandinavian Journal of Statistics 2017–2019: Chair, Danish Society for Theoretical Statistics 2015–2017: Board Member, Danish Society for Theoretical Statistics As a central figure in the Data Science Laboratory , Markussen leads statistical consultancy initiatives and contributes to methodological advancements. His expertise bridges theoretical statistics with real-world applications, particularly in handling complex datasets across biological and environmental domains.
