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 .
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.
Sithik Aliyar is a Postdoctoral Researcher at the Department of Wind and Energy Systems, Flows Wind Turbine Design Division, at the Technical University of Denmark (DTU). He specializes in computational fluid dynamics (CFD) and offshore wind turbine dynamics, focusing on wave interactions with floating structures. Institution: Technical University of Denmark (DTU) Department: Flows Wind Turbine Design Division, Wind and Energy Systems Research Focus: Floating wind turbines, extreme sea states, harmonic separation, and numerical algorithms His work combines advanced CFD simulations with experimental validation to analyze floating wind turbine stability under directional waves. Recent contributions include the FloatStepper algorithm for robust wave response modeling and studies on SPAR platform upending risks. Publications highlight collaborations with experts like H. Bredmose and J. Roenby, with research outputs spanning Renewable Energy , Royal Society Open Science , and international conferences on ocean engineering. Key metrics include open-access citations, computational fluid dynamics, and floating wind turbine dynamics.
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.
Elena Irene Zavala serves as an Assistant Professor in the Section of Forensic Genetics and Guest Researcher at the Globe Institute, Section for Geogenetics at the University of Copenhagen's Faculty of Health and Medical Sciences. Her work bridges forensic science with paleogenetic research, focusing on ancient human DNA analysis and population genetics. Dr. Zavala's research interests span ancient DNA analysis, paleogenetics, forensic genetics, human evolution, population genetics, archaeogenetics, and anthropological genetics. Her work demonstrates a consistent focus on understanding human evolutionary history through genetic analysis, with particular emphasis on migration patterns, adaptation to diverse environments, and the development of methodological approaches for analyzing degraded DNA samples. She has made significant contributions to understanding Neanderthal admixture timing and early human dispersal into Europe. Her publication record shows a strong trend toward high-impact interdisciplinary research, with numerous publications in Nature and other top-tier journals. Her work frequently involves international collaborations across multiple institutions, reflecting the global nature of paleogenetic research. A notable pattern in her recent publications is the integration of multiple analytical approaches (genomic, isotopic, archaeological) to reconstruct human history. Young Investigator Award (2019) Miller Postdoctoral Fellowship (2022) Peter M. Schneider ISFG Fellowship (2023) Novo Nordisk Hallas-Møller Emerging Investigator Grant (2024) Dr. Zavala has secured significant research funding including the prestigious Novo Nordisk Hallas-Møller Emerging Investigator Grant in 2024, indicating strong institutional support for her research program. Her work has garnered substantial attention with multiple publications being picked up by hundreds of news outlets and referenced across social media platforms and academic networks. As a Guest Researcher at the Globe Institute's Section for Geogenetics, Dr. Zavala collaborates with interdisciplinary teams focused on ancient DNA and human evolutionary history. Her research often involves large international collaborations, as evidenced by the extensive author lists on her publications, suggesting she works within substantial research networks dedicated to paleogenetic investigations.
Ole Winther is a Professor at the Department of Biology, University of Copenhagen, specializing in Computational and RNA Biology. He also holds a joint appointment as Professor at DTU Compute, Technical University of Denmark. His research bridges machine learning, bioinformatics, and natural language processing with applications in biological sequence analysis, transcriptomics, and health informatics. Education: 1998: PhD in Physics, University of Copenhagen 1994: Master of Science in Physics, University of Copenhagen Winther's research focuses on developing advanced machine learning methodologies for biological applications. He has pioneered protein language models for sequence analysis (DeepLoc, SignalP, DeepTMHMM), interpretable deep learning for RNA subcellular localization, and benchmarking frameworks for DNA language models. His work spans latent variable models, variational inference, diffusion models, and novel architectures for deep generative modeling, with increasing emphasis on practical healthcare applications including rare disease diagnosis through findzebra.com and medical question answering with large language models. Scientific Recognition: ELLIS Fellow (2021) Head of ELLIS Copenhagen Unit H-index of 61 (Google Scholar, May 2023) 19,700+ citations (Google Scholar, May 2023) Winther has supervised 25+ PhD students to completion with 7 currently in progress, along with over 100 master's projects. He frequently serves as PhD opponent and committee chairman across European institutions. His research is supported by substantial funding including multiple Novo Nordisk Foundation grants totaling over 60 million DKK for the Center for Basic Machine Learning Research in Life Science and CAZAI projects, plus significant funding from the Danish Independent Research Fund. He leads an active research group developing cutting-edge machine learning approaches for bioinformatics and NLP challenges. Winther co-founded two spin-out companies: findzebra.com (2014, 2018), a search engine for rare diseases, and raffle.ai, an NLP startup for enterprise search. He initiated DTU's popular BSc in AI and Data program and teaches the highly enrolled MSc course in Deep Learning (450+ students) and PhD course in Bayesian Data Analysis.
Fabio Pierella is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Wind and Energy Systems Flows, specializing in Wind Turbine Design Division. His research focuses on offshore wind energy systems, fluid dynamics, and structural engineering. He has contributed to projects like OC6 Phase IV and the DeRisk database, validating numerical models for floating offshore wind structures and extreme wave loads. Key research interests include computational fluid dynamics (CFD), hydrodynamic load modeling, and the design of large-scale floating wind turbines. His work spans numerical simulations, experimental validation, and database development for extreme sea states. Pierella has presented at international conferences on topics like wave-structure interaction and turbine control systems. He received the Best Poster Presentation Award (2024) and contributed to datasets such as the DeRisk Database, which provides critical wave data for offshore wind turbine design. His research emphasizes practical applications, including monopile structural integrity under extreme loads and control strategies for floating platforms. Pierella's activities include conference presentations on ultra-large floating turbines (EMULF2 project) and the impact of wave shape on 15MW turbine loads. His interdisciplinary approach integrates computational models with experimental results to address challenges in offshore renewable energy systems.
Elham Ramin is a Researcher at the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), affiliated with the Center for Energy Resources Engineering (CERE) and the Process and Systems Engineering Centre (PROSYS). Her work contributes to multiple UN Sustainable Development Goals, particularly in clean water and sanitation, affordable and clean energy, and industry innovation. Dr. Ramin completed her PhD at DTU (2010-2014) with research focused on modeling water quality in sewer-WWTP systems. Her academic journey demonstrates a strong foundation in environmental process engineering with applications to real-world water treatment challenges. Her research interests span wastewater treatment optimization, Power-to-X applications for water resource recovery, industrial symbiosis in water management, and biomanufacturing process modeling. She specializes in computational fluid dynamics, activated sludge modeling, and one-dimensional simulation models for wastewater treatment plants. Her work bridges environmental engineering with sustainable resource management, focusing on practical solutions for water-energy nexus challenges. Analysis of her recent publications reveals a strong trend toward integrating sustainable energy solutions with water treatment processes, particularly Power-to-X technologies. Her research portfolio shows increasing focus on digitalization of water resource recovery facilities and cross-sectoral industrial symbiosis for optimal resource utilization. The work demonstrates strong interdisciplinary connections between environmental engineering, chemical process modeling, and sustainable development. Dr. Ramin has participated in significant research projects including ERASE (Evaluation of Resource recovery Alternatives in South African water) and GECKO (Green and Circular Innovation for Kenyan Companies), demonstrating international collaboration and application of research to diverse water management contexts. Her work has generated substantial academic interest with multiple publications receiving significant downloads and reader engagement on platforms like Mendeley. She is actively involved with research centers including CERE and PROSYS at DTU, contributing to interdisciplinary teams focused on energy resource engineering and process systems optimization. Her collaborations extend to pharmaceutical industry applications, particularly in vaccine manufacturing development and digital twin implementation for bioprocesses.
Anders Kalsgaard Møller is an Associate Professor in the Department of Culture and Learning at Aalborg University's Faculty of Humanities and Social Sciences. He is actively engaged in research and innovation in learning design, digital technologies, and artificial intelligence in education. His work is centered around the L-ILD (IT and Learning Design), Green Society, and MASSHINE Xlab – Design, Learning and Innovation research environments. His research interests span Learning Design , Computational Thinking , Artificial Intelligence in Education , Human-Robot Interaction , and Environmental Literacy . He investigates how emerging technologies can be integrated into educational practices to enhance collaborative learning, literacy development, and sustainable thinking. His work often involves participatory and co-design methods with educators and children. The recent publications of Anders Kalsgaard Møller reflect a strong trend toward the application of generative AI, robotics, and digital tools in language and primary education. His scholarly output emphasizes interdisciplinary collaboration, technological innovation, and real-world educational impact, particularly in K-12 and higher education contexts. Principal Investigator, 'Using artificial intelligence in English teaching at upper secondary schools' (2023–2026) Co-PI, 'Co-Designing Robot-Assisted Learning for Children' (ongoing) Co-PI, 'Labor market-oriented AI skills at cand.it.' (2024–2026) Co-PI, 'Understanding and fostering future consumers' environmental literacy' (2024–2025) Anders Kalsgaard Møller has been involved in media outreach, including coverage on children's interactions with social robots and discussions on AI in education. He has also contributed to academic leadership through conference organization and editorial roles, such as in the DLI conference series. He is affiliated with key research labs including: L-ILD – IT and Learning Design Green Society MASSHINE Xlab – Design, Learning and Innovation These labs focus on digital innovation, sustainability, and human-centered design in educational contexts.
Rob Gleasure is a Professor in the Department of Digitalization at Copenhagen Business School (CBS), Denmark. His research focuses on the intersection of information systems, digital technologies, and human behavior, with particular expertise in blockchain technology, crowdfunding, AI applications, and technology adaptation. Based at Solbjerg Square 3 in Frederiksberg, he contributes to CBS's mission of advancing knowledge in business and society through digital transformation. Professor Gleasure's research spans several key areas within information systems and digital innovation: Digital finance and blockchain technologies, including cryptocurrency and financial applications Crowdfunding platforms and digital fundraising mechanisms Artificial intelligence applications in various domains including healthcare and banking Human-computer interaction and the psychological aspects of technology adoption Digital collaboration and the affective dimensions of online work Quantum computing infrastructure and emerging technologies His recent publications reveal an evolving research trajectory that increasingly addresses the societal implications of digital technologies. Gleasure has moved from foundational work on crowdfunding and blockchain to more complex examinations of AI ethics, gender bias in technological systems, and the psychological impacts of digital media. His research demonstrates growing attention to sustainable development goals, particularly those related to responsible consumption and production, reduced inequalities, and climate action. The interdisciplinary nature of his work bridges business, technology, and social sciences, often employing both qualitative and experimental methodologies. Professor Gleasure has served as a supervisor for numerous students (21 supervisor tasks mentioned) and has been active in academic service including co-chairing the ACM Collective Intelligence Conference in 2021. His research has attracted media attention, with contributions to discussions on cryptocurrency, carbon offsetting in aviation, and AI applications.
Jes Frellsen is an Associate Professor at the Department of Applied Mathematics and Computer Science (DTU) since 2016. Previously, he held academic positions at the IT University of Copenhagen (2016-2019), postdoctoral roles at University of Cambridge (2013-2016) and University of Copenhagen (2011-2013). Education: PhD in Bioinformatics (2011), University of Copenhagen MSc in Bioinformatics (2007), University of Copenhagen BSc in Mathematics and Computer Science (2005), University of Copenhagen EAP Exchange at University of California, Santa Cruz (2004-2005) Research Focus Jes Frellsen specializes in statistical machine learning , particularly generative AI and deep generative models with applications in bioinformatics . His work integrates Bayesian inference , directional statistics , and Markov chain Monte Carlo methods to address challenges in macromolecular structure prediction and missing data imputation . Recent efforts explore uncertainty quantification in image segmentation and generative modeling for materials science. Advising & Collaborations He actively supervises PhD students and postdoctoral researchers in projects spanning news recommendation systems , medical imaging , and 3D structure generation . Collaborations include work with Zoubin Ghahramani (Cambridge) and Thomas Hamelryck (Copenhagen), with contributions to protein structure prediction and statistical methods in structural bioinformatics .
Jens Honore Walther is a Professor in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU). His research focuses on fluid mechanics, coastal and maritime engineering, and computational fluid dynamics (CFD). He leads projects on wave energy converters, multiphase flow systems, and thermal energy applications. His work contributes to sustainable development goals related to clean energy and climate action. External Roles: Research associate at ETH Zurich (2003–present) Postdoctoral fellow at ETH Zurich (2000–2003) Project manager at Danish Maritime Institute (1996–1997) Research scientist at Danish Meteorological Institute (1994–1996) Research Interests: Walther’s expertise spans CFD modeling, granular flow dynamics, and nanofluidics. His recent projects include optimizing wave energy converters, analyzing gap resonances in marine structures, and developing multiphase ejector geometries for heat pumps. His work integrates high-performance computing and experimental validation to address challenges in marine engineering and energy systems. Advising & Projects: He supervises PhD students in areas such as elite sport aerodynamics, gas lubrication, and alternative fuel combustion. Notable projects include: Elite sport aerodynamics (2024–2026) Alternative fuel injection in marine engines (2023–2026) Multi-physical gas bearing modeling (2024–2027) Labs & Collaborations: Walther collaborates with institutions like ETH Zurich and engages in experimental facilities at DTU. His group focuses on advanced CFD simulations and fluid-structure interaction studies.
