Konstantinos Kalogeropoulos is an Assistant Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), leading research at the Cell Diversity Lab. His work bridges proteomics, computational biology, and snake venom research. Current projects: "The Proteomic Landscape during Influenza Infection" (2022-2025) Supervisor for PhD projects on protease network rewiring in psoriasis and wound exudate degradomics Research interests include: Proteomic analysis of inflammatory diseases Snake venom toxin structure prediction Extracellular matrix biomechanics De novo peptide sequencing algorithms Computational modeling of protease networks Recent article trends demonstrate his work in • Database-free proteomics (InstaNovo/InstaNexus) • Snake venom pathophysiology (V-ToCs clustering) • Inflammatory disease biomarkers (psoriasis, impaired healing) • Extracellular matrix mechanics (fibronectin tension, gut inflammation) Advising: Supervises PhD students Polhaus, C. J. M. and Haack, A. M., focusing on protease networks and wound healing.
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.
Luis Emilio Bruni is an Associate Professor at Aalborg University’s Department of Architecture, Design and Media Technology, within The Technical Faculty of IT and Design. He leads the Media Cognition and Interactive Systems (MeCIS) research group and coordinates the Master of Science in Medialogy. Bruni is also the founder and director of the Augmented Cognition Lab, focusing on perception, cognition, and immersive technologies. His academic roles include PI on multiple interdisciplinary projects and board memberships in international associations like the Nordic Association for Semiotic Studies (2011–2017) and the International Society for Biosemiotic Studies (founding member, 2005). Academically, Bruni holds a Ph.D. in Molecular Biology and Theory of Science (University of Copenhagen), M.Sc. in International and Global Relations (Universidad Central de Venezuela), and B.Sc. in Environmental Engineering (Pennsylvania State University). His research spans narrative cognition, extended reality, biosemiotics, and the interplay between technology, cognition, and culture. He has conducted projects on neurocinematic analysis, interactive storytelling, and the psychological impact of digital media. Key research contributions include studies on EEG responses to branded advertising, functional connectivity in psychiatric disorders, and the role of narrative in immersive technologies. Bruni’s work bridges cognitive science, computer science, and semiotics, with applications in healthcare (e.g., pediatric counseling tools) and cultural engagement (e.g., citizen curation systems). Over 80+ publications and active participation in conferences and media discussions highlight his interdisciplinary impact.
Jacob Gorm Davidsen is an Associate Professor at Aalborg University's Department of Communication and Psychology, affiliated with The Faculty of Social Sciences and Humanities. He leads the Collaboratory for Human-Centered Immersive Problem-Solving Spaces (CHIPS) and co-founded initiatives like VILA and AVA360VR. His research focuses on leveraging digital technologies, particularly Virtual Reality (VR), to enhance learning, collaboration, and problem-solving in immersive environments. He holds a PhD in Human Centered Communication and Informatics. Key projects include 'En bedre start' (funded by Independent Research Fund Denmark) exploring VR for teacher training and the 360mash project addressing GPU cloud and software anonymization. His work bridges computer science, education, and human-centered design. Main research interests include immersive VR applications, collaborative learning environments, and digital infrastructure for social sciences. His contributions span 105+ publications, with recent emphasis on activity-based VR frameworks and near-future educational technologies. He serves on editorial boards (e.g., European Journal of Engineering Education) and actively reviews manuscripts. Notable software tools developed include DOTE and AVA360VR for qualitative analysis and video collaboration.
Søren Eilers is a Professor at the Department of Mathematical Sciences , University of Copenhagen. His research focuses on Operator Algebras , particularly the classification of C*-algebras related to discrete and low-dimensional structures. He is a member of the FNU network 'Automorphisms and Invariants for Operator Algebras' and advocates for experimental mathematics using computational methods in pure mathematics. Education: MS in Mathematics and Computer Science, University of Copenhagen (1993) PhD in Mathematics, University of Copenhagen (1995) Research Interests: Operator Algebras K-theory Symbolic Dynamics Discrete Mathematics Experimental Mathematics Recent Publications (2016-2024) demonstrate expertise in graph C*-algebras , symbolic dynamics , and computational approaches to pure mathematics, with key collaborations in Denmark, Japan, Canada, and the U.S. Scientific Leadership: President, Danish Mathematical Society (2006-2008) Principal Investigator, Villum Fonden (2012-2016) Main Organizer, Mittag-Leffler Institute Program (2016) Advisory Roles: Supervised 28 master's theses and mentored 9 PhD students/postdocs (2003-2022) across institutions in Denmark, Canada, Japan, and the U.S.
Emilia Mendes is a Full Professor in the Department of Electrical and Computer Engineering at Aarhus University . Her research focuses on Empirical Software Engineering , particularly human-centric approaches, evidence-based decision-making, and the application of machine learning and statistical techniques in software development. Current research themes: Human-Centric Software Engineering, Evidence-Based Research, Statistical/Machine-Learning Techniques, and Value-Based Software Engineering. Developed tools for team climate forecasting, capability measurement, and value-based decision-making. Research Trends: Her work bridges software engineering with psychology (personality traits, team dynamics), machine learning (effort estimation, dementia prognosis), and value-based frameworks for decision-making. She emphasizes industrial applications, including agile methodologies, cross-company predictions, and Bayesian network modeling. Scientific Impact & Awards: 10,018 citations, h-index 58. Ranked #32 in Empirical Software Engineering Scholars (Google Scholar). Ranked #20 in Top Computer Science Scientists in Sweden (2023). Top 2% scientist in the world (2019, 2020, 2022; only female in Sweden for SE in 2022. Nine best paper awards at international conferences. Editorial board member: Information and Software Technology , ACM Computing Surveys , former roles at IEEE Transactions on Software Engineering and others. Grants & Leadership: Awarded €11.921.603 in research grants. Held leadership roles as General Chair (EASE 2017), PC Co-Chair (EASE 2012, ESEM 2012), and active participant in 200+ academic events.
Martin Aumüller is a Lecturer in Theoretical Computer Science Algorithms at the IT University of Copenhagen . He serves as Head of Education and Master of Software Design , focusing on algorithm engineering, differential privacy, and similarity search. Research interests include: Algorithm engineering for high-dimensional data Locality-sensitive hashing and nearest neighbor search Privacy-preserving machine learning Fairness in approximate search algorithms Benchmarking and evaluation of similarity search tools Publications trends highlight his work on approximate nearest neighbor search , privacy-preserving techniques , clustering algorithms , and scalable outlier detection in high-dimensional spaces. His recent projects (2024-2025) focus on fairness, differential privacy, and efficient indexing. Grants and projects : DIREC (2020-2025): Digital Research Centre Denmark (Innovation Fund Denmark) DIREC: Bias and Benefit of Approximate Nearest Neighbor Search (2022-2025): Principal Investigator (Innovation Fund Denmark) BARC (2017-2024): Basic Algorithms Research Copenhagen (Villum Fonden) SSS (2014-2019): Scalable Similarity Search (European Commission)
Anders Haug serves as Associate Professor at the Department of Business and Sustainability (DBS) within the University of Southern Denmark's Kolding campus. Having joined the university in 2008 as Assistant Professor in the Department of Entrepreneurship and Relationship Management before transitioning to his current role in 2010, his academic career spans over 15 years of research and teaching in operations, supply chain, and digital transformation contexts. His work bridges theoretical rigor with practical industry applications, particularly in engineer-to-order manufacturing and logistics sectors. Education: PhD in communication, representation and automation of design knowledge (2005-2007) Haug's research centers on information and knowledge management systems, with deep expertise in data quality frameworks, knowledge-based configuration, and digitalization of business processes. His fingerprint reveals distinctive contributions to product configuration systems, digital twin applications, and supply chain resilience—particularly examining how configurators transform warehouse services, manufacturing processes, and product-service ecosystems. Recent work increasingly addresses sustainability through green dynamic capabilities frameworks and life cycle assessment tools, maintaining strong empirical grounding via case studies in Danish manufacturing. Analysis of his 2024-2025 publications shows converging trends: digital technologies (configurators, digital twins) are examined through operational performance lenses while addressing sustainability imperatives. These works span operations management, information systems, and strategic management disciplines but consistently prioritize practical implementation frameworks for manufacturing SMEs. The research demonstrates methodological diversity—from conceptual modeling to empirical case studies—with strong industry relevance in logistics, engineering-to-order contexts, and manufacturing digitization. Scientific Awards: Top read paper in Business 2017/18 (Wiley) (2019) Haug has supervised 34 teaching courses between 2018-2024 covering business information systems, digitalization projects, and supply chain management. His academic service includes extensive peer reviewing for conferences like NOFOMA and DRS, plus organizational roles in Nordic business research networks. While specific grant details aren't provided, his 175+ research outputs and industry collaborations (evidenced by consultant work since 2006) indicate substantial research funding engagement. Media contributions on 3D printing and business process efficiency demonstrate effective knowledge transfer to practitioners. Though no dedicated research lab is specified, Haug's extensive co-authorship network—including collaborations on projects like digital twin implementation and configurator development—reveals embeddedness in multiple research collectives. His industry-facing approach manifests through case studies with logistics providers, manufacturer partnerships, and practical frameworks for warehouse service design and supply chain resilience.
Arijit Khan is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark. He leads the Data Engineering, Science and Systems group and is affiliated with the Technical Faculty of IT and Design. His research focuses on Graph Neural Networks , Blockchain , Data Management , and AI interpretability . He is the Principal Investigator (PI) of a major project on Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks (2022–2027). Research Interests : Graph Data Management & Machine Learning Blockchain Transaction Analysis Large Language Model + Knowledge Graph Synergies Healthcare AI (e.g., ICU glucose prediction) Explainable AI for Graph Neural Networks Research Trends : His publications emphasize neuro-symbolic systems , uncertain graph analysis , and AI-driven blockchain insights . Recent work bridges large language models with knowledge graphs and explores GPU performance optimization via shader code analysis. Awards & Grants : No explicit awards listed, but his active research grants include a 5-year project on large network analysis with interdisciplinary applications in life and health sciences. Funding emphasizes algorithmic innovation and data science integration. Labs/Teams : Head of the Data Engineering, Science and Systems research group, focusing on AI for societal impact ('AI for the People') and scalable graph data systems. Collaborations span blockchain analytics, healthcare informatics, and GPU architecture design.
Claus Brabrand is a Professor of Software Engineering and Head of the Center for Computing Education Research at the IT University of Copenhagen. His research focuses on computing education, gender diversity in STEM, and software product line analysis. He has led projects like DIREC (Digital Research Centre Denmark) and ATTiKA (Adaptive Tools for Technical Knowledge Acquisition), funded by the Innovation Fund Denmark and Villum Foundation. PhD in Computer Science Over 45 publications in computing education and software engineering Active in curriculum development and educational policy Research interests include improving teaching quality through learning technologies, gender representation in IT materials, and cognitive competencies in programming education. His work bridges software engineering principles with pedagogical innovations, addressing issues like novice programmer performance and curriculum design.
Ole Madsen is a Professor at the Department of Materials and Production within The Faculty of Engineering and Science at Aalborg University . His research focuses on Robotics and Automation , particularly in 5G Smart Production , AI for Manufacturing , and Industry 4.0 applications. He also holds a part-time position at Adding Robotics , applying his expertise in robot integration for industrial and healthcare settings. Research Interests : Robotics, Automation, AI, Sensor Systems, Modular Manufacturing, Welding Technology, Digital Twins, Human-Centered Robotics, Industry 4.0 His work spans 35+ years with over 205 publications , emphasizing smart production systems and robot-assisted processes . Key contributions include Swarm Production Architectures , 5G-Enabled Robotics , and Human-Robot Collaboration frameworks. He has supervised 10 PhD students and led major projects like RAU (Robot-Assisted Ultrasound) and GINP: Robotics & AI Innovation Network . Scientific Awards : SCAP2020 Best Presentation Award (2020) Ole's 31 projects include AP2030: Aseptic Factory 2030 (pharma production), AddSmart (robotics R&D), and 5G-Enabled Autonomous Systems . His 127 press/media mentions highlight advancements in robotic welding , industrial metaverse , and swarm production . He maintains an ORCID: 0000-0003-2133-2541 with extensive publication records across Swarm Robotics , Modular Manufacturing , and AI-Driven Production .
Peter C. Petersen is an Associate Professor in the Department of Neuroscience within the Faculty of Health and Medical Sciences at the University of Copenhagen. Holding a Civilingeniør (MSc) in Technical Physics from DTU and a PhD in Neuroscience, he specializes in systems-level neural mechanisms using electrophysiological approaches. His educational background includes: Civilingeniør (MSc) in Technical Physics, DTU PhD in Neuroscience Petersen's research focuses on neural dynamics in memory and motor systems, combining in vivo electrophysiology with computational modeling. He investigates hippocampal place cells for spatial working memory and rotational dynamics in spinal cord networks, while developing neurotechnology tools like CellExplorer for single-neuron analysis. His work bridges experimental neuroscience, engineering, and data science to decode circuit-level computations. Recent publications (2020-2024) reveal a dual emphasis on hippocampal memory mechanisms (e.g., temperature effects on sharp wave ripples) and innovative methodology (e.g., 3D-printed microdrives). This trajectory demonstrates consistent advancement from tool development to fundamental discoveries in neural coding, with increasing collaboration intensity as evidenced by multi-institutional authorship. Scientific awards: No specific awards were documented in the source material. While explicit advising details are absent, his leadership in software/hardware development (CellExplorer, microdrive systems) implies active mentorship of technical researchers. Grant information isn't specified, though high-impact publications suggest sustained funding for neurotechnology and systems neuroscience projects. Petersen directs the Petersen Lab (https://petersenlab.org/), which employs chronic electrophysiology in rodent models to study memory and movement. The lab maintains strong ties with the Buzsáki lab (hippocampal research) and continues collaborations initiated during his NYU Langone Health tenure (2016-2022), reflecting an integrated approach to neural circuit analysis across institutions.
Frederik Marinus Trudslev is a PhD Fellow at the Department of Computer Science, The Technical Faculty of IT and Design, Aalborg University, Denmark, focusing on critical challenges at the intersection of data privacy and bioinformatics. His research bridges computer science and computational biology through innovative work in synthetic data generation and genomic analysis. Trudslev's primary research domains include privacy-preserving synthetic data, where he develops rigorous metrics and evaluation frameworks to balance data utility with individual privacy protection. In bioinformatics, he pioneers ensemble methods for metagenomic binning, significantly improving microbial genome reconstruction from complex environmental samples through advanced clustering techniques. His 2023-2025 publications reveal a strategic pivot toward privacy-enhancing technologies, evolving from metagenomic binning (BinChill, 2023) to comprehensive privacy metric frameworks (2025 review) and practical evaluation tools (PrivEval, 2025). This progression demonstrates increasing specialization in synthetic data validation while maintaining cross-disciplinary relevance. As a key participant in the HEREDITARY project (2024-2027) on gut-brain interplay data integration, Trudslev collaborates with international researchers including Dell'Aglio and Lissandrini. Though no student advising is documented, his project leadership in this major EU-funded initiative highlights significant research impact. His work shows strong potential for future applications in healthcare data sharing and microbiome research.
Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.
Lisbet Tarp is an Associate Professor in Art History at the School of Communication and Culture, Aarhus University. Her academic work bridges traditional art historical scholarship with digital methodologies and interdisciplinary research, particularly in the fields of painting, materiality, and conservation. She is actively engaged in several high-impact research projects exploring the intersections of art, science, and technology. Research Interests: Digital Art History and computational analysis of paintings Materiality and technique in historical and contemporary painting Conservation science and hidden layers in artworks Mathematics and geometry in visual art Early modern court culture and ceremonial representation Interdisciplinary practices between art and anatomy Her recent publications reflect a strong trend toward integrating digital tools into art historical inquiry, with a focus on uncovering the material and technical dimensions of paintings. Projects such as Digital Art History: Rediscovering the Painting and ANAT: Anatomical Theater demonstrate her innovative approach to visual culture through scientific and digital lenses. Her work often involves collaborative, peer-reviewed publications and digital dissemination. Scientific Projects & Activities: ANAT: Anatomical Theater (2023–2029) – Investigating dissection as aesthetic practice in early modern and contemporary contexts Digital Art History: Rediscovering the Painting (2019–2022) – Using digital methods to analyze painting techniques and material composition MoCMa: Mobility Creates Masters (2017–2019) – Studying transnational influences in European art LUMEN Center (2015–2025) – Researching Lutheran theology and its impact on confessional societies and visual culture Lisbet Tarp has contributed extensively to academic discourse through peer-reviewed journals, anthologies, and digital publications. While no formal students or awards are listed, her leadership in major research initiatives underscores her scholarly influence. She employs digital platforms for both research and pedagogy, including student-organized seminars and open-access digital versions of her work.
