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.
Søren Munch Kristiansen is an Associate Professor in the Department of Geoscience at Aarhus University, Faculty of Natural Sciences. His interdisciplinary research bridges geoscience and archaeology, focusing on the complex interactions between soil, water, and human societies across time. He is actively engaged in transdisciplinary projects involving geoarchaeology, groundwater, and public health. Research Interests: His work centers on how soil and groundwater have shaped human prehistory and continue to influence modern life. Key areas include safe drinking water from a lifelong perspective, geoarchaeological prospection, Viking Age settlements, and the application of geophysical and geochemical methods in archaeological contexts. He is particularly interested in novel, interdisciplinary methodologies. Recent Research Trends: His recent publications reveal a strong focus on integrating geophysical data (e.g., GPR, borehole databases) with archaeological interpretation, especially in 3D urban modeling and landscape change. Themes include Viking Age sites, interglacial deposits, and anthropogenic soil modifications. His work increasingly employs machine learning and large-scale data synthesis. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific students are not listed, he leads and participates in multiple funded research projects, indicating an active supervisory role. His grants span from 2016 to 2024, including projects like TITAN, SAGA, and 'Fingerprinting displaced molecular substances,' highlighting sustained funding and leadership in interdisciplinary geoscience-archaeology research. Labs and Teams: He is involved in collaborative networks such as the Soil Science & Archaeo-geophysics Alliance (SAGA), suggesting leadership in interdisciplinary research teams. His work often involves multi-proxy analyses and international collaborations, particularly in Scandinavian archaeological geophysics.
Erwin Schoof is an Associate Professor at the Department of Biotechnology and Biomedicine , Technical University of Denmark. He leads the Cell Diversity Lab and focuses on advancing proteomics and mass spectrometry technologies. Expertise in single-cell proteomics , stem cell niches , and bioinformatics . Active in myelofibrosis and leukemia research , with applications in UN Sustainable Development Goals . Research Trends from 2025–2024 include: Machine learning-driven peptide sequencing (InstaNovo, InstaNexus). Single-cell resolution tools for mapping hematopoietic stem cells and tumor microenvironments . Biomarker discovery in chronic diseases and respiratory conditions . Supervision : Mentors multiple PhD students on single-cell proteomics , omics data analysis , and biotherapeutic production . Labs & Collaborations : Collaborates with international teams on plasma proteomics , 3D bioengineering , and advanced mass spectrometry workflows .
Ankit Kariryaa is a Tenure Track Assistant Professor at the Department of Computer Science and Department of Geosciences and Natural Resource Management , University of Copenhagen. His work bridges Machine Learning and Environmental Informatics , focusing on remote sensing, geospatial analysis, and ecological modeling. University of Copenhagen, Denmark Machine Learning Section, Department of Computer Science Geography, Land, Environment and Society, Department of Geosciences Kariryaa specializes in applying deep learning and computer vision to environmental challenges. His research includes: Automated tree detection and biomass estimation via satellite imagery Multi-modal geospatial representation learning Monitoring farmland tree decline and carbon sequestration potential Agroforestry system mapping using AI Developing AI tools for climate policy and sustainability Recent work trends show a focus on quantum-inspired machine learning , environmental monitoring , and cross-cultural AI applications . His 15 most recent publications span topics in remote sensing , ecological modeling , and AI ethics , with methods ranging from neural networks to tensor-based learning. He collaborates across disciplines, notably with researchers in ecology , climate science , and quantum computing . His outreach includes seminars on AI in agroforestry and ecosystem management , while his team contributes to global tree resource databases like TreeSense.
Søren Lundbye-Christensen is an Associate Professor and Biostatistician affiliated with the Clinical Institute at the Faculty of Health Sciences, Aalborg University, and Aalborg University Hospital in Denmark. He specializes in biostatistical support for medical research, with a strong emphasis on cardiovascular and epidemiological studies. His research interests include biostatistics, survival analysis, cohort studies, clinical epidemiology, and statistical modeling in public health. He has contributed to a wide array of healthcare research, particularly in cardiovascular diseases, cancer, maternal health, and infectious diseases. His methodological expertise spans time-to-event analysis, registry-based research, and interval-censored data modeling. The recent publications highlight a strong trend in applying advanced statistical methods to large-scale clinical and population-based datasets. His work often involves collaboration with medical researchers to derive prognostic models, validate clinical databases, and assess public health outcomes. Key themes include cardiovascular risk, fertility, cancer biomarkers, and implementation of medical training programs. Scientific Contributions and Recognition: Published over 320 research articles and datasets. Active contributor to methodological advancements in biostatistics. Regular peer reviewer, including for journals like the R Journal. Public engagement through media appearances on statistics and health. Academic Advising and Grants: Søren has supervised 31 student theses, formally serving as PhD supervisor for 14 theses and as a biostatistical advisor for 19 others, primarily in mathematics and statistics. He has participated in numerous research projects funded through institutional and national grants, including studies on seasonal disease trends, postoperative complications, and metabolic disease prediction. His work often involves interdisciplinary collaboration across medicine, public health, and data science. Labs and Research Teams: He is embedded in collaborative research networks at Aalborg University Hospital and Aalborg University, contributing statistical expertise to clinical research groups. He is involved in projects utilizing Danish national health registries and has contributed to the development and validation of clinical databases. His work supports both hypothesis-driven medical research and methodological innovation in biostatistics.
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
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.
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.
Fredrik Rask Dalby is a Tenure Track Assistant Professor at the Department of Biological and Chemical Engineering, Aarhus University, affiliated with AU Engineering. His research focuses on mitigating greenhouse gas emissions from livestock farming, particularly methane and ammonia from manure management. Dalby leads multiple interdisciplinary projects including N-LIFE (2025-2028), STOREMIS (2024-2027), and PIGMET (2023-2026), addressing methane emission modeling in pig facilities and manure storage systems. His expertise spans environmental engineering, agricultural sustainability, and biogas technologies. Current projects explore surfactant treatments for methane reduction, ventilation control in manure tanks, and GHG emission quantification frameworks. Dalby collaborates with institutions like DCA - National Food & Agriculture Center, contributing to policy-relevant studies under EU directives. He holds a PhD (likely in environmental engineering) and has published extensively on manure management, ammonia mitigation, and climate-smart agriculture. His work combines computational modeling with field experiments to develop practical solutions for reducing livestock sector emissions.
Bernhard Palsson is the Scientific Director at the Novo Nordisk Foundation Center for Biosustainability (DTU Biosustain), Technical University of Denmark (DTU). His research focuses on systems biology, metabolic engineering, and computational modeling in microorganisms such as Escherichia coli and Yarrowia lipolytica . Key roles : Scientific Director, Researcher, PhD Supervisor SDG contributions : Biosustainability, Antibiotic Discovery, Climate Action Research Interests : Palsson's work spans metabolic pathways , regulatory networks , and genome-scale modeling . He explores chemical stress tolerance mechanisms, pangenome structures, and integrates machine learning with transcriptomic data to advance biosynthetic applications. His projects include antibiotic discovery via computational resources and metabolic model reconstruction for Lactobacillus and Escherichia coli species. Recent Article Trends : His 2025 submissions highlight interdisciplinary approaches combining machine learning and experimental evolution to enhance biochemical production and address antibiotic resistance. Topics include transcriptional network analysis , pangenome decomposition , and metabologenomic modeling , emphasizing scalability and data-driven methodologies. Supervision & Collaboration : Palsson mentors PhD students like Omid Ardalani and collaborates on projects such as iimena (Integration of Informatics and Metabolic Engineering for Novel Antibiotics) and pangenome metabolic model reconstruction. His team includes researchers from DTU and international institutions. Projects : iimena: Novel Antibiotic Discovery (2017–2023) Lactobacillus Pangenome Modeling (2021–2025) Networks : Collaborated with institutions in 12+ countries Co-authorships in Escherichia coli and Yarrowia lipolytica studies
Karina Kosiara-Pedersen is an Associate Professor at the Department of Political Science, University of Copenhagen. She coordinates the Center for Voting and Parties (CVAP) and contributes to the Gender & Politics research group. Her work focuses on party membership, organizational development, candidate recruitment, and political harassment. Research keywords include political parties, democracy, electoral systems, and political violence Teaching courses in Danish and Comparative Politics Current research examines gender-based anger in politics (2024-2025), political harassment (DIPAS, 2022-2025), and candidate surveys across municipal/regional/parliamentary elections. She co-leads the Political Parties Database (PPDB) and studies online harassment. Her media contributions (1,193) often address Danish political trends, including recent analysis of electoral shifts and parliamentary dynamics. She serves on the Department’s Faculty board and has been study board chair since 2022.
Harpa Birgisdottir is a Professor and Head of the Building Sustainability Section at Aalborg University's Department of Construction, Urban and Environmental Engineering. Her work focuses on Life Cycle Assessment (LCA), net-zero carbon buildings, and circular economy strategies in construction. Key Research Areas: Greenhouse Gas Emissions, Environmental Product Declarations (EPD), Urban Development, and Climate Mitigation Academic Recognition: 2022 Best Paper at Sustainable Built Environment, 2020 Applied Energy Highly Cited Award Research Trends Recent publications emphasize data-driven sustainability assessments, embodied carbon in buildings, and fire safety LCA tools. She leads EU-wide projects on greenhouse gas emissions and co-develops frameworks for net-zero carbon buildings through IEA EBC Annex 89. Scientific Awards Best Paper (Sustainable Built Environment Berlin 2022) Highly Cited Research Paper (Applied Energy 2020) Det Bæredygtige Element - Produktprisen (2019) ROCKWOOL Prisen (2017) Best Paper (2013) As a principal investigator and supervisor, she guides PhD projects on biobased fire safety and urban circularity. Her team collaborates with international researchers on climate impact metrics and sustainable construction standards.
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.
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.
Teresa Anna Steiner serves as an Assistant Professor in the Department of Mathematics and Computer Science at the University of Southern Denmark, specializing in algorithmic research with emphasis on privacy-preserving computational methods and theoretical computer science. Her research centers on differential privacy mechanisms, where she investigates trade-offs between data utility and privacy guarantees through rigorous analysis of noise injection techniques like Laplace and Gaussian distributions. She extends this work to dynamic graph databases requiring real-time privacy protections and develops novel text indexing approaches for regular expression pattern matching, contributing to foundational advancements in algorithm design for sensitive data environments. Recent 2025 publications reveal a cohesive research trajectory focused on practical implementations of differential privacy across diverse data structures, with particular attention to variance optimization in noise mechanisms, edge-level privacy in evolving graphs, and efficient indexing for textual pattern recognition. These works collectively address critical challenges in balancing computational efficiency with robust privacy guarantees in modern data systems. No scientific awards were documented in the available information. Details regarding student advising or research grant funding were not specified in the provided materials.
