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Yang ChengView profile

Associate Professor

• Supply Chain Management
• Manufacturing Strategy
• Manufacturing Network
• +5 more

Yang Cheng is an Associate Professor at the Department of Materials and Production, Aalborg University, Denmark. He holds a PhD in Mechanical Engineering from the same institution (2011), focusing on manufacturing strategy and network dynamics. His research spans supply chain management, sustainability, and global operations, with a focus on integrating technology and environmental policies into manufacturing systems. He leads or participates in high-impact projects like MAASive (2024–2026) and the Sino-Danish Center Research Project (2011–present), addressing resilience in value networks and global operations innovation. Research Interests: Supply Chain Management & Integration Sustainability & Green Technologies Manufacturing Strategy & Networks Technology Policy & Digitalization Global Operations & Cross-Border Collaboration Recent Work Trends: Prof. Cheng's 2025 articles emphasize blockchain in sustainable supply chains, green technology investments under carbon policies, and digitalization's ethical implications. His 2024 research explores smart factories, EU battery regulations, and robotization in manufacturing. These studies blend quantitative models with case-based analysis to address real-world challenges. Awards: 2024 Emerald Literati Awards – Outstanding Reviewer Advising & Grants: As PI for multiple Global Operations Management PhD programs (2019–2025), he guides research on digital transformation and university-industry collaboration. His projects receive funding from Danish and international grants, focusing on innovation and resilience in manufacturing networks. Labs/Teams: Collaborates with the Center for Industrial Production at Aalborg University and engages in international partnerships through the Sino-Danish Center. Active editorial roles include Production Planning & Control and Journal of Manufacturing Technology Management .

Giulio CiminiView profile

Associate Professor

• Statistical Physics
• Complex Networks
• Economic Networks
• +12 more

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.

• Applied Statistics
• Statistical Consultancies
• Functional Data Analysis
• +5 more

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.

Fabio PierellaView profile

Associate Professor

• Offshore Wind Energy
• Fluid Dynamics
• Structural Engineering
• +3 more

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 RaminView profile

Researcher

• Wastewater Treatment
• Computational Fluid Dynamics
• Water Resource Recovery
• +5 more

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.

• Natural Language Processing
• Explainable AI
• Fact-Checking
• +4 more

Isabelle Augenstein is a Professor at the University of Copenhagen, Department of Computer Science (DIKU), where she heads the Copenhagen Natural Language Understanding (CopeNLU) research group and the Natural Language Processing section. She is also a co-lead of the Danish Pioneer Centre for Artificial Intelligence, Denmark's largest research center initiated by the Danish Ministry of Higher Education and Science. In October 2022, she became Denmark's youngest ever female full professor. Dr. Augenstein earned her undergraduate degree in Computational Linguistics and Psychology from Heidelberg University, followed by a Master's in Computational Linguistics. She completed her PhD in Computer Science at the University of Sheffield under the supervision of Dr. Diana Maynard and Prof. Fabio Ciravegna. In 2021, she earned a Habilitation at the University of Copenhagen in Explainable Fact-checking. Professor Augenstein's primary research focuses on fair and accountable Natural Language Processing, with particular emphasis on explainability, factuality, and bias detection. Her work spans multiple subfields including automated fact-checking, stance detection, gender bias analysis, and cultural bias in language models. She has pioneered research in explainable fact-checking, developing methods that not only predict claim veracity but also provide meaningful explanations of the decision-making process. Her research group has produced numerous influential papers on measuring model fragility, quantifying gender biases, and developing robust fact-checking systems that account for distribution shifts. Her significant contributions have been recognized with several prestigious awards: ERC Starting Grant on 'Explainable and Robust Automatic Fact Checking' DFF Sapere Aude Research Leader fellowship on 'Learning to Explain Attitudes on Social Media' Karen Spärck Jones Award from the British Computing Society and Bloomberg Hartmann Diploma Prize from the Hartmann Foundation Member of the Royal Danish Academy of Sciences and Letters since 2024 Professor Augenstein has secured significant research funding including her ERC Starting Grant supporting five years of blue-sky research. She actively mentors PhD students and postdoctoral researchers through her 'ExplainYourself' project. She served as President of SIGDAT (which organizes the EMNLP conference series), having previously held leadership roles as Vice President and Vice President-Elect. She is a co-founder of Widening NLP (WiNLP), an initiative to increase diversity in the NLP community, and maintains the BIG Directory of underrepresented groups in NLP. She leads the Copenhagen Natural Language Understanding (CopeNLU) research group, which relocated to the historic Østervold Observatory in Copenhagen's Botanical Gardens in 2023. The group focuses on developing methods for explainable and robust natural language understanding, with applications in fact-checking, bias detection, and social media analysis. Professor Augenstein also co-leads the Speech and Language collaboratory at the Pioneer Centre for Artificial Intelligence, where her team investigates how language models can better serve diverse populations while maintaining accountability and transparency.

• Transportation Engineering
• Urban Planning
• Sustainable Mobility
• +5 more

Ravi Seshadri is an Associate Professor in the Transport Division at the Department of Technology, Management and Economics, Technical University of Denmark (DTU). His research focuses on designing equitable, efficient, and sustainable mobility solutions with a focus on fiscal instruments like congestion pricing and tradable permits, as well as emerging mobility modes such as shared and demand-responsive transit. He employs methods from transportation network equilibria, dynamic traffic assignment, and agent-based simulation. His research interests span transportation economics, urban planning, and intelligent transportation systems. Key areas include evaluating the impacts of automated mobility-on-demand systems, optimizing tolling strategies using predictive control and reinforcement learning, and integrating multi-modal transportation networks through game-theoretical frameworks. His work emphasizes real-world applications in urban freight systems, e-commerce logistics, and sustainable urban mobility policies. Recent projects include studying congestion pricing schemes via agent-based microsimulation, analyzing behavioral responses to decarbonization policies, and developing frameworks for tradable credit systems with peer-to-peer trading. He has contributed to both theoretical advancements (e.g., robust traffic assignment models) and applied tools like the SimMobility simulation platform. Ravi's research demonstrates a strong focus on bridging transportation engineering with policy analysis, using cutting-edge computational methods to address complex urban mobility challenges. His work spans academic publications, industry collaborations, and policy consultations to advance sustainable transportation systems.

Henrik Myhre JensenView profile

Professor

• Mechanics of Materials
• Solid Mechanics
• Mechanical Engineering
• +4 more

Henrik Myhre Jensen is a Professor at the College of Engineering , Aarhus University, specializing in Mechanics of Materials , Solid Mechanics , and Mechanical Engineering . His research focuses on fracture mechanics, composite materials, and computational modeling of structural behaviors. Research Focus Fracture mechanics in composites and layered materials Computational modeling of kink band propagation Surface wear and coating technologies Ultrasound imaging applications in mechanical systems Notable Contributions Henrik has contributed to understanding crack propagation in cantilever beams, developed numerical methods for simulating delamination in composites, and explored buckling instabilities in solids. His recent work connects machine learning (holomorphic neural networks) to traditional fracture mechanics problems. Key Projects MAGFLY (2017-2021): Magnets for Flywheel Energy Storage InnoVacc (2009): Pressure Testing of Vacuum Chambers Simulation of composite structures (2011-2020): Micro-mechanical modeling

Borja Valverde PérezView profile

Associate Professor

• Microalgae Biotechnology
• Resource Recovery
• Life Cycle Assessment
• +3 more

Borja Valverde Pérez is an Associate Professor in the Department of Environmental and Resource Engineering at the Technical University of Denmark (DTU). His research advances sustainable water resource recovery through biotechnology innovations. Research focuses on microalgae cultivation, microbial protein production, and bioelectrochemical systems for water treatment. Key projects explore nutrient recovery from waste streams and greenhouse gas mitigation in biological processes. Recent publications demonstrate innovative approaches to wastewater valorization, including microalgae-bacteria consortia for pollutant degradation and inorganic bioelectric systems for low-temperature denitrification. Work integrates experimental validation with life cycle assessment. He coordinates projects on industrial symbiosis and circular economy applications in water systems. Current initiatives investigate decarbonization pathways for water resource recovery facilities through energy-flexible operation.

Frederik Rask DalbyView profile

Academic

• Environmental Engineering
• Agricultural Engineering
• Sustainability
• +7 more

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.

• Microgrid Control Systems
• Renewable Energy Integration
• Smart Grids
• +3 more

Juan C. Vasquez is a Professor at Aalborg University's Faculty of Engineering and Science, Department of Energy Technology, and Co-Director of the Center for Research on Microgrids (CROM). He holds a PhD in Automatic Control from the Technical University of Catalonia and has held academic positions at Aalborg University since 2011. His research focuses on microgrid control, renewable energy integration, power electronics, and smart grids. He has supervised numerous PhD and master’s students and leads projects funded by EU and national grants. Education: BS in Electronics Engineering (Autonomous University of Manizales, Colombia, 2004); PhD in Automatic Control (Technical University of Catalonia, Spain, 2009). Research interests include operation and control strategies for AC/DC microgrids, maritime microgrids, energy management systems, and IoT integration in smart grids. He has authored 648+ publications, including highly cited works, and received awards like the Young Investigator Award (2019) and Clarivate’s Highly Cited Researcher status since 2017. Key projects: EU-DREAM (Digital Services for Energy Transition), NEST (National Research Infrastructure), and ActRes (Resilience in Energy Systems). Collaborations include Virginia Tech and Ritsumeikan University.

• Liver Disease
• Alcohol-Related Liver Disease
• Liver Fibrosis
• +7 more

Camilla Dalby Hansen is a researcher at the Department of Clinical Research, University of Southern Denmark, affiliated with Odense University Hospital (OUH) and the FLASH - Centre for Liver Research in Odense. Her work focuses on liver diseases, particularly metabolic and alcohol-related disorders, with a strong emphasis on biomarker development and fibrosis assessment. University: University of Southern Denmark Faculty: Faculty of Health Sciences Department: Department of Clinical Research Research Centre: FLASH - Centre for Liver Research (Odense) Collaborations: Odense University Hospital (OUH), KI Her research interests center on liver disease, alcohol-related liver disease, liver fibrosis, nonalcoholic fatty liver disease (NAFLD/MASLD), biomarkers, and prospective cohort studies. She investigates metabolic dysfunction-associated steatotic liver disease (MASLD), fibrosis progression, and the accuracy of diagnostic tools such as self-reported alcohol intake versus phosphatidylethanol biomarkers. Her work integrates clinical data, biomarker validation, and risk prediction models for early detection and management of liver disease. Camilla Dalby Hansen's recent publications (2025) in journals like The Lancet Gastroenterology & Hepatology and Journal of Hepatology reflect a research trajectory focused on improving early diagnosis and prognostic tools for liver fibrosis. Her studies often employ prospective cohort designs and involve dual biopsy validation, biomarker performance evaluation, and community-based prevalence assessments. Themes include the development of LiverPRO for primary care, discrepancies in alcohol reporting, and the role of novel biomarkers like soluble TREM2 and PRO-C3 in tracking disease activity. She has not received any publicly listed scientific awards or fellowships in the provided text. Camilla Dalby Hansen has contributed to research projects as a co-author and collaborator, particularly in dietary interventions for type 2 diabetes and liver disease. While no formal students are listed, her role in large-scale studies suggests mentorship and collaborative supervision. She is involved in EU-funded projects like LIVERAIM, indicating participation in major translational research initiatives. Her email is cdhansen@health.sdu.dk. She is part of the FLASH - Centre for Liver Research, a multidisciplinary team focusing on liver disease mechanisms, diagnostics, and treatment. Her work aligns with clinical hepatology, metabolic research, and public health screening, contributing to both academic knowledge and practical clinical tools.

Jes FrellsenView profile

Associate Professor

• Statistical Machine Learning
• Generative AI
• Deep Learning
• +5 more

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 .

Klaus MosthafView profile

Associate Professor

• Contaminant Transport in Porous Media
• Groundwater Contamination
• Numerical Modeling
• +10 more

Klaus Mosthaf is an Associate Professor in the Department of Environmental and Resource Engineering at the Technical University of Denmark (DTU), where he conducts research on contaminant transport and numerical modeling in porous and fractured media. His work focuses on protecting groundwater resources through advanced modeling of contamination from substances like PFAS, chlorinated solvents, and pesticides. He is actively involved in teaching and academic leadership, coordinating the Nordic Masters program Enviro5Tech and the Sino-Danish Center module on Pollutants and Pollution Control. Research Interests: Transport processes in porous media Groundwater contamination and remediation Numerical modeling of reactive transport Aquifer Thermal Energy Storage (ATES) Fractured and variably saturated geologies Coupled porous-medium and free-flow systems His recent publications reveal a strong focus on PFAS fate, bioremediation in ATES systems, and tracer-based characterization of glacial tills. He employs tools like COMSOL Multiphysics, Python, and FEFlow to develop predictive models grounded in laboratory and field data. Scientific Contributions: Active contributor to over 60 publications in hydrogeology and environmental engineering Key developer of models for coupled processes in subsurface systems Organizer and speaker at international conferences on multiphase flow and contaminant transport Advising and Grants: Klaus Mosthaf supervises multiple PhD students and has coordinated significant research projects, including those on PFAS transport and bioremediation. He is the main supervisor of two active PhD projects and has previously co-supervised two others. His leadership extends to board membership in the Danish Academy of Technical Sciences on Soil and Groundwater (ATV Jord og Grundvand), where he fosters collaboration among academia, consultants, and public authorities. Laboratories and Research Groups: His work is conducted within DTU Sustain, a leading research environment in environmental engineering, where he collaborates with experts in hydrogeology, bioremediation, and sustainable technologies. He is deeply integrated into a network of national and international collaborators focused on groundwater protection and sustainable subsurface utilization.

Gregor GiebelView profile

Researcher

• Wind Power Forecasting
• Renewable Energy Integration
• Wind Farm Flow Control
• +7 more

Dr. Gregor Giebel is a senior researcher and Head of Section in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specifically within the Renewable Plants in Energy Systems group. He is actively engaged in advancing wind energy technologies and their integration into modern power systems. His leadership extends to major international and EU-funded initiatives, including IEA Wind Task 51 and the NEST Facilities research infrastructure. Gregor Giebel's research focuses on short-term wind power forecasting , large-scale integration of wind into electricity grids , wind farm flow control , and condition monitoring of wind turbines . His work is instrumental in improving the reliability and efficiency of renewable energy systems. He has made significant contributions to international standardization through the IEC and is a key figure in global wind energy research coordination. The recent publications highlight a strong trend toward weather-driven energy forecasting , modeling wind farm impacts on weather systems , and developing national research infrastructures for energy transition . These works reflect a deep integration of meteorology, energy systems engineering, and policy-relevant research. His scientific recognition includes: Poster Award at the WindEurope Offshore Conference, Copenhagen 2019 Poster Award on WindEurope Conference, Copenhagen 2021 Dr. Giebel is a Principal Investigator (PI) on multiple high-impact projects such as NEST Facilities , IEA Wind Task 51 , and GreenHyScale . He is renowned for his success in research funding, with a proposal success rate exceeding 50%. He has led the EU Marie Curie Initial Training Network Train 2 Wind and previously headed the FarmConners EU Coordination Action on wind farm control. He leads and is deeply involved in the NEST Facilities —a distributed Danish research infrastructure for energy transition—and contributes significantly to the Weather2X and GreenHyScale projects, which aim to advance green hydrogen production and weather forecasting for energy systems.