Skill Extraction Professors and Supervisors in Denmark

Chenjuan Guoمشاهده پروفایل

دانشیار

Aalborg UniversityDenmark

Chenjuan Guo is an Associate Professor at the Department of Computer Science, Aalborg University, within The Technical Faculty of IT and Design. She is affiliated with the Data Engineering, Science and Systems group and the AI for the People initiative, and is part of the Daisy - Center for Data-intensive Systems. Her research focuses on machine learning, data engineering, spatio-temporal data analysis, and time series forecasting. Key projects include the Villum Foundation-funded 'Explainable AI for Complex Microbial Community Interactions and Predictions' (2021-2024) and the Astra project on time series analytics in spatial networks (2018-2021). Her research interests span representation learning, autoencoders, path representation, outlier detection, trajectory data analysis, and time series modeling. She has supervised 3 PhD students and contributed to over 60 publications, with a recent emphasis on transformer-based forecasting, neural architecture search, and continuous learning frameworks for spatio-temporal data. Her work bridges theoretical advancements with practical applications in environmental science, cloud computing, and urban mobility systems. Key achievements include developing frameworks like AutoCTS++ for automated time series forecasting and LightGTS for lightweight models. She actively collaborates internationally, contributing to conferences like ECML PKDD and CVPR. Her research is supported by grants from the Villum Foundation and other institutions.

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Lasse Riis Østergaardمشاهده پروفایل

دانشیار

Aalborg UniversityDenmark

Lasse Riis Østergaard is an Associate Professor at the Department of Health Science and Technology, Aalborg University, affiliated with The Faculty of Medicine. His research focuses on medical imaging, AI applications in healthcare, and computational methods for analyzing medical images, particularly in CT and MRI. He leads projects such as 'Modelling and quantification of the cerebral cortex' and contributes to initiatives like the Danish Centre for Health Informatics and AI for the People. Key research areas include: Medical Image Analysis: Specializing in segmentation, artifact reduction, and quantitative measurements in CT/MRI AI in Surgery: Developing deep learning models for surgical action recognition and robotic skill assessment Clinical Applications: Investigating body composition via CT, lung function correlations, and placental vascular imaging He has authored over 120 publications and supervised 5 PhD students. Notable collaborations include work with the Virtual Brain project and NemoMed. Recent studies explore ethnic differences in body composition and AI-driven surgical training. Awards: None explicitly listed, but his work has received media attention including coverage in Surgical Endoscopy and Advances in Respiratory Medicine .

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Mike Zhangمشاهده پروفایل

پژوهشگر

Aalborg UniversityDenmark

Mike Zhang is a Postdoctoral Researcher in the Data, Knowledge and Web Engineering group at the Department of Computer Science , Aalborg University . Previously, he completed his PhD in Natural Language Processing (NLP) at the IT University of Copenhagen under the supervision of Prof. Barbara Plank and Associate Professor Rob van der Goot, with additional guidance from Prof. Johannes Bjerva and Prof. Euan Lindsay during his postdoc. PhD research focused on Computational Job Market Analysis and NLP for HR Current work centers on NLP for Education and NLP Applications Active in resource creation including datasets and annotation guidelines Part of research groups NLPnorth and MaiNLP His research spans Large Language Models , Multilingualism , and Generative AI with emphasis on practical applications in education and human resources. He has contributed to datasets like HiFi-KPI and presented at venues including IEEE CVPR and ACL workshops.

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Cristian De Gobbaمشاهده پروفایل

پژوهشگر

University of CopenhagenDenmark

Cristian De Gobba is a PhD Guest researcher at the Department of Nutrition, Exercise and Sports within the Faculty of Science at the University of Copenhagen. His research focuses on developing analytical methods for food and nutrition science using advanced chromatography and mass spectrometry techniques. Dr. De Gobba's primary research interests include analytical chemistry methods development, particularly for the study of advanced glycation end-products (AGEs), alcohol biomarkers, and Maillard reaction products. His expertise spans food science, nutrition, and biochemistry, with specific technical skills in LC-MS, HPLC, and protein characterization techniques. He has developed methods for extraction and quantification of various compounds from food systems and biological samples, including alcohol metabolites in hair and acetaldehyde adducts in hemoglobin. His recent research demonstrates a strong focus on protein chemistry in food systems, particularly milk proteins and their digestion patterns, as well as the analysis of bioactive compounds in various food matrices. His work often involves collaboration with industry partners such as Danish Crown Ingredients and focuses on practical applications in food production and nutrition. The publications show consistent work in method development for analyzing complex food components and their effects on human health. Dr. De Gobba has extensive experience with protein and peptide identification using LC-MS/MS, SEC-HPLC, and UV-Vis spectroscopy. His work includes characterizing blood hydrolysates for edible protein powders and identifying bioactive peptides from milk proteins. He has developed novel methods for simultaneous determination of multiple AGEs and quantification of thiol quinones adducts.

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Barbara Plankمشاهده پروفایل

استاد مهمان

IT University of CopenhagenDenmark

Barbara Plank is a Visiting Professor at the IT-University of Copenhagen, affiliated with the NLPnorth research group. She specializes in Natural Language Processing (NLP), focusing on multilingual language understanding, computational job market analysis, and annotation tools. Her work bridges machine learning techniques with practical applications in domains like skill extraction and cross-lingual systems. Affiliations: NLPnorth, IT University of Copenhagen Key Research Areas: Multitask learning, domain adaptation, entity linking Education: Not explicitly listed in text. Research Interests: Barbara’s research emphasizes advancing NLP through robust models for under-resourced languages and real-world applications. She explores techniques like nearest neighbor methods for occupational analysis, domain-aware relation classification, and easy-to-use annotation tools (e.g., EEVEE) to democratize NLP tasks. Her work often addresses challenges in multilingual systems and ethical AI deployment. Grants & Projects: MultiSkill : Multilingual information extraction for job market analysis (2020–2024) MultiVaLUe : Multilingual variety-aware language understanding (2020–2024) Pioneer Centre for Artificial Intelligence : Focus on pre-registered replication and ethical AI (2021–2034) Awards: Amazon Research Award (2019) Outstanding paper awards at EACL 2021 and ML Evaluation Standards Workshop 2022 Labs/Teams: Active in the NLPnorth group, collaborating on projects like the 18th Linguistic Annotation Workshop and SemEval tasks.

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Subburaj Karupppasamyمشاهده پروفایل

دانشیار

Aarhus UniversityDenmark

Subburaj Karupppasamy is an Associate Professor at Aarhus University's Department of Mechanical and Production Engineering, leading interdisciplinary research focused on medical device design, biomechanics, and computational modeling for aging-related musculoskeletal disorders including osteoarthritis, osteoporosis, and scoliosis. His work integrates engineering methodologies with clinical applications to develop diagnostic tools and treatment systems. Research interests span biomechanics, medical device innovation, diagnostics, computational modeling, and AI-driven design tools. His team employs medical imaging, 3D geometric analysis, finite element modeling, and mechanobiology principles to address bone and spine health challenges, emphasizing translational outcomes through industry and clinical collaborations. Publication trends reveal a dominant focus on computational biomechanics for vertebral fracture prediction, with significant contributions to finite element analysis optimization, medical device manufacturing, and design cognition studies. Recent works also explore VR/AR/MR systems for medical training and additive manufacturing of fabrics, demonstrating cross-disciplinary applications. Scientific Awards: No specific awards, fellowships, or medals listed in source text He actively supervises PhD candidates as evidenced by his participation in the Foundational Course in PhD Supervision (November 2023) and membership on PhD examination boards. His research has generated 4 patents and 2 technology transfers but grant details remain unmentioned. The team operates within Aarhus University Engineering facilities, utilizing medical imaging, finite element simulation, and AI tools for musculoskeletal health research. Collaborations with clinical institutions and industry partners drive their mission to translate engineering solutions into practical healthcare technologies for improving quality of life in chronic conditions.

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Bent Petersenمشاهده پروفایل

پژوهشگر

University of CopenhagenDenmark

Bioinformatics
Genomics
Metagenomics
+۵ مورد دیگر

Bent Petersen serves as a Senior Researcher at the Section for Hologenomics within the Globe Institute at the University of Copenhagen. With over 13 years of professional experience in Bioinformatics, he is a key member of the Computational Biodiscovery group where he applies machine learning techniques to projects focused on deciphering the medicinal potential of the Rainforest. His primary expertise lies in genomics and metagenomics with extensive work involving Next Generation Sequencing data analysis. His educational background includes: PhD in Bioinformatics from the Technical University of Denmark (DTU), with dissertation on "Prediction of protein structural features by use of artificial neural networks" (2011) Master's degree in Biotechnology from DTU, with thesis on "Prediction of local structural elements by use of artificial neural networks" (2007) Petersen's research interests span multiple cutting-edge fields including bioinformatics, genomics, metagenomics, machine learning applications in biology, and the study of host-microbiota interactions. His work bridges computational approaches with biological discovery, particularly in areas related to rainforest biology, phage therapy, and agricultural microbiome research. He actively collaborates with scientific groups worldwide to expand research portfolios in NGS, phage biology, rainforest biology, supercomputing, and machine learning applications. With 76 research outputs including journal articles, letters, and preprints, Petersen's publication record shows a strong focus on genomic analyses across diverse biological systems - from African hunting dogs and Galápagos plants to agricultural systems and microbial communities. His recent work demonstrates particular interest in host-microbiota interactions, phage therapy applications, and the genomic basis of plant domestication and adaptation. Petersen has significant teaching experience, having previously served as Head of Studies at DTU. He is recognized for his excellent educational skills and has conducted international mobile workshops in NGS, metagenomics, and bioinformatics across Brazil, China, Colombia, Egypt, India, Malaysia, and the Faroe Islands. His external positions include Adjunct Lecturer and Deputy Director at the Asian Institute of Medicine, Science and Technology, as well as Editorial Board Member for Scientific Reports since 2017. He is actively involved in research collaborations worldwide and serves as a member of the Chairmanship of the Biological Corps for external examiners (Censorkorpset) since 2019. His ORCID identifier is 0000-0002-2472-8317, and his research has been referenced across multiple platforms including news outlets, social media, and academic readership services.

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Rob van der Gootمشاهده پروفایل

دانشیار

IT University of CopenhagenDenmark

Rob van der Goot is an Associate Professor in Data Science at the IT University of Copenhagen. His affiliations include the NLPnorth group and the Pattern Recognition Revisited lab . His research focuses on Natural Language Processing (NLP), with emphasis on language modeling, lexical normalization, and computational job market analysis. Key contributions include the development of the EEVEE annotation tool, studies on language model biases, and cross-lingual parsing techniques. He has received prestigious awards such as the Best Paper Award at W-NUT 2022 and the Outstanding Paper Award at EACL 2021 . His work spans projects like the Pioneer Centre for Artificial Intelligence (funded by the Danish National Research Foundation) and Multi-Task Sequence Labeling Under Adverse Conditions (funded by Amazon). His research also intersects with societal impacts, addressing bias in AI systems and improving NLP tools for under-resourced languages. Media engagements include discussions on AI adoption in Danish municipalities and business applications. His publications (48+) span topics from domain adaptation to large language model evaluation, emphasizing practical NLP solutions and reproducible research practices.

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Joe Dumitمشاهده پروفایل

استاد

Aarhus UniversityDenmark

Joe Dumit is a Professor at the University of California Davis, holding appointments in Science and Technology Studies (STS), Anthropology, and Performance Studies. He serves as Chair of Performance Studies and is a key figure in interdisciplinary research, bridging anthropology, neuroscience, gaming, and data studies. His work examines how knowledge and technology shape human experience, particularly through studies of pharmaceutical marketing, brain imaging, and embodied practices like Contact Improvisation. Research interests include the anthropology of neuroscience, gaming studies, and the critical analysis of data science. Notable publications include *Drugs for Life* (2012) and *Picturing Personhood* (2004). He co-founded the ModLab to explore gaming and interfaces, and collaborates internationally on projects like the *Experiencing, Experimenting, Reflecting* initiative with Aarhus University. His recent work integrates immersive visualization technologies (e.g., KeckCAVES) and improvisation studies, emphasizing embodied cognition. Awards include recognition for *Cyborg Babies* as one of the Top 25 Books of the Year by the Voice Literary Supplement. Dumit is also pivotal in developing the Data Studies undergraduate program at UC Davis, merging critical thinking with technical skills.

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Johannes Wachsمشاهده پروفایل

دانشیار

University of CopenhagenDenmark

Johannes Wachs is an Associate Professor at the Institute of Data Analytics and Information Science, Corvinus University of Budapest, and a Research Fellow at the Centre for Economic and Regional Studies. He is affiliated with the Complexity Science Hub Vienna, where he has been a faculty member since April 2020. His interdisciplinary research bridges data science, network science, and complexity to study digital economies, open source software, and societal challenges. PhD in Network Science, Central European University (2019) MS in Applied Mathematics, Central European University (2012) BS in Mathematics and Economics, Tulane University (2009) His research focuses on the application of network and data science to understand social, economic, and technical systems. Key interests include open source software ecosystems, AI’s impact on knowledge sharing, corruption detection, urban inequality, and digital innovation. He uses large-scale digital trace data to model complex behaviors in online communities, software development, and public policy. His recent publications reveal a strong trend in analyzing digital platforms such as GitHub and Stack Overflow, studying brain drain in tech, and assessing climate and health risks in Austria. His work combines network modeling, machine learning, and empirical analysis to uncover patterns in human behavior and systemic risk. IMF Anti-Corruption Challenge Winner (2020) Principal Investigator, CRISP Project (2021–2024), funded by FFG Grants from Hungarian Research Funding Agency (OTKA), City of Vienna, and WU Projects Johannes Wachs actively supervises PhD and Master’s students, including Hannah Schuster and Brigi Németh. He has taught courses in computational social science, social networks, and data mining at institutions including RWTH Aachen, CEU, and WU Vienna. He is launching a new MSc in Social Data Science at Corvinus in 2025. He leads the CRISP project, which builds semantic data pools for real-time crisis response and intervention, integrating heterogeneous data sources for impact forecasting and policy transparency.

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Tor Ivan Simonsenمشاهده پروفایل

پژوهشگر

University of CopenhagenDenmark

Dr. Tor Ivan Simonsen is a Translational Postdoc Researcher at the Department of Geosciences and Natural Resource Management within the Faculty of Science at the University of Copenhagen. His research focuses on sustainable materials development, particularly in the area of lignin-based technologies for wood protection and biofuels. As co-inventor and innovation lead of the LignoSolve technology, he bridges academic research with industrial applications to create high-performance, eco-friendly materials for outdoor applications. Dr. Simonsen's educational background includes: PhD in Wood Science from the Department of Geosciences and Natural Resource Management (awarded October 10, 2024), with dissertation titled "Lignin-Alcohol Dispersions: A Promising Marine Biofuel" Master's degree in Biology Biotechnology from the University of Copenhagen (awarded September 22, 2017), with thesis on "Light-driven enzymatic oxidation of polysaccharides - Light response and oxygen species" Dr. Simonsen's research interests center on sustainable materials science with a particular focus on lignin applications. He is passionate about bridging academia and industry to create high-performance materials for outdoor applications. His work spans wood science, biorefining, biofuels, and sustainable materials engineering. As a lignin scientist, he specializes in impregnating wood with lignin to enhance its natural resistance to fungal decay. His current research focus involves developing entrepreneurial skills through Spin-Outs Denmark and paving the way for a successful spinout of LignoSolve technology. Analysis of Dr. Simonsen's recent publications reveals a strong focus on lignin-based technologies across multiple applications. His work spans wood protection, biofuel development, and sustainable materials engineering. Key themes include lignin-alcohol dispersions as marine biofuels, lignin impregnation for wood preservation, and optimization of lignin extraction and processing methods. His research demonstrates interdisciplinary collaboration across chemistry, materials science, and engineering to develop practical, sustainable solutions for industry applications. Dr. Simonsen has received recognition for his research contributions: Best oral presentation award (December 1, 2022) Best poster award (November 30, 2023) As innovation lead for LignoSolve technology, Dr. Simonsen is actively translating academic research into commercial applications. He is developing entrepreneurial skills through Spin-Outs Denmark to facilitate the successful spinout of LignoSolve. His work has attracted media attention, with three press/media contributions covering sustainable shipping fuels and eco-friendly wood protection. His research has been referenced in policy sources and has garnered attention from researchers worldwide as indicated by Mendeley reader statistics. Dr. Simonsen is part of the Forest and Bioresources research group within the Department of Geosciences and Natural Resource Management. His collaborative network spans multiple institutions and countries, focusing on advancing lignin-based technologies for sustainable applications. He is currently working to establish LignoSolve as an independent venture to bring these innovations to market.

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