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• Electrocatalysis
• PEM fuel cells
• Degradation mechanisms of fuel cell catalysts
• +3 more

Matthias Arenz serves as an Affiliate Professor in the Department of Chemistry at the University of Copenhagen, where he has maintained a prominent research position since 2010. His work centers on electrocatalysis and fuel cell technology, with particular focus on understanding catalyst degradation mechanisms and developing more durable electrocatalytic materials. With over 158 research publications and an H-index of 29, Professor Arenz leads an active research group that has secured substantial external funding and maintains extensive international collaborations. Arenz completed his academic training in Germany, earning a Diploma in Physics from the University of Bonn in 1999, followed by a PhD in Physical Chemistry from the same institution in 2002. His early career included prestigious postdoctoral appointments: a DAAD stipend at Lawrence Berkeley National Laboratory (LBNL) in 2001 and a Feodor Lynen Postdoctoral scholarship at LBNL from 2002-2004. In 2006, he established himself as an independent researcher through an Emmy Noether Research group leadership position at TU-Munich before joining the University of Copenhagen faculty in 2010. Professor Arenz's research program focuses on electrocatalysis for proton exchange membrane (PEM) fuel cells, specifically investigating the activity and stability of platinum-alloy nanoparticles, degradation mechanisms of fuel cell catalysts, and utilizing size-selected metal clusters as model catalysts. His work bridges fundamental surface science with practical energy applications, employing advanced characterization techniques to understand catalyst behavior at the atomic level under operating conditions. This research directly addresses critical challenges in fuel cell durability and efficiency. Analysis of Arenz's recent publication record reveals a strong emphasis on operando and in situ characterization methods to study catalyst behavior during actual operation. His research spans from fundamental studies of single-crystal models to applied research on commercial catalyst systems. Key emerging themes include the development of high-entropy alloys for improved stability, advanced characterization of degradation mechanisms, and innovative cell designs for electrochemical studies. Professor Arenz has successfully secured substantial external research funding, with over 20 million DKK from Danish and European sources since 2010, and approximately 1.5 million euros from German sources between 2004-2009. He has supervised 5 postdoctoral researchers, 9 PhD students, 3 master's students, and 5 bachelor's students either currently or to completion. His research group operates within the Nanocatalysis facility at the University of Copenhagen, maintaining state-of-the-art equipment for electrocatalyst synthesis and characterization.

• Molecular Biology
• Pharmacology
• Veterinary Pathobiology
• +4 more

Dan Arne Klærke serves as a Professor in the Department of Veterinary and Animal Sciences at the University of Copenhagen, specializing in Pathobiological Sciences. His research integrates molecular biology, pharmacology, and veterinary medicine through advanced electrophysiological techniques and genomic approaches. His primary research interests focus on molecular mechanisms of ion channel function , parasite drug targets , and neuropharmacology related to migraine pathways . Utilizing Xenopus laevis oocyte expression systems as a core methodology, his work spans veterinary genomics (particularly equine miRNA), anthelmintic drug mechanisms against whipworms, and migraine-associated signaling pathways. Current investigations examine environmental xenobiotic impacts on neuronal signaling and computational modeling of drug-channel interactions. Analysis of recent publications reveals strong international collaborations across veterinary genetics, electrophysiology, and parasitology. His work demonstrates consistent methodological innovation in membrane protein expression systems and translational applications from basic channel physiology to veterinary and human therapeutics. Klærke actively participates in academic discourse through conference engagements including the 2019 Scandinavian Physiological Society Meeting. His research group maintains technical expertise in oocyte-based electrophysiology, molecular cloning, and computational modeling approaches applied to both veterinary and biomedical questions.

• Pharmacogenomics
• Bioinformatics
• Deep Learning
• +2 more

Trinh Trung Duong Nguyen serves as a Postdoctoral Research Fellow within the Department of Drug Design and Pharmacology at the Faculty of Health and Medical Sciences, University of Copenhagen. His institutional affiliation centers on pharmaceutical informatics with a focus on computational approaches to drug design and pharmacological research. Dr. Nguyen's research program integrates pharmacogenomics, bioinformatics, and deep learning methodologies to address complex challenges in drug development and medical diagnostics. His work emphasizes the creation of practical computational tools for pharmacogenomic data analysis, including web-based platforms for drug-gene interaction visualization, and develops novel AI-driven solutions for medical image analysis and protein sequence interpretation. This interdisciplinary approach bridges molecular pharmacology with artificial intelligence to advance personalized medicine. Analysis of his recent publications (2022-2025) reveals a consistent trajectory in applying machine learning to biomedical problems, with particular emphasis on pharmacogenomics infrastructure development and medical computer vision applications. His publications demonstrate expertise in creating interpretable AI models for biological sequence analysis and developing accessible web platforms for genomic data, indicating a research philosophy centered on translational computational solutions for real-world healthcare challenges. No scientific awards are documented in the available institutional records. Current information does not specify student advising responsibilities or externally funded research grants. His collaborative network appears active within computational pharmacology and medical AI domains based on co-authorship patterns, though specific mentoring activities remain unreported in the source material.

• Machine Learning
• Tensor Decomposition
• Chemometrics
• +3 more

Jesper Løve Hinrich serves as a Guest Researcher in the Design and Consumer Behavior section at the University of Copenhagen's Department of Food Science, focusing on advanced computational methodologies for complex data analysis. His research spans interdisciplinary domains including: Machine Learning for predictive modeling Tensor Decomposition techniques for multiway data Chemometrics applications in spectroscopy Health Informatics for clinical decision support Signal Processing of time-resolved measurements Data Science for multi-modal integration Analysis of his 2019-2024 publications reveals a cohesive research trajectory centered on probabilistic tensor frameworks. His work progresses from foundational tensor train decomposition (2019) to sophisticated coupled decompositions handling data drift (2023) and higher-order arrays (2024), while bridging theoretical advances with practical implementations in fluorescence spectroscopy and obstetric care analytics. This demonstrates consistent innovation in mathematical frameworks for real-world data challenges across scientific domains.

• Obstetric Anaesthesia
• Epidural Analgesia Management
• Simulation-Based Medical Education
• +3 more

Kim Ekelund serves as Clinical Associate Professor in the Department of Anaesthesiology within the Faculty of Health and Medical Sciences at the University of Copenhagen. Based at Blegdamsvej 3 in Copenhagen, Denmark, Dr. Ekelund maintains active clinical and research roles in obstetric anaesthesia with email contact kim.ekelund@sund.ku.dk and phone +4527285042. Research focuses on obstetric anaesthesia complications , particularly epidural failure management and maternal mental health biomarkers. Key projects include ESAIC clinical guidelines development, ultrasound-guided procedure phantoms, and simulation-based training evaluation. Recent work integrates predictive modeling for labour dystocia and educational interventions for anaesthesia trainees. Current publications demonstrate strong emphasis on translational clinical research bridging anaesthesiology, obstetrics, and medical education. The 2025 ESAIC guidelines represent international consensus work, while biomarker studies explore novel physiological connections between pregnancy and mental health. Dr. Ekelund actively collaborates across European institutions, evidenced by multi-center publications and international guideline development. Current research networks include anaesthesiology departments across Scandinavia and ESAIC working groups.

• Biophysics
• Soft Matter Physics
• Computational Modeling
• +2 more

Yavor Kirilov Novev serves as a Guest Researcher at the Biocomplexity group within the Niels Bohr Institute, University of Copenhagen, focusing on quantitative modeling of biological and soft matter systems. His research spans Biophysics , Soft Matter Physics , and Computational Modeling , with specialized expertise in cellular mechanotransduction pathways (particularly Rho/YAP signaling) and polymer aggregate dynamics. He employs mathematical frameworks to analyze spatiotemporal phenomena in cellular mechanics and enzymatic degradation processes, bridging theoretical physics with biological applications. Recent publications demonstrate consistent contributions to interdisciplinary modeling, with 2021 work on cellular signaling dynamics and 2020 research on polymer digestion mechanisms. These studies reflect his focus on multi-scale approaches to complex biophysical systems, emphasizing predictive computational techniques. He operates within the Biocomplexity research environment at the Niels Bohr Institute, which specializes in theoretical and quantitative analysis of emergent phenomena in biological contexts.

• Dermatology
• Immunology
• Genetics
• +3 more

Rune Kjærsgaard Andersen is a Postdoctoral Researcher at the Department of Immunology and Microbiology within the Faculty of Health and Medical Sciences at the University of Copenhagen. He is affiliated with the Skin Immunology Research Center, where he conducts research on hidradenitis suppurativa, a chronic inflammatory skin condition. His research interests span dermatology, immunology, and genetics, with a specific focus on hidradenitis suppurativa pathogenesis, genetic susceptibility, epidemiology, and associated comorbidities. His work investigates the connections between hidradenitis suppurativa and conditions like cardiometabolic disease and female infertility, while also developing predictive algorithms for disease progression. Dr. Andersen has published extensively on hidradenitis suppurativa, with notable contributions including genome-wide association studies, epidemiological research across different populations (including Greenland), and methodological frameworks like the Global Hidradenitis Suppurativa Atlas (GHiSA). His recent publications (2023-2025) demonstrate a strong focus on genetic factors, pain assessment, disease progression modeling, and international collaborative research. Among his notable achievements is receiving the BRIDGE fellowship in May 2022, which has garnered significant attention with coverage across multiple news outlets, social media platforms, and clinical guideline sources. Dr. Andersen actively contributes to the academic community through peer review activities, having reviewed manuscripts for prominent dermatology journals including Archives of Dermatological Research, British Journal of Dermatology, and Journal of the European Academy of Dermatology and Venereology. He has also engaged with media, including an interview for Medicinske Tidsskrifters's Dermatological newsletter in March 2024.

• Anaesthesia
• Perioperative Medicine
• Artificial Intelligence
• +3 more

Kira Philipsen Prahm serves as an External Lecturer within the Department of Clinical Medicine at the University of Copenhagen. Her institutional affiliation is evidenced by her regionsjaelland.dk email domain and Copenhagen address (Blegdamsvej 3, 2200 København N), linking her to Region Zealand's healthcare-academic partnership. Her research focuses on integrating artificial intelligence into perioperative medicine, specifically through the development of the TRIPLE-A (AI and Automation in Anaesthesia) Perioperative Database. This work centers on creating scalable platforms for epidemiological analysis, predictive modeling, quality control systems, and automated data retrieval within anaesthesia practice. Her methodology emphasizes real-world clinical implementation to enhance surgical safety and operational efficiency through data-driven decision support. Analysis of her sole documented publication reveals a strong trend toward operationalizing AI in routine anaesthesia workflows, with emphasis on longitudinal database utility since 2017. The research bridges clinical practice and data science, targeting practical applications in quality monitoring and predictive analytics for perioperative outcomes. Scientific Awards: No awards or honors were documented in the provided materials Advising and Grants: No graduate students or doctoral advisees were listed No research grants or funding sources were specified Laboratory and Collaborative Efforts: Active member of the TRIPLE-A Collaborator Group, a multidisciplinary Danish research consortium focused on AI implementation in anaesthesia Collaborates with clinicians and data scientists across Eastern Denmark's healthcare institutions

• Emergency Abdominal Surgery
• Surgical Complexity Assessment
• Postoperative Complications
• +3 more

Thomas Korgaard Jensen serves as a Clinical Associate Professor at the Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen. He maintains dual appointments with both the university (sund.ku.dk) and the regional healthcare system (regionh.dk), reflecting his clinical-academic role. His work bridges surgical practice with academic research, focusing on emergency abdominal surgery and reproductive health outcomes. Dr. Jensen's research interests center on emergency abdominal surgery complexity , postoperative complications , and reproductive health outcomes . His work analyzes surgical history profiles, frailty assessment in surgical patients, and semen quality correlations with lifespan. He employs both clinical observational studies and nationwide survey methodologies to address these topics. His recent publications demonstrate significant impact, with multiple articles receiving media attention ( Picked up by 142 news outlets ) and social media discussion ( Posted by 39 X users ). The research shows consistent focus on surgical outcomes assessment and male reproductive health epidemiology. Dr. Jensen has received notable recognition for his work, though specific awards aren't detailed in the available information. His research has been widely shared across academic and social media platforms, indicating substantial interest in his findings. As a Clinical Associate Professor, Dr. Jensen contributes to both clinical practice and academic training. His work with colleagues across multiple Danish institutions demonstrates strong collaborative networks within the Scandinavian surgical research community. His dual focus on surgical complexity and reproductive health represents an interdisciplinary approach to clinical research.

Jason KoskinenView profile

Associate Professor

• Neutrino Physics
• Particle Physics
• Astroparticle Physics
• +3 more

D. Jason Koskinen is an Associate Professor at the Niels Bohr Institute, University of Copenhagen, specializing in Experimental Particle Physics. His primary research focuses on measurements of neutrino oscillation using the IceCube neutrino observatory, specifically the DeepCore sub-array and IceCube Upgrade. Dr. Koskinen investigates the properties of neutrinos, which are the most abundant particles in the known universe after photons. His work explores how neutrinos oscillate quantum mechanically between flavors (electron $$\nu_e$$, muon $$\nu_\mu$$, and tau $$\nu_\tau$$) as they propagate, described as an admixture of mass eigenstates ($$\nu_1$$, $$\nu_2$$, and $$\nu_3$$). This research provides critical insights into physics beyond the Standard Model, as neutrino mass contradicts the Standard Model's prediction of massless neutrinos. His recent publications demonstrate expertise in analyzing IceCube data across multiple domains including neutrino oscillation parameters, cosmic-ray anisotropy, dark matter searches, and astrophysical neutrino spectra. His work employs advanced statistical methods and machine learning techniques for precision measurements that have important consequences for cosmology and fundamental physics. Research Focus: Neutrino oscillations, IceCube data analysis, Beyond Standard Model physics Methods: Statistical analysis, machine learning, experimental data reconstruction Current Projects: DeepCore sub-array analysis, IceCube Upgrade Dr. Koskinen has presented his research at numerous international conferences including NuPhys2014, Neutrino Oscillation Workshops, and the Interplay of Particle and Astroparticle Physics conference. He has also organized events such as the Astroparticle Neutrino Physics in Antarctica conference. He teaches advanced courses including "Advanced Methods in Applied Statistics" (2016-2023) and "Quantum Mechanics" at the University of Copenhagen, emphasizing practical statistical methods and data analysis approaches relevant to modern physics research.

• Bioinformatics
• Genomics
• Metagenomics
• +5 more

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.

• Pharmacology
• Drug Design
• Pharmaceutical Informatics
• +3 more

Morten Lindow serves as a Professor in the Department of Drug Design and Pharmacology at the Faculty of Health and Medical Sciences, University of Copenhagen, Denmark. His research spans Pharmacology, Drug Design, and Pharmaceutical Informatics, with emphasis on computational approaches to molecular modeling, bioinformatics, and structure-based drug discovery. His work integrates pharmacoinformatics methodologies to optimize pharmaceutical compounds and predict drug interactions. Based at Universitetsparken 2 in Copenhagen, he contributes to academic programs within the pharmaceutical sciences division, focusing on quantitative analysis of drug behavior and therapeutic optimization.

• Clinical Pharmacology
• Oncology
• Cardiovascular Medicine
• +3 more

Marie Lund serves as Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen's Faculty of Health and Medical Sciences, specializing in Clinical Pharmacology. Her research focuses on drug safety and pharmacovigilance, particularly examining cardiovascular complications associated with cancer therapies and electrolyte disorders from diuretic treatments. Her primary research interests include clinical pharmacology, oncology, cardiovascular medicine, and pharmacoepidemiology. Lund investigates critical intersections between cancer treatments and cardiovascular health, with emphasis on aromatase inhibitors' cardiotoxic effects in breast cancer patients, LDL-cholesterol dynamics during hormone therapy, and thiazide-induced hyponatremia mechanisms. Her work employs nationwide cohort studies and real-world data analysis to address drug safety questions with direct clinical implications. Lund's recent publications reveal strong trends in pharmacoepidemiology and translational pharmacology, with significant contributions to understanding drug-induced electrolyte imbalances and cardiovascular risks in cancer therapy. Her research spans from basic pharmacogenomics (GWAS studies on sodium regulation) to regulatory science (comparative analysis of drug approval pathways), demonstrating methodological breadth across observational studies, predictive modeling, and policy-relevant research. Her collaborative network includes major Danish health registries and international research groups, with publications appearing in high-impact journals including The Lancet Oncology, JAMA Oncology, and Annals of Internal Medicine. Lund's work has generated substantial scientific discussion, evidenced by media coverage across 14 news outlets and social media engagement from hundreds of researchers.

• Geriatrics
• Frailty Assessment
• Sarcopenia Diagnostics
• +3 more

Martin Schultz serves as a Clinical Associate Professor in the Department of Clinical Medicine under the Faculty of Health and Medical Sciences at the University of Copenhagen. His clinical appointment is based at Gentofte Hospital (Gentofte Hospitalsvej 1, 2900 Hellerup) with additional affiliation to the Blegdamsvej campus (2200 København N), specializing in Internal Medicine: Geriatrics. His research integrates clinical practice with academic investigation in elderly care. Dr. Schultz's research focuses on critical geriatric syndromes including frailty, sarcopenia, and acute care biomarkers. His work examines falls risk, physical decline during cancer treatment, and novel diagnostic markers like GDF-15 and neutrophil gelatinase-associated lipocalin. Recent publications demonstrate strong emphasis on cross-sectional analyses of acutely admitted elderly patients and validation of clinical prediction models. His publication record shows significant collaboration across Danish medical institutions, particularly through the Copenhagen PROTECT Study and BIOFRAIL research. The 2025 policy commentary co-authored with 25 researchers highlights his active role in shaping national geriatric research strategy. Current work includes machine learning applications for mortality prediction using routine blood tests and investigation of partial oral antibiotic therapy in endocarditis. Scientific contributions include: Development of frailty-sarcopenia diagnostic frameworks Validation of biomarkers for acute kidney injury Analysis of physical decline in oncogeriatric populations Machine learning models for acute care mortality prediction Dr. Schultz maintains active clinical research through hospital-based studies at Copenhagen University Hospital facilities, with recent work emphasizing translational applications of geriatric assessment tools. His collaborations span cardiology, oncology, and nephrology departments, reflecting interdisciplinary approaches to elderly care challenges.

• Quantum Chemistry
• Quantum Computing
• Computational Chemistry
• +3 more

Phillip Wagner Kastberg Jensen serves as both Assistant Professor and Postdoc in the Department of Chemistry at the University of Copenhagen. Based at Universitetsparken 5, 2100 København Ø, he can be contacted via phone (+4535333681) or email (pwkj@chem.ku.dk). His research bridges quantum computing and quantum chemistry with emphasis on: Quantum algorithm development for molecular property calculations Polarizable embedding frameworks for hybrid quantum-classical simulations NISQ-device-compatible linear response formulations Hyperfine coupling and electric field gradient computations Error analysis in quantum chemistry simulations Orbital optimization techniques for near-term hardware Publications from 2023-2025 reveal consistent focus on adapting quantum computing to solve quantum chemistry challenges, particularly targeting hardware limitations of current quantum devices. His work shows strong collaboration patterns with S. P. A. Sauer, J. Kongsted, and S. Coriani across multiple publications. No scientific awards were documented in the source material. Details regarding student supervision, grant funding, laboratory infrastructure, or research team composition were not provided in the available text.