Morten Nielsen is a Professor at the Department of Health Technology, Technical University of Denmark, specializing in Bioinformatics with a focus on Immunoinformatics and Machine Learning . His research develops pattern recognition algorithms for immune system characterization and protein structure analysis, contributing to vaccine design against infectious diseases like HIV and tuberculosis. Professor since 2008 Director of Algorithm in Bioinformatics course (27623) Active in 8 current and 27 completed research projects Research spans epitope prediction , T-cell receptor modeling , and genomic variation analysis of pathogens. Recent work (2024) includes cancer neo-epitope immunogenicity studies, B-cell epitope prediction tools (DiscoTope-3.0), and TCR specificity modeling using machine learning. Current projects involve deep immune receptor modeling , personalized neoantigen screening , and autoimmunity pattern identification , with students including L. Machado, B. Scapolo, S. N. Deleuran, G. Nos, and A. B. Saksager.
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 .
Prof. Dr. Markus List is a Professor of Data Science of Systems Biology at the TUM School of Life Sciences, Technical University of Munich (since 2023). He previously served as Group Leader at the Chair of Experimental Bioinformatics (2018–2023) and held a PostDoc position in Computational Biology at the Max-Planck Institute for Informatics (2015–2018). His educational background includes a PhD in Molecular Oncology, an MSc in Bioinformatics from the University of Southern Denmark, and BSc and further studies in Bioinformatics at Eberhard-Karls Universität Tübingen. Current Role: Professor of Data Science and Systems Biology Previous Roles: Group Leader, PostDoc, and Academic Researcher His research focuses on interdisciplinary applications of data science to systems biology, bioinformatics, and molecular oncology. He also explores organizational theory, innovation processes, and the dynamics of routines in management contexts. His work bridges computational methods and organizational challenges, addressing topics like digital twins, distributed innovation, and strategic adaptation. Key contributions include studies on organizational imprinting, digital transformation in firms, and the role of routines in institutional dynamics. His research has been published in top-tier journals and presented at international conferences.
Birgitte Zeuner is an Associate Professor at the Department of Biotechnology and Biomedicine , Technical University of Denmark, specializing in Protein Chemistry and Enzyme Technology . Her research focuses on Enzymatic Synthesis Technology with particular emphasis on carbohydrate-active enzymes. Active supervisor in Engineering alkenal reductase reversibility (2025-2028) Main supervisor in Regioselectivity in enzymatic carbohydrate synthesis (2024-2027) Supervisor in Enzymatic xyloglucan modification (2018-2022) Recent 54 publications highlight her work on glycosylation, human milk oligosaccharides, and transglycosylation. She has received significant attention in Mendeley readership and peer review platforms. Current projects explore: Enzyme engineering for biomass upgrading Sustainable biocatalytic processes using ionic liquids Gut microbiome interactions with plant-derived carbohydrates Her research aligns with UN Sustainable Development Goals for biocatalytic applications in health and sustainability.
Mark D. Scherz is an Associate Professor at the Natural History Museum of Denmark, University of Copenhagen. His work focuses on evolutionary biology, taxonomy, and herpetofauna of Madagascar, integrating molecular and morphological approaches. ERC Starting Grant (GEMINI) for vertebrate miniaturization genomics Co-PI on DFG Taxon-OMICS grant Develops integrative taxonomic methods using micro-CT and museomics Research Interests : Specializes in the evolutionary dynamics of giant pseudo-island systems like Madagascar, investigating macroevolution, convergent evolution, and speciation. Key projects include: Phylogenetic analysis of microhylid and mantellid frogs Comparative osteology of miniaturized vertebrates Biofluorescence mechanisms in geckos and chameleons Biogeographic patterns in Malagasy reptiles/amphibians Publication Trends : Recent work emphasizes cross-disciplinary approaches (2025: skull morphology in snakes; 2024: amphibian genomics) 2021 studies on fluorescence and miniaturization Long-term taxonomic revisions of amphibians (2019-2024) Scientific Awards : ERC Starting Grant (2025) DFG Priority Programme participant (Taxon-OMICS) Collaborations : Works closely with Miguel Vences (Technical University of Braunschweig) and Frank Glaw (Bavarian State Collection of Zoology), focusing on Malagasy amphibians and reptiles.
Peter Sestoft is a Professor at the IT University of Copenhagen (ITU), leading the Computer Science Department since 2017. His primary roles include academic leadership, research in programming languages and software engineering, and teaching. He holds a PhD in Computer Science from the University of Copenhagen (1991) and has held academic positions at institutions like the Royal Veterinary and Agricultural University and the Technical University of Denmark before joining ITU in 1999. His research focuses on programming languages, functional and managed object-oriented languages, parallel programming, compilers, and spreadsheet implementation technologies. He has developed influential tools like the C5 Generic Collection Library for C# and Moscow ML, a Standard ML implementation. His work on Funcalc and Corecalc advanced spreadsheet technology with user-defined functions and efficient recalculation algorithms. Key contributions include over 30 publications, including books on programming language concepts and Java/C# syntax. He has led major research projects such as 'Popular Parallel Programming' (P3) and 'Probabli' for actuarial calculations. His academic service includes roles on national grant committees and international conference organizing committees. Notable advising includes PhD students like Andrzej Wasowski (ITU Professor) and David Christiansen (Director of Haskell Foundation). His work has been recognized through grants exceeding 25 million DKK and collaborations with institutions like Microsoft Research and Harvard University.
Chao Sun is an Associate Professor affiliated with multiple departments at Aarhus University , including the Department of Molecular Biology and Genetics, DANDRITE, the Interdisciplinary Nanoscience Center (INANO-MBG), and the Department of Biomedicine. His research integrates neurobiology , molecular cell biology , and nanotechnology , focusing on proteostasis, synaptic regulation, and advanced imaging techniques. PhD in Chemistry from Cornell University (2013-2018) Research interests include: Cellular neurobiology Proteostasis and protein turnover Super-resolution microscopy applications Proteomics of neuronal compartments Synaptic biology and plasticity Article trends reveal expertise in: Proteasome dynamics in synapses Multi-omics approaches to subcellular protein synthesis Single-molecule imaging in synaptic contexts Quantitative analysis of neuronal protein turnover Collaborations include leading researchers like Poul Nissen and Erin Schuman, with publications in high-impact journals such as Science and Current Opinion in Neurobiology . His work bridges molecular neuroscience with cutting-edge nanoscale imaging technologies.
Ida Moltke is an Associate Professor in the Department of Biology at the University of Copenhagen's Faculty of Science, specializing in Computational and RNA Biology. She leads a research group focused on developing and applying statistical and computational methods to genomic data. Her work spans both population genetics and medical genetics, with particular emphasis on human evolution, population history, and identifying genetic variants associated with diseases like type 2 diabetes. Current position: Associate Professor (Promotion Programme), Department of Biology, University of Copenhagen (2024-present) Previous positions: Associate Professor (2020-2024), Assistant Professor (2015-2019) Education: PhD in Biology (2011), MSc in Bioinformatics (2007), BSc in Computer Science and Math (2005), all from University of Copenhagen Dr. Moltke's research focuses on developing novel bioinformatics tools to analyze genomic data, with applications in understanding human evolution and identifying genetic factors in diseases. Her group has made significant contributions to studying Greenlandic populations and their unique genetic architecture. She has developed several widely used software packages including NgsRelate, localNgsRelate, and RelateAdmix for analyzing relatedness from low-coverage sequencing data. Her recent publications span diverse topics from human population history to conservation genomics of endangered species. Notable work includes studies on genetic architecture in Greenlandic populations, analysis of the saola genome, and research on diabetes genetics. Her research has been published in high-impact journals including Nature, Cell, and Nature Communications. Carlsberg Foundation Young Researcher Fellowship (2021-2025) ERC Starting Grant (2019-2023) Villum Young Investigator Award (2019-2024) L'Oréal-UNESCO For Women in Science Award (2016) SSSD Young Investigators Award (2015) Sapere Aude: DFF Young Elite Researcher Award (2012) Dr. Moltke actively mentors students, with her PhD student Frederik winning multiple awards including the Charles J. Epstein Award. She serves on PhD committees at multiple institutions and has organized numerous scientific meetings including EMBO conferences. Her group has developed multiple bioinformatics tools that are widely used in the field for analyzing relatedness from low-coverage sequencing data.
Professor Matthias Mann is Research Director and Group leader at the Proteomics Program at Novo Nordisk Foundation Center for Protein Research (CPR) at the University of Copenhagen's Faculty of Health and Medical Sciences. He also holds a Director position at the Max-Planck Institute of Biochemistry in Munich. As one of the most highly cited researchers in the world with h-index 216 and over 200,000 citations, Mann is a pioneer of mass spectrometry-based proteomics who has made landmark contributions to the development of electrospray ionization. Professor Mann's research interests focus on proteomics technology development and its application to biological and clinical problems. His Clinical Proteomics group applies mass spectrometry-based proteomics to understand human health and disease, with the goal of improving patient diagnosis, stratification, and prevention of diseases such as metabolic disorders and cancer. The group has established robust, high-throughput proteome profiling pipelines for clinical cohorts and develops AI-guided platforms for analyzing proteomes from low amounts of formalin-fixed, paraffin-embedded samples. A key research area is the interpretation of multi-omics data through the Clinical Knowledge Graph, which harmonizes multi-omics data with meta-data for machine learning applications. Professor Mann's recent publications demonstrate trends across several fields including clinical proteomics, biomarker discovery, mass spectrometry technology development, and multi-omics integration. His work spans applications in cancer research, metabolic diseases, neuroscience, and cardiac biology, with a consistent focus on translating proteomic technologies into clinical applications for personalized medicine. Dr H.P. Heineken Prize for Biochemistry and Biophysics 2024 Louis-Jeantet Foundation Prize for Medicine (2012) Leibniz Prize of the German Research Society (2012) Körber European Science Award (2012) Ernst Schering Prize (2012) Protein Society Anfinsen Award (2005) Novo Nordisk Prize (2004) Professor Mann has mentored numerous researchers, with several former post-docs receiving prestigious ERC Starting Grants. His research has been supported by significant funding from the Novo Nordisk Foundation and other major research organizations. The Mann Group maintains collaborations with clinical researchers across multiple institutions to apply proteomics to patient cohorts and disease studies. The Mann Group operates within the Novo Nordisk Foundation Center for Protein Research at the University of Copenhagen, working closely with other research groups including the Choudhary Group, Olsen Group, and others within the CPR. The group maintains state-of-the-art mass spectrometry facilities and develops computational tools for proteomic data analysis, creating an integrated environment for technological innovation and biological discovery.
Amelie Stein is an Associate Professor at the Department of Biology, University of Copenhagen, specializing in Bioinformatics and RNA Biology. Her research focuses on protein stability, molecular mechanisms of disease variants, and computational methods for protein design. She is affiliated with the UCPH Quantum Hub, reflecting interdisciplinary interests in biological systems. Her work integrates bioinformatics tools, mutational scanning, and structural biology to understand protein degradation pathways and their relevance to human diseases such as Lynch syndrome and metabolic disorders. Key research areas include analyzing protein variants using deep learning models (e.g., SSEmb), developing web-based tools like MutationExplorer for 3D visualization, and characterizing disease-linked mutations in proteins such as Parkin and MLH1. Her publications highlight breakthroughs in rapid protein stability predictions, degon mapping, and the interplay between protein toxicity and degradation. No scientific awards are explicitly mentioned in the provided texts. Stein’s research also explores the application of computational approaches to biotechnology and therapeutic development, emphasizing translational applications of her findings. Her lab, linked to the SCARB research group (https://www1.bio.ku.dk/english/research/scarb/), focuses on structural and computational biology, with ongoing projects involving protein quality control networks and enzyme variant analysis. Collaborations span molecular biology, bioinformatics, and interdisciplinary quantum-related research through her UCPH Quantum Hub membership.
Rasmus Nielsen is a Professor at the University of Copenhagen, specifically affiliated with the Globe Institute and the Section for Geogenetics. His research spans evolutionary genetics, population genetics, and computational genomics with a focus on both human and non-human species. He maintains an active research profile with numerous high-impact publications in leading scientific journals. Professor Nielsen's research interests center around evolutionary and population genetics, with particular expertise in ancient DNA analysis, statistical methods for genomic data, and phylogenetics. His work bridges computational biology with empirical data from diverse species, including humans, plants, and other organisms. He has made significant contributions to understanding human evolutionary history, population structure, and the genetic basis of adaptation. His research also extends to medical genomics, particularly in understanding the genetic architecture of complex traits and diseases. His recent publications demonstrate a strong focus on methodological development in genomic analysis, with papers appearing in top-tier journals like Nature , Science , and Nature Reviews Genetics . His work shows consistent engagement with both theoretical and applied aspects of genetics, spanning human evolutionary history, medical genomics, and plant evolutionary biology. The research output reveals a collaborative approach, with frequent co-authorship across multiple institutions and disciplines. As a Professor at the University of Copenhagen's Globe Institute, Nielsen leads research within the Section for Geogenetics, which focuses on evolutionary and population genetics using cutting-edge genomic approaches. The section maintains strong connections with both computational and empirical research groups, facilitating interdisciplinary work that spans from methodological development to application in diverse biological contexts.
Professor Simon Holst Bekker-Jensen is affiliated with the University of Copenhagen , specifically the Faculty of Health and Medical Sciences and the Department of Cellular and Molecular Medicine . He leads research at the Molecular Aging Program Damage and Repair Center for Healthy Aging , focusing on stress signaling pathways in cellular biology. Academic Rank: Professor Department: Cellular and Molecular Medicine Research Center: Molecular Aging Program Damage and Repair Center for Healthy Aging His research investigates MAP kinase activation mechanisms under stress , novel stress signaling pathways , and the role of cellular stress responses in cancer . Using siRNA screens , proteomics , and biochemical techniques , he explores RNA-binding proteins and post-transcriptional regulation in stress and inflammation. Current projects target ZAKα kinase and NLRP1 inflammasome dynamics, with potential therapeutic applications in cancer and inflammatory disorders. Collaborations span international institutions, with recent external partnerships in multiple countries. He serves as a consultant for KinxeaTherapeutics , developing kinase inhibitors for clinical trials.
Sarah Frances Homewood is an Assistant Professor (Tenure Track) in the Department of Computer Science at the University of Copenhagen, affiliated with the Human-Centred Computing research section. Her research focuses on the intersection of human-computer interaction and artificial intelligence, with applications in healthcare, natural language processing, and interpretable machine learning. Her diverse research interests span Human-Computer Interaction, Machine Learning, Natural Language Processing, and Artificial Intelligence. Recent investigations include interpretability of large language models, clinical NLP applications, fairness in recommender systems, and quantum natural language processing. Analysis of her recent publications reveals strong emphasis on NLP interpretability techniques, healthcare applications of AI, and theoretical foundations of machine learning. Her work frequently bridges fundamental computer science with practical applications in medicine and human-centered systems. Emerging research directions include quantum NLP and protein sequence modeling. Dr. Homewood's research contributes to the Machine Learning Section's focus on both theoretical foundations and applied domains including medical data analysis and information retrieval.
Anders Albrechtsen is a Professor at the Bioinformatics Centre, Department of Biology, University of Copenhagen, specializing in computational and RNA biology. He leads research in statistical and computational methods for genomic data analysis with a focus on population genetics, particularly in isolated populations like the Greenlandic Inuit. Education: Natural Science Basic Education, Roskilde University Centre, Denmark (2000-2002) BSc in Molecular Biology, Roskilde University Centre, Denmark (2003) Mathematics, Roskilde University, Denmark (2002-2004) MSc in Bioinformatics, Copenhagen University, Denmark (2006) PhD from the Department of Biostatistics, Copenhagen University, Denmark (2009) Albrechtsen's research focuses on developing statistical and computational methods for genomic data analysis, with particular emphasis on multi-loci association studies, population structure analysis, and next-generation sequencing data. His work bridges computational methods development with applied population genetics, contributing significantly to understanding human and wildlife genomics. His research group develops open-source software available at www.popgen.dk/software. His recent publications demonstrate expertise across population genetics, genomic methods development, and medical applications, with numerous high-impact papers in journals like Nature, Cell, and Nature Communications. His work often involves large-scale genomic studies of human populations (particularly Greenlandic Inuit) and wildlife species, addressing questions related to population history, adaptation, and disease genetics. Scientific Recognition: Lundbeck Fellow (10M DKK, 2016-2021) Novo Ascending Investigator (10M DKK, 2021-) Villum Young Investigator Programme (2.3M DKK, 2011-2015) Albrechtsen actively supervises students and researchers, currently serving as main supervisor for 6 PhD students (with 8 completed), 2 postdocs, and 1 master's student (with 25 completed). He has secured significant research funding as PI and co-PI, including large collaborative grants like LuCamp (60M DKK) and the UCPH Excellence Programme (36M DKK). His research group maintains strong international collaborations, particularly with institutions in the United States. He serves as a journal reviewer for prestigious publications including Nature Genetics, Genome Research, and American Journal of Human Genetics, contributing to the scientific community through peer review and mentorship.
Kasper Harpsøe is a Research Consultant and Data and Computing Facility Manager at the Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen. He has extensive expertise in computational medicinal chemistry with over 15 years of experience in molecular modeling techniques, particularly focused on G Protein-Coupled Receptors (GPCRs). Harpsøe earned his Ph.D. in Computational Chemistry from The Danish University of Pharmaceutical Sciences in 2006 with research on "Computational Studies on the Allosteric Modulation of AMPA Receptors." He holds a Master of Science in Pharmacy (Cand. Pharm.) from The Royal Danish School of Pharmacy completed in 2001. His international experience includes a three-month traineeship at Schrödinger Inc. in New York and research collaboration with the Carlson group at the University of Michigan. His research expertise spans structure-based design of peptide and small molecule ligands, binding site identification, docking and binding pose evaluation, protein-ligand interactions, conformational analysis, QSAR, sequence analysis, homology modeling, molecular dynamics, and quantum chemistry calculations. Harpsøe has made significant contributions to understanding GPCR structure-function relationships, ligand recognition mechanisms, and G protein coupling specificity. Analysis of his publication record reveals a consistent focus on GPCR molecular pharmacology, with particular emphasis on serotonin receptors, orphan receptors like GPR139, and GABA receptors. His work integrates computational approaches with experimental validation to identify molecular determinants of receptor selectivity and to design novel ligands for therapeutic applications. The research bridges structural biology, molecular modeling, and medicinal chemistry in the context of drug discovery. Harpsøe currently manages the department's Data and Computing Facility, overseeing a GPU Linux cluster and providing computational support for research groups. Previously, from 2014 to 2021, he served as project manager for computational drug design activities within the Gloriam Group, working on multidisciplinary drug discovery projects in collaboration with medicinal chemists, molecular pharmacologists, structural biologists, and data scientists from both academia and industry.
