Anne Ljungars is a Senior Researcher at the Department of Biotechnology and Biomedicine, Technical University of Denmark , specializing in Antibody Technologies and Biologics Engineering . Her work focuses on advancing antivenom development, single-domain antibody engineering, and proteomics innovation. Expertise: Antivenom development, Phage display, Protein engineering, Toxin detection Key Projects: Supervising multiple PhD students in projects like AI-driven protein binder design and nanobody diagnostics Research trends are concentrated in snakebite envenoming , nanobody-based diagnostics , and computational proteomics . She contributes to UN Sustainable Development Goals via global health initiatives targeting neglected tropical diseases. Collaborations span immunology , toxicology , and biotechnology . Her recent publications emphasize single-domain antibodies , antibody-dependent enhancement , and high-throughput sequencing analysis .
Kristoffer Vitting-Seerup is an Associate Professor at the Department of Health Technology , Technical University of Denmark, specializing in Bioinformatics and Isoform Analysis . His research focuses on leveraging RNA sequencing, alternative splicing, and protein domain variants to advance cancer genomics and neuro-oncology. Current academic rank: Associate Professor Key collaborations: DTU, University of Copenhagen, international cancer research teams Supervisory role: 5 PhD students in projects spanning machine learning for single-cell sequencing and isoform-level systems biology His work demonstrates strong emphasis on transcriptomics in glioblastoma, with recent publications analyzing tumor infiltration, neurodevelopmental pathways, and therapy resistance mechanisms. Articles reveal expertise in alternative splicing's role in biological signaling, protein domain functional diversity, and genomic stability in cancer stem cells. Research tools developed include satuRn for transcript usage analysis and IsoformSwitchAnalyzeR for splicing variant characterization. Current projects aim to improve clinical diagnostics through machine learning frameworks and enhance understanding of isoform-level biology in diseases. Advising: Rasmussen, M. N. (PhD Student, 2025-2028) Zhen, Z. T. (PhD Student, 2024-2027) Hsieh, C.-Y. (PhD Student, 2024-2027) Kanakoglou, D. S. (PhD Student, 2023-2026) Dam, S. H. (PhD Student, 2021-2025)
Lasse Ebdrup Pedersen is a Senior Researcher in the Biotherapeutic Glycoengineering and Immunology group at the Department of Biotechnology and Biomedicine, Technical University of Denmark. His research focuses on antibody engineering, CRISPR/Cas9 applications in cell line development, and glycoengineering for biotherapeutics. He actively supervises multiple PhD students in projects related to bispecific antibodies, stem cell-derived NK cell manufacturing, and machine learning applications in biotechnology. Accepting PhD students Active in multiple collaborative projects Expert in antibody engineering and cell line optimization His research interests span biotechnology, immunology, and genetic engineering with specific emphasis on CRISPR activation screening, antibody development, and computational analysis of binding interfaces. Recent publications highlight advancements in CHO cell engineering, phage display data mining, and bispecific antibody design. Scientific activities include participation in conferences like GlycoBioTec 2019 and Danish Conference on Biotechnology . Current projects focus on scalable manufacturing of iPSC-derived NK cells and Raman spectroscopy with machine learning models.
Janine Erler is a Professor and Group Leader at the Biotech Research and Innovation Center (BRIC) , University of Copenhagen. She has held academic positions at the Institute of Cancer Research (London) and Stanford University , where she established her expertise in hypoxia-regulated cancer biology and metastasis . Education : PhD in Molecular Pharmacology (University of Manchester, 2003) BSc (Hons) in Molecular Genetics (University of Sussex, 2000) European Baccalaureate (The European School, 1996) Her research focuses on cancer biology and translational research , particularly mechanisms of metastasis , hypoxia-induced drug resistance , and extracellular matrix (ECM) remodeling . Recent work explores ECM stiffness , LOX enzyme function , and fibroblast-cancer cell interactions in metastatic progression. Key publications include studies on lysyl oxidase in cholangiocarcinoma, angiocrine signaling in cancer targeting, and machine learning analysis of ECM patterns. Her work frequently intersects computational biology , cancer metabolism , and stromal remodeling . Scientific awards : BACR Translational Research Award (2009) BACR/AstraZeneca Young Scientist Frank Rose Award (2012) Novo Nordisk Hallas Møller Stipendum (2012) - first woman to receive this award
Michael Lisby is a Professor in Genome Integrity at the Department of Biology , University of Copenhagen , and leads research in Functional Genomics . His work focuses on homologous recombination (HR) and its role in genome stability , with applications in cancer genetics , neurological disorders , and cellular aging . PhD in Science (2000) from Aarhus University , studying topoisomerase mechanisms Postdoctoral Fellowship at Columbia University (2000-2004) His research combines cell biological and genetic methods to analyze HR regulation via post-translational modifications and chromatin structure , while also developing genetic libraries for biopharmaceutical applications . Recent work includes computational modeling of excitable media in yeast, DNA repair in mitosis , and protein stability in metabolic diseases . Scientific Awards : European Research Council Starting Grant (2009) NNF Distinguished Investigator Grant (2019-2024) Carlsberg Foundation Semper Arden Grant (2023-2028) He has held managerial roles as Vice-head of Department for Research (2015-present) and Head of Section for Functional Genomics (2010-2015).
Henrik Vorum is a Clinical Professor at the Department of Clinical Medicine, Aalborg University , and a senior physician at Aalborg University Hospital 's Eye Department. He serves as Deputy Head of Department for Research and maintains a dual appointment in clinical practice and academic research. 1994: MD from Aarhus University 1999: Dr.med. degree on ligand binding to serum albumin 2006: Specialist certification in ophthalmology His research focuses on molecular mechanisms and biomarker discovery in retinal diseases, including diabetic retinopathy , AMD , and glaucoma . He pioneered the first translational pig model for retinal occlusions, enabling preclinical treatment testing. Recent publications (2025) emphasize chemokine signaling in AMD , AI applications for diabetic retinopathy screening, and proteomic biomarkers for personalized risk stratification. His work spans proteomics, molecular biology, and clinical cohort studies. Bagger-Sørensen Research Prize (2012) Synoptik Foundation Research Prize (2022) Knight's Cross of the Order of the Dannebrog (2022) Vorum supervises PhD students and leads interdisciplinary consortia including immunologists and clinicians. His research environment at Aalborg University integrates clinical proteomics with high-tech translational approaches.
Professor Yonglun Luo is a leading academic at Aarhus University, affiliated with DANDRITE and the Department of Biomedicine. His research focuses on genome editing technologies (e.g., CRISPR), regenerative medicine, and translational applications such as xenotransplantation. Key projects include developing safer pig models for organ transplantation and studying extrachromosomal circular DNA (eccDNA) in cancer progression. He leads a multidisciplinary group applying cutting-edge tools like single-cell RNA/ATAC sequencing and machine learning. Research interests span biomarker discovery, CRISPR tool optimization, and ethical frameworks for gene therapy. He collaborates internationally on initiatives like the FarmGTEx consortium and the EU COST Action on genome editing. Teaching responsibilities include advanced courses in genome engineering for PhD students and personalized medicine for medical trainees. Current projects include EXOCURE (CRISPR-based muscle stem cell therapy for Duchenne muscular dystrophy) and CIRCULAR VISION (eccDNA dynamics modeling). His lab's innovations include TRAP-seq for CRISPR off-target analysis and pig cell landscape mapping for xenotransplantation compatibility.
Gitte Hoffmann Bruun is a researcher at the Department of Biochemistry and Molecular Biology, University of Southern Denmark, specializing in translational biology. Her work bridges genetic research and molecular medicine, focusing on RNA splicing mechanisms and genetic susceptibility to diseases. Research Interests: Biochemistry, Genetics, Molecular Biology, RNA Splicing, Exome Sequencing, and Genetic Susceptibility. Bruun's research leverages advanced bioinformatics and molecular biology techniques, such as deep learning models for predicting protein-RNA binding effects and exome sequencing to identify disease-related genes. Her work has applications in developing allele-specific therapies and antisense oligonucleotide-based treatments. Her publications and patents highlight a strong emphasis on splice switching oligonucleotides, pseudoexon targeting, and Mycobacterial infection genetics. These contributions underscore her role in translational research linking computational biology to clinical applications.
Jakob Lorentzen serves as a Clinical Professor in the Department of Neuroscience within the Faculty of Health and Medical Sciences at the University of Copenhagen. His research focuses on motor control disorders, neurorehabilitation techniques, and neurophysiological mechanisms in neurological conditions. His primary research interests include motor control , cerebral palsy pathophysiology , spasticity assessment , and wearable sensor technology for movement analysis. Current work explores neural mechanisms of muscle fatigue, contracture development in cerebral palsy, and pharmacological interventions targeting spinal reflex pathways. Recent publications demonstrate strong emphasis on quantitative neurophysiological assessment and technology-driven rehabilitation approaches , with significant contributions to understanding movement disorders through biomechanical and electrophysiological methodologies. His work frequently appears in high-impact journals including Clinical Neurophysiology and Journal of Neurophysiology . Collaborative research spans multiple international institutions, with documented external collaborations across various countries as indicated by network analysis of his publication record.
Christophe Biscio is an Associate Professor in the Department of Mathematical Sciences at Aalborg University's Faculty of Engineering and Science. His research focuses on spatial statistics, point processes, and topological data analysis, with applications in materials science and engineering. He leads interdisciplinary projects like 'Deciphering Nanoporosity of Amorphous Materials using Topological Data Analysis,' exploring medium-range order structures in glasses and metal-organic frameworks. Key research interests include statistical learning for point processes, functional central limit theorems, and adversarial machine learning. His work bridges theoretical mathematics with practical challenges in wireless communication, radar sensing, and urban system modeling. Collaborations span materials scientists, computer scientists, and data analysts. Biscio has advised one PhD student and contributed to datasets on topological summaries for spatial processes. He actively organizes conferences on data science and participates in public outreach events like Earth Day climate change discussions.
Deming Kong is a Researcher at the Department of Electrical and Photonics Engineering, Technical University of Denmark (DTU), affiliated with the Photonic Integrated Circuit based Systems Centre of Excellence for Silicon Photonics for Optical Communications. His research spans optical communications, silicon photonics, and optical signal processing, with expertise in photonic integrated circuits for optical neural networks and wireless communication systems. Key focus areas include optical matrix multiplication processors, digital precoding for multi-mode fiber transmission, nonlinear channel equalization using silicon microring modulators, and ultrafast terahertz wireless communication leveraging Kerr frequency combs. Recent publications (2024-2025) demonstrate significant contributions to optical computing hardware for neural networks and advanced optical communication techniques, integrating silicon photonics with machine learning and communication theory to address challenges in high-speed data transmission and neural network acceleration. Dr. Kong actively supervises PhD research at DTU, including: Digital Optical Computing Platform for Neutral Networks (2024-2027) Silicon Photonics for Optical Neural Networks (2024-2027) Silicon Photonic Integrated Circuits for Optical Processing aided Artificial Intelligence (2019-2023) These projects focus on optical neural networks and silicon photonics for AI applications. He operates within DTU's Photonic Integrated Circuit based Systems Centre of Excellence, a leading hub for silicon photonics research targeting optical communications and neural network hardware acceleration.
Henrik Nielsen is an Associate Professor at the Department of Bioinformatics, Technical University of Denmark, specializing in protein sorting prediction and signal peptide analysis. His research leverages deep learning and protein language models to advance subcellular localization and secretion pathway studies. Department of Bioinformatics, DTU Focus on signal peptides, protein targeting, and computational methods His recent work includes SignalP 6.0 , DeepLoc 2.1 , and SpanSeq , highlighting the integration of protein language models for multi-label localization prediction and sequence data splitting. Collaborations span projects in pathogenic eukaryotes, vaccine development, and structural bioinformatics. Notable contributions include: Development of SignalP: a cornerstone tool for signal peptide cleavage prediction Creation of DeepLoc for membrane protein type classification Advancing SpanSeq to optimize deep learning model assessment He has supervised PhD candidates in protein sorting, bioinformatics, and sequence analysis, with a focus on improving vaccine design and pathogen characterization through computational approaches.
David Andres Figueroa Salvador is a Postdoctoral Researcher at the Department of Materials and Production, Faculty of Engineering and Science, Aalborg University, Denmark. His work centers on human-robot interaction and machine learning applications in real-world contexts, especially for elderly care and healthcare technology. He earned his PhD from Osaka University, specializing in human-robot interaction. His educational background provides a strong foundation for his current research in socially assistive robotics. Dr. Figueroa's research interests span Human-Robot Interaction, Machine Learning, Artificial Intelligence, Social Robotics, Healthcare Robotics, and Elderly Care Technology. He investigates how technology can seamlessly integrate into daily life, with a focus on older adults facing cognitive decline, social isolation, and loneliness. His goal is to develop robotic systems that offer emotional support and combat cognitive deterioration through sustained, meaningful interactions. His recent publications (2021-2025) demonstrate a consistent focus on social robotics for elderly care, particularly targeting mild cognitive impairment and social isolation. His work ranges from fundamental machine learning algorithms to practical healthcare applications, including hand hygiene monitoring and conversational AI with character-inspired voices. This interdisciplinary research bridges computer science, psychology, and gerontology. No scientific awards were listed in the available information. Dr. Figueroa serves as a project participant in the Villum Foundation-funded 'Time-Traveling Conversations' project (2024-2026), which explores robots imitating historical figures' speaking styles. While no formal advisees are mentioned, his collaborative publications indicate active teamwork with researchers in Japan and Denmark. He conducts research within Aalborg University's Production Robotics and Automation group, collaborating with an international network of researchers as seen in his publications with institutions in Japan.
Veit Schwämmle is an Associate Professor in Computational Proteomics and Bioinformatics at the Department of Biochemistry and Molecular Biology, University of Southern Denmark (SDU), where he leads the Computational Proteomics Group. His research focuses on developing computational solutions for large-scale omics data analysis, particularly in proteomics and post-translational modifications. PhD in Physics, University of Stuttgart (2006) Postdoctoral Fellowships: Centro de Pesquisas Fisicas (Rio de Janeiro), ETH Zürich Postdoctoral Researcher and Assistant Professor, University of Southern Denmark Research interests include software and workflow development for protein mass spectrometry data analysis, chromatin biology through histone modifications, tools for omics data quantification and interpretation, and the application of deep learning methods to improve proteomics data processing. His work bridges physics-based modeling and biological data science, with a strong emphasis on open, reproducible research. His recent publications highlight trends in machine learning for proteomics, benchmarking of analysis workflows, and community-driven bioinformatics standards. He is actively involved in international initiatives like EuBIC-MS and bio.tools, promoting software interoperability and training. Member of the European Bioinformatics Community for Mass Spectrometry (EuBIC-MS) Contributor to the bio.tools registry for life sciences software Advocate for open science and reproducible workflows He supervises researchers and students in computational proteomics and has contributed to numerous collaborative projects in systems biology and biomedical mass spectrometry. His group develops tools such as VIQoR, CrossTalkMapper, and MetaboLink, supporting the broader scientific community. Visit the group’s webpage: http://computproteomics.bmb.sdu.dk
Axel Thielscher is a Magnetic Resonance Professor and Head of Section at the Department of Health Technology Magnetic Resonance Neurophysics, Technical University of Denmark (DTU). His research focuses on neuroimaging, non-invasive brain stimulation, and computational modeling of electric fields in the brain. He leads projects on transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), and tumor treating fields (TTFields). His work integrates clinical applications with advanced MRI techniques and computational simulations. Research interests include electric field modeling for brain stimulation, neuroimaging methodology, and translational neuroscience. He collaborates internationally on guidelines for concurrent TMS-fMRI and clinical trials of neurostimulation therapies. His lab develops open-source tools like SimNIBS for electric field simulations and MRI-based dosimetry. Recent articles emphasize optimizing TMS coil positioning, validating electric field simulations, and exploring neural mechanisms underlying stimulation effects. He advises multiple PhD students and has contributed to over 155 publications, including work on magnetic resonance current density imaging and personalized head modeling.
