Klaus Mølmer is a Professor at the Niels Bohr Institute, University of Copenhagen, specializing in Quantum Optics and Photonics. His research spans quantum information, entanglement, and cavity QED, leveraging machine learning and Grover's algorithm for quantum state engineering. His recent work focuses on spin squeezing, Rydberg atom interactions, and mechanical resonator cooling. A leader in quantum simulation and superradiance, he collaborates on cavity-mediated emission and quantum network design. The 15 most recent articles highlight advancements in quantum state manipulation, entanglement protocols, and robust differential phase sensing. These studies bridge theoretical frameworks with experimental applications in cavity QED, Rydberg arrays, and zero-photon detection.
Torben Barington is a Clinical Professor at the Department of Clinical Research, Faculty of Health Sciences, University of Southern Denmark, and a Consultant at the Department of Clinical Immunology, Odense University Hospital. He has held this position since August 2001 and continues to be actively involved in research, teaching, and clinical leadership. MD, University of Copenhagen, 1987 Doctoral Thesis (dr.med.), University of Copenhagen, 1996 Specialist in Clinical Immunology, 1998 His research focuses on cellular immunotherapy of cancer , particularly using CAR T-cell and CAR NK-cell technologies, primary immunodeficiencies , and the B-lymphocyte repertoire and immunoglobulin genes . His work bridges fundamental immunology with clinical applications in oncology and immunodeficiency disorders. His recent publications (2024–2025) highlight advancements in CAR T/NK-cell characterization, cytotoxicity assays, clinical translation, and tumor microenvironment interactions. These works reflect a strong trend toward translational immunology , with emphasis on personalized cancer therapy , single-cell technologies , and clinical trial development . Scientific Awards: Aage og Edith Dyssegaards Fonds æreslegat (1993) Silver Medal, University of Copenhagen (1981) He has supervised over 30 thesis students and currently mentors several graduate students in CAR-based cancer immunotherapies. He serves as an examiner for PhD defenses at both the University of Southern Denmark and the University of Copenhagen. He is also actively involved in national scientific leadership, including as Chairman of the Scientific Committee of the Danish Blood Donor Organization since 2011 and as a member of the Advisory Board for Clinical Immunology in the Region of Southern Denmark since 2007. His research is conducted in collaboration with multidisciplinary teams focusing on cellular immunotherapy , clinical immunology , and translational hematology , often in partnership with Odense University Hospital and national blood and immunology networks.
Diego Garlaschelli is Professor of Theoretical Physics at the IMT School for Advanced Studies in Lucca, Italy, and at the Lorentz Institute for Theoretical Physics, University of Leiden, the Netherlands. He leads the NETWORKS research unit at IMT and the Econophysics and Network Theory group at Leiden. He is also an external faculty member at the Complexity Science Hub in Vienna and an associate member of the Enrico Fermi Research Center in Rome. His affiliations reflect a strong international and interdisciplinary research profile in network science and statistical physics. He holds a master's degree in theoretical physics from the University of Rome III (2001) and a PhD in Physics from the University of Siena (2005). His postdoctoral experience includes positions at the Australian National University, the University of Siena, the University of Oxford, and the Sant’Anna School of Advanced Studies in Pisa. Garlaschelli’s research spans network theory, statistical physics, econophysics, financial complexity, ecological networks, and social dynamics. He applies maximum entropy models, information theory, and random graph frameworks to understand complex real-world systems. His teaching includes courses in Network Theory, Econophysics, and Complex Systems at both PhD and MSc levels. The 15 most recent publications highlight a consistent focus on network reconstruction, ensemble inequivalence, renormalization, and applications to financial and socio-economic systems. Key themes include statistical inference in networks, resilience, and multi-scale modeling, with publications in top journals such as Nature Reviews Physics , Physics Reports , Science , and Physical Review Letters . His scientific awards include the Best Paper Award at the 6th International Workshop on Self-Organizing Systems (2012) and the Jan Kijne Prize (2013) as supervisor. He has secured multiple grants from NWO, the European Union, and the Royal Society, and has supervised over 40 students at PhD, master’s, and bachelor’s levels. He also mentors postdocs and visiting scientists. Garlaschelli leads and organizes major international workshops and schools in network science and complex systems. He serves on scientific committees and is an active referee for journals like Nature and Physical Review Letters , as well as funding agencies including the ERC and NWO.
Per Christian Hansen is a Professor at the Department of Applied Mathematics and Computer Science (DTU Compute), Technical University of Denmark (DTU), where he leads the Section for Scientific Computing. He is a VILLUM Investigator and heads the CUQI (Computational Uncertainty Quantification for Inverse Problems) research initiative, aiming to develop accessible computational platforms for uncertainty quantification in inverse problems. His expertise lies in numerical analysis, numerical linear algebra, iterative reconstruction methods, and computational inverse problems, with applications in tomography, signal analysis, and plasma physics. His research integrates theoretical analysis—such as perturbation and convergence analysis—with the development of robust, adaptive, and efficient computational methods. He has co-authored five books, over 100 scientific papers, and several widely used MATLAB software packages, including IR Tools and Regularization Tools. His recent work (2023–2025) emphasizes uncertainty quantification, Bayesian inversion, and high-dimensional tomography in fusion plasmas, reflecting a strong trend toward probabilistic and robust modeling in inverse problems. He is a SIAM Fellow (2015) for his contributions to computational methods for rank-deficient and discrete ill-posed problems and regularization techniques. His scientific leadership is evident in both theoretical advances and practical software implementations. He actively collaborates across disciplines, particularly in nuclear fusion and medical imaging, and continues to supervise PhD students and publish in top-tier journals such as Inverse Problems , SIAM Journal on Scientific Computing , and Nuclear Fusion . SIAM Fellow (2015) VILLUM Investigator He advises PhD and Master’s students in computational mathematics and inverse problems, and his research is supported by major grants, including the VILLUM Investigator award. He leads the CUQI team, which develops open-source tools for non-experts to apply uncertainty quantification in inverse problems. His lab focuses on creating modeling frameworks that bridge theory, computation, and real-world applications in materials science, imaging, and plasma diagnostics.
Konstantinos Kalogeropoulos is an Assistant Professor at the Department of Biotechnology and Biomedicine, Technical University of Denmark (DTU), leading research at the Cell Diversity Lab. His work bridges proteomics, computational biology, and snake venom research. Current projects: "The Proteomic Landscape during Influenza Infection" (2022-2025) Supervisor for PhD projects on protease network rewiring in psoriasis and wound exudate degradomics Research interests include: Proteomic analysis of inflammatory diseases Snake venom toxin structure prediction Extracellular matrix biomechanics De novo peptide sequencing algorithms Computational modeling of protease networks Recent article trends demonstrate his work in • Database-free proteomics (InstaNovo/InstaNexus) • Snake venom pathophysiology (V-ToCs clustering) • Inflammatory disease biomarkers (psoriasis, impaired healing) • Extracellular matrix mechanics (fibronectin tension, gut inflammation) Advising: Supervises PhD students Polhaus, C. J. M. and Haack, A. M., focusing on protease networks and wound healing.
Maxim Kontsevich is a permanent professor at the Institut des Hautes Études Scientifiques (IHÉS), holding the AXA Chair for Mathematics since 1995 and a visiting chair at Rutgers University (one month annually since 1997). Born in 1964 in Khimki, USSR, he earned his PhD from Bonn University in 1992. His career includes visiting positions at Harvard, the Institute for Advanced Study, and Berkeley, where he was a professor from 1993 to 1995. His research spans mathematical physics, algebraic geometry, and non-commutative geometry. Notable contributions include deformation quantization, mirror symmetry, and motivic integration. His work bridges algebraic structures with geometric and physical concepts, influencing areas like topological field theories, string theory, and integrable systems. Awardees of Fields Medal (1998), Crafoord Prize (2008), and Breakthrough Prize (2014), he also holds editorial roles at Compositio Mathematica and Publications Mathématiques IHÉS. His over 50 publications explore advanced topics such as quantum cohomology, Hodge theory, and categorical structures in geometry.
Henrik Rasmus Andersen is a Professor at the Department of Environmental and Resource Engineering, Water Technology & Processes at the Technical University of Denmark (DTU). His research focuses on water treatment processes, particularly the occurrence, transformation, and removal of micropollutants like pharmaceuticals and hormones. Key Research Areas: Chemical analysis, bioassays, ozonation, biofilter optimization, by-product profiling, and advanced oxidation processes. Projects: Leads initiatives like BIZON (ozone technology for fish farms) and Sustainable Industrial Laundry Wastewater Treatment , emphasizing sustainable solutions. Collaborations: Works with institutions such as University of Copenhagen and industry partners on municipal and industrial wastewater challenges. Education: Master of Science in Environmental Chemistry from Copenhagen University (1998).
Erwin Schoof is an Associate Professor at the Department of Biotechnology and Biomedicine , Technical University of Denmark. He leads the Cell Diversity Lab and focuses on advancing proteomics and mass spectrometry technologies. Expertise in single-cell proteomics , stem cell niches , and bioinformatics . Active in myelofibrosis and leukemia research , with applications in UN Sustainable Development Goals . Research Trends from 2025–2024 include: Machine learning-driven peptide sequencing (InstaNovo, InstaNexus). Single-cell resolution tools for mapping hematopoietic stem cells and tumor microenvironments . Biomarker discovery in chronic diseases and respiratory conditions . Supervision : Mentors multiple PhD students on single-cell proteomics , omics data analysis , and biotherapeutic production . Labs & Collaborations : Collaborates with international teams on plasma proteomics , 3D bioengineering , and advanced mass spectrometry workflows .
Christian Igel is a Professor at the Department of Computer Science, University of Copenhagen, and serves as director of the SCIENCE AI Centre . He is also a co-lead of the Pioneer Centre for Artificial Intelligence in Denmark. His academic journey includes a Doctoral degree from Bielefeld University (2002) and a Habilitation degree from Ruhr-University Bochum (2010). Igel is a Juniorprofessor (2002–2010) and has held editorial roles at journals like KI - Künstliche Intelligenz and Artificial Intelligence Journal . Doctoral degree: Faculty of Technology, Bielefeld University, Germany (2002) Habilitation degree: Department of Electrical Engineering and Information Sciences, Ruhr-University Bochum, Germany (2010) His research spans Machine Learning , focusing on Support Vector Machines , Evolution Strategies , Reinforcement Learning , Deep Neural Networks , and PAC-Bayesian Analysis . He applies these methods to Environmental Monitoring , Medical Diagnostics , and Climate Research . Recent publications highlight work on adversarial machine learning , environmentally sustainable AI , and tree resource mapping using deep learning. His scientific awards include being a ELLIS Fellow . Igel’s software tools like Shark , woody , and Multi-Planar UNet are widely used in research and industry. Notable grants and collaborations involve projects with European Lab for Learning and Intelligent Systems (ELLIS) , SCIENCE AI Centre , and international teams in Denmark , Germany , and France . His lab leadership emphasizes open-source frameworks and reproducible research. Editorial Roles: German Journal on Artificial Intelligence , Evolutionary Computation Journal , Artificial Intelligence Journal Software Projects: Shark , woody , Multi-Planar UNet , U-Time Collaborations: SCIENCE AI Centre , Pioneer Centre for Artificial Intelligence , European Lab for Learning and Intelligent Systems
Niels Richard Hansen is a Professor at the Department of Mathematical Sciences , University of Copenhagen, leading research at the intersection of Artificial Intelligence and Statistics . He co-founded the Copenhagen Causality Lab and focuses on automating causal explanation discovery from data using Bayesian networks, stochastic processes, predictive models, and machine learning. His work emphasizes creating interpretable and robust AI systems capable of generalizing across domains. His research has produced over 56 publications spanning causal inference , graphical modeling , stochastic processes , and machine learning . Recent work includes: Predictive and causal learning (2018 keynote) High-dimensional regression solutions (2016 lecture) Interdisciplinary applications in actuarial science , environmental statistics , and neuroscience He actively contributes to scientific communication through media appearances and public explanations of statistical concepts, including analyses of: Gaussian correlation inequality proofs Daylight saving time and blood clots Mathematical approaches to lotteries Climate change vs lunar effects
Morten Søndergaard is an Associate Professor at Aalborg University’s Department of Communication and Psychology, affiliated with the Faculty of Social Sciences and Humanities. He is part of the Art, Aesthetics & Health Research Laboratory and the MASSHINE initiative. His research focuses on sound art, media art curation, and transdisciplinary practices, emphasizing the exclusion mechanisms in 20th-century art systems and unarchived avant-garde movements. Søndergaard has curated exhibitions globally, including at Kiasma and ZKM, and co-founded the POM conference series and ISACS symposia. He leads the Erasmus Master of Excellence in Media Arts Cultures, collaborating with institutions in Austria, Poland, and Hong Kong. His work bridges art, science, and technology, with recent projects exploring sonic archives and participatory curatorial frameworks. Key collaborations include roles with the European NeMe network, SUNY College New York, and the Momentum Biennial. He has organized over 20 projects since 2008, including the 2025 Momentum Biennial as head curator. His teaching spans media art theory, sound art practices, and curatorial methodologies at both bachelor and master levels. Søndergaard’s research outputs include over 145 publications, with a focus on sound art’s theoretical and practical dimensions. His current projects emphasize ‘uncurating’ methodologies and the reactivation of marginalized avant-garde practices. Notable activities include editorial roles, international conference organization, and advisory roles in art and science networks. His work has been featured in media outlets like Artdaily and the Biennial Foundation, highlighting his contributions to contemporary art discourse and curatorial innovation.
Philip Loldrup Fosbøl is an Associate Professor in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), College of Engineering. He is actively affiliated with CERE – Center for Energy Resources Engineering, where he conducts research on CO 2 capture, storage, transport, and utilization. His work integrates thermodynamic modeling, process simulation, and pilot-scale experimentation to address challenges in carbon management and sustainable energy systems. His research interests include: Carbon Dioxide Capture and Storage (CCS) Thermodynamics and Phase Equilibrium of Electrolyte Solutions Process Design, Simulation, and Optimization CO 2 Corrosion in Energy Systems Biogas Upgrading and Cleaning CO 2 Utilization and Conversion Development of Predictive Thermodynamic Models Mobile and Large-Scale Pilot Facilities for CO 2 Capture His recent publications (2025) highlight a strong focus on biogas upgrading, solvent degradation in industrial CO 2 capture, thermophysical property measurements, and novel electrochemical separation methods. These works reflect a consistent trend toward energy-efficient, scalable, and industrially applicable solutions for decarbonization, particularly in flue gas and biogas treatment. Scientific awards received: Top PhD Thesis of the Year (2008) He actively supervises multiple PhD students and leads research projects funded by industrial partners such as Ørsted, Shell, Equinor, and Novozymes, as well as EU initiatives including CASTOR, iCap, and OCTAVIUS. His work contributes to UN Sustainable Development Goals related to climate action and affordable, clean energy. He is involved in laboratory research on thermodynamic equilibrium (VLE, SLE), heat capacity, corrosion mechanisms, and core flooding for CO 2 storage. His team develops experimental methods and operates pilot facilities for CO 2 capture and biogas cleaning, often in collaboration with key researchers like Kaj Thomsen, Nicolas von Solms, and Georgios Kontogeorgis.
Philip Bille is a Professor and Head of the Algorithms, Logic and Graphs section at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), College of Engineering. His research centers on the design and analysis of efficient algorithms, particularly for string processing, compressed data, and data structures. His research interests lie at the intersection of theoretical computer science and practical applications. He focuses on algorithms , data structures , string indexing , pattern matching , and compressed computation . His work enables efficient querying and processing of large-scale, repetitive data, with applications in bioinformatics, intrusion detection, and green computing. The recent publications reflect a strong trend in developing space-efficient and fast algorithms for modern computational challenges. Key themes include compressed data structures , sliding window indexing , finite automata compression , and energy-aware matrix operations . These works demonstrate expertise in balancing theoretical rigor with practical performance. Philip Bille actively supervises multiple PhD students and leads several research projects. He contributes to advancing sustainable computing aligned with UN SDGs. His work integrates algorithmic theory with real-world efficiency. Supervises PhD projects on hierarchical compression, adaptive computation, and vector processor algorithms. Involved in research on green computing, compressed formats, and efficient data models. He is affiliated with the Algorithms, Logic and Graphs group at DTU, a hub for theoretical and applied algorithmic research. The team explores fundamental problems in data representation and processing, pushing the boundaries of what is computationally feasible in terms of time and space.
Niels Anne Jacob Obers is a Professor at the Niels Bohr Institute , University of Copenhagen, specializing in Theoretical High Energy, Astroparticle, and Gravitational Physics. He leads research in string theory, quantum field theory, and gravity, with a focus on non-relativistic gravity, holography, and higher-dimensional black holes. Education: PhD in Physics (1991) from the University of California, Berkeley, and earlier studies at Universiteit Nijmegen (cum laude Drs, 1987). His research spans AdS/CFT correspondence , black hole dynamics , non-perturbative string dualities , and non-Lorentzian geometries . He has published extensively on matrix theories, gravitational solitons, and the interplay between string theory and holography. Recent work explores non-relativistic string theory and its applications to gravity and thermodynamics. Scientific awards include a CERN-Fellowship . He teaches foundational and advanced courses such as General Relativity , Advanced Quantum Field Theory , and String Theory . Fluent in Dutch, English, and Danish, with proficiency in French and German.
Jan Engelhardt serves as Assistant Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specializing in e-mobility and prosumer integration within power and energy systems. His work directly contributes to UN Sustainable Development Goals through grid modernization and renewable energy integration. His research focuses on electric vehicle-grid integration , with core expertise in battery energy storage systems, DC microgrids, and virtual power plants. Key investigation areas include smart charging architectures for EV clusters, frequency response services, phase balancing techniques, and V2X management strategies. His experimental approach combines theoretical modeling with real-world validation of control systems for enhanced grid stability. Recent publications demonstrate a clear trend toward distributed control solutions for electric vehicle clusters, emphasizing user-centric scheduling while providing grid services. His work increasingly incorporates experimental validation of frequency control architectures and explores high-power reconfigurable battery applications for fast-charging infrastructure. Dr. Engelhardt actively supervises PhD candidates on projects including Hybrid Energy Solutions (EV charging and battery storage synergies) and Provision of Grid Services through EV Aggregation. He participates in major EU initiatives like EV4EU (Electric Vehicles Management for Carbon Neutrality in Europe) and GREAT (GRid Enhancement for Ancillaries in Tomorrow’s power systems), securing substantial research funding through Horizon Europe frameworks.
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