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Ole Winther is Professor in High dimensional biological data analysis/Machine learning at the Department of Biology, University of Copenhagen and Professor in Data science and complexity at DTU Compute, Technical University of Denmark. He serves as CRO and co-founder of raffle.ai, CTO and co-founder of FindZebra, Head of ELLIS Unit Copenhagen, and co-PI of the Machine Learning for Life Science Center. His research spans Bioinformatics , Machine Learning , and AI for Science , focusing on applying deep learning to biological sequence analysis, latent variable models, and medical NLP. Winther's work develops predictive and generative models for bioinformatics, with significant contributions to protein localization tools (SignalP, DeepLoc, DeepTMHMM), single-cell genomics, and novel deep learning architectures like variational autoencoders and diffusion models. Analysis of Winther's recent publications (2023-2025) reveals a strong trend toward integrating protein language models with traditional bioinformatics approaches and applying diffusion models to scientific problems. His work bridges theoretical machine learning advancements with practical applications in biology and medicine, particularly in protein sequence analysis, medical search engines, and scientific simulation acceleration. Winther currently supervises a diverse research group including Panagiotis Antoniadis, Rachael M. DeVries, Jun Wang, Beatrix M. G. Nielsen, Felix G. Teufel, Irene R. Rodriguez, Anders Christensen, and Christopher Heje Grønbech. His former students have established successful careers at institutions including Google, Apple, and various startups, with notable alumni like Casper Sønderby (Google Brain) and Søren Sønderby (Apple). He leads significant research initiatives including the ELLIS Unit Copenhagen and the Machine Learning for Life Science Center, while maintaining active industry partnerships through his co-founded companies raffle.ai (enterprise search using NLP) and FindZebra (search engine for rare diseases). His teaching includes Deep Learning courses at both DTU (02456) and University of Copenhagen (NDAK24002U).

• Bioinformatics
• Machine Learning
• Deep Learning
• +5 more

Professor Ulrik Lund Andersen heads the quantum information group at DTU Physics, Technical University of Denmark. His research develops quantum technologies including quantum computation, secure communication, and quantum-enhanced measurement systems. His group generates entangled optical states and investigates diamond-photon interactions for quantum nonlinearities. Key research areas: Quantum computing architectures Continuous-variable quantum information Quantum key distribution Quantum-enhanced sensing Solid-state quantum systems Recent work advances error correction, quantum state engineering, and quantum sensing algorithms. Publications demonstrate consistent focus on practical quantum technology implementation. Awards include multiple Sapere Aude research grants and the Eliteforsk Award from the Danish Ministry of Science.

• Quantum Information
• Quantum Optics
• Quantum Communication
• +3 more

Seth Lloyd is a Professor of Mechanical Engineering at the Massachusetts Institute of Technology (MIT), where he directs the Center for Extreme Quantum Information Theory (xQIT). His work bridges theoretical physics, quantum information science, and complex systems theory. He has made significant contributions to the foundations of quantum computing and quantum information processing. Lloyd received his education from prestigious institutions: B.A. from Harvard College (1982) M.Phil from Cambridge University (1984) as a Marshall Scholar Ph.D. in Physics from Rockefeller University (1988) Lloyd's research focuses on quantum information science, particularly quantum computation and quantum communications. He has pioneered work in quantum analog computation, quantum error correction, and quantum metrology. His research explores how quantum mechanics can be harnessed for information processing tasks, with applications ranging from quantum computing to understanding biological processes like photosynthesis. Lloyd is also known for his work on complex systems and the relationship between information and physical systems, arguing that the universe itself can be viewed as a quantum computer. His publication record shows a clear progression from foundational quantum computing work to applications in quantum machine learning and quantum biology. The most recent articles reveal a strong focus on quantum algorithms for machine learning, quantum metrology, and the intersection of quantum mechanics with biological systems. His work on the HHL algorithm for solving linear systems has been particularly influential in quantum machine learning, though its practical advantages have been debated following Ewin Tang's classical algorithms. Lloyd has received numerous scientific honors: Lindbergh Fellow (1994) Finmeccanica Professorship (1996) Edgerton Prize (2001) Fellow of the American Physical Society (2007) Quantum Communication Award (2012) International Quantum Communication Award (2012) Throughout his career, Lloyd has mentored numerous students and researchers in quantum information science. He has secured significant research funding for his work in quantum computing and complex systems. His research has been supported by various foundations and government agencies interested in advancing quantum technologies. Lloyd has also been involved in interdisciplinary collaborations, particularly with biologists studying quantum effects in photosynthesis. Lloyd directs the Center for Extreme Quantum Information Theory (xQIT) at MIT, which brings together researchers from physics, computer science, and engineering to tackle fundamental challenges in quantum information processing. His lab has been at the forefront of developing theoretical frameworks for quantum computing and exploring practical implementations of quantum information protocols.

• Quantum Information Science
• Quantum Computation
• Quantum Communications
• +5 more

Emil Bjerrum-Bohr is an Associate Professor at the Niels Bohr Institute, University of Copenhagen, where he holds a position in the Theoretical high energy, astroparticle and gravitational physics department within the Faculty of Science. He is also affiliated with the Niels Bohr International Academy and leads the Computations of Amplitudes Group as a Lundbeck Foundation Junior Group Leader. Dr. Bjerrum-Bohr's research focuses on theoretical particle physics with particular emphasis on amplitude analysis and computations. His primary fields of research include amplitude analysis and computations, amplitudes and string theory, and quantum gravity. His current research explores relations between amplitudes from string theory and computation of amplitudes in Quantum Chromodynamics (QCD) for use at the Large Hadron Collider (LHC) at CERN. He has made significant contributions to understanding scattering equations and effective field theory in the context of gravitational physics. His recent publication record demonstrates a strong focus on gravitational scattering amplitudes, quantum gravity, and connections between string theory and particle physics. A notable trend in his research is the application of amplitude techniques to gravitational physics, particularly in the post-Minkowskian expansion framework which has implications for gravitational wave astronomy and black hole physics. His work bridges theoretical concepts with practical applications for collider physics. Scientific awards: Lundbeck Foundation Junior Group Leader As a Lundbeck Foundation Junior Group Leader, Dr. Bjerrum-Bohr oversees the Computations of Amplitudes Group, where he mentors junior researchers and collaborates with international colleagues on cutting-edge theoretical physics problems. His research has involved organizing academic meetings including the "Current Themes in High-Energy Physics and Cosmology" series (2013-2015) and Nordic Winter Schools on Cosmology and Particle Physics (2013, 2015). His work is conducted within the vibrant theoretical physics environment of the Niels Bohr Institute, which provides access to computational resources and collaborative opportunities with both experimental and theoretical physicists across multiple disciplines.

• Amplitude analysis and computations
• Amplitudes and String theory
• Quantum gravity
• +4 more

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.

• Quantum Optics
• Photonics
• Quantum Information Science
• +7 more

Timo Minssen is Professor of Law at the University of Copenhagen (UCPH) and the Founding Director of UCPH's Center for Advanced Studies in Bioscience Innovation Law (CeBIL). He also holds affiliations as an LML Research Affiliate at the University of Cambridge and an Inter-CeBIL Research Affiliate at Harvard Law School's Petrie-Flom Centre. With extensive expertise in Intellectual Property, Competition, and Regulatory Law, Minssen focuses on the legal aspects of emerging health and life science technologies, including genome editing, big data, artificial intelligence, and quantum technology. His educational background includes a German law degree (Staatsexamen) from Georg-August-University in Göttingen, and Swedish biotech & IPR related LL.M., LL.Lic., and LL.D. degrees from Lund University and Uppsala University. His PhD thesis on the patentability of biopharmaceutical technology in the US & Europe received the prestigious Swedish King Oscar award. 2024: TUM Global Visiting Professor, Technical University of Munich (Germany) 2016: Visiting Research Fellow, University of Cambridge (UK) 2014: Visiting Research Fellow, University of Oxford (UK) 2013-14: Visiting Scholar, Harvard Law School (US) 2012: LL.D. - Doctor of Laws (Swedish "juris doktor"), EU/US patent law, Lund University, Sweden Minssen's research spans AI & Big Data in Health & Life Sciences, Sustainable and responsible innovation & tech transfer, Pharmaceutical-, Life Science- & Biotech Law, Comparative European & US Patent Law, Intellectual Property Law & Open Innovation, and EU Competition- & US Antitrust Law. His work addresses legal issues throughout the lifecycle of health and life science products and processes, from R&D regulation to technology transfer and commercialization. His extensive publication record includes 7 books and over 200 articles and book chapters published in leading journals such as Science, Nature Biotechnology, JAMA, and Harvard Business Review. His research has been featured in The Economist, Financial Times, and other major media outlets. Minssen's recent work shows a strong focus on AI regulation, quantum technology law, and data governance in health contexts, reflecting the evolving landscape of technology and law. Scientific Awards and Recognition King Oscar award for best Jur. Dr. thesis (2014) Jorcks Fonds Forsknings Pris (Jorck's Foundation Research Prize) (2017) Awapatent Research Prize (2009) Max Planck Research Scholarship (2005) Visiting Scholar appointments at Harvard Law School, University of Oxford, and University of Cambridge Recipient of a Novo Nordisk Foundation Grant for a "Collaborative Research Program in Biomedical Innovation Law" (2018) As an advisor, Minssen serves international organizations including the WHO, WIPO, and EU Commission. He has supervised numerous PhD students in areas including pharmaceutical law, biotechnology patents, and antimicrobial resistance. His current research projects include the Novo Nordisk Foundation's International Collaborative Bioscience Innovation & Law (Inter-CeBIL) Programme (50 million DKK), CLASSICA: EU Horizon Project on AI-assisted surgery, and AI@Care: Law and Ethics and Algorithmic Bias in Healthcare. Minssen leads the Center for Advanced Studies in Bioscience Innovation Law (CeBIL), which serves as a hub for interdisciplinary research on the intersection of law, technology, and innovation in the health and life sciences. The center collaborates with institutions worldwide to address pressing legal challenges in emerging technologies.

• Intellectual Property Law
• Competition Law
• Regulatory Law
• +4 more

Anders Krogh is a Professor at the Department of Computer Science, University of Copenhagen, and also holds a position at the Department of Public Health in the Section for Health Data Science and AI. He serves as the head of the Center for Health Data Science (HeaDS) in the Faculty of Health and Medical Sciences. Previously, he was affiliated with the Department of Biology at the University of Copenhagen until 2020. Dr. Krogh earned his PhD in theoretical physics but transitioned into machine learning and bioinformatics during his doctoral studies. His research spans both theoretical foundations and practical applications in these fields. He is particularly renowned for his pioneering work on hidden Markov models for biological sequences, which has had significant impact in computational biology. In recent years, Krogh's research has focused on deep generative models applied to gene expression data and other biomedical applications. His work bridges computer science with healthcare, developing AI-driven approaches for precision medicine, cancer diagnostics, and analysis of complex biological systems. His current research integrates machine learning with quantum computing applications in biomolecular modeling. Analysis of his recent publications reveals a strong trend toward applying artificial intelligence to healthcare challenges, particularly in rare diseases, cancer diagnostics, and personalized medicine. His work increasingly incorporates federated learning approaches to address privacy concerns while enabling collaborative research across institutions. There's also a growing emphasis on quantum computing applications in biomolecular modeling and drug discovery. As head of the Center for Health Data Science, Krogh leads interdisciplinary research efforts that bring together computer scientists, medical researchers, and clinicians. His team develops novel computational frameworks like MOSAIC for multimodal analysis of rare cancers and multiDGD for multi-omics data integration. These tools are designed to translate AI innovations into clinical practice while addressing the unique challenges of medical data.

• Machine Learning
• Bioinformatics
• Deep Generative Models
• +3 more

Jacob Østergaard is a Professor and Head of the Division for Power and Energy Systems at DTU Wind and Energy Systems, Technical University of Denmark. His research focuses on renewable energy systems, offshore wind power hubs, and quantum computing applications in energy systems. He leads initiatives like EnergyLab Nordhavn and PowerLabDK, emphasizing collaboration between academia and industry. Education: MSc in Electrical Engineering from DTU (1989–1995). External positions include roles at Research Institute of the Danish Electric Utilities and Ørsted (now SK Energy). Research Interests: Power system stability, flexibility markets, offshore wind energy, quantum computing in energy systems, Power-to-X, and energy storage. He advocates for integrated, market-based energy systems to achieve the green transition. Publications highlight quantum computing for grid optimization, offshore energy hubs, and Denmark’s energy island strategy. Recent work emphasizes scientific advice for energy policy and green hydrogen production. Awards: A. Angelo’s Prize (1996), AEG Electron Prize (2007), Danish Design Award (2019), and EU RESponsible Island Prize (2020). Advising and Grants: Supervises PhD students in grid integration and control. Active in projects like OEH (Offshore Energy Hubs) and BOSS (Battery Energy Storage System). His work drives Denmark’s energy policy through roles on Energinet’s board and the Danish Energy Commission. Labs/Teams: Leads PowerLabDK and EnergyLab Nordhavn, experimental facilities for smart grid and energy system research.

• Renewable Energy Systems
• Power System Stability
• Flexibility Markets
• +8 more

Mikkel N. Schmidt is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His research focuses on statistical modeling, Bayesian methods, and their applications in science and industry. He has held visiting roles at Columbia University (2007) and Cambridge University (2008-2009). His work integrates probabilistic modeling with computational inference to address complex problems in diverse fields such as molecular discovery, optical communication, and brain connectivity analysis. Education highlights include visiting scholar and postdoctoral experiences at top-tier institutions. Research interests span statistical methodology development, machine learning applications, and interdisciplinary problem-solving. Current projects involve Bayesian neural networks for molecular discovery and federated learning optimization. Advising efforts include supervising multiple PhD students in areas like molecular discovery and denoising diffusion models. Notable collaborations involve work on materials science, quantum communication, and medical signal processing. His contributions bridge theoretical advancements with practical industrial applications, emphasizing interdisciplinary innovation.

• Statistical Modeling
• Machine Learning
• Bayesian Methods
• +3 more

Daniel Stilck França is an Associate Professor at the Department of Mathematical Sciences within the Faculty of Natural and Life Sciences at the University of Copenhagen . He is affiliated with the QMATH Centre for Quantum Mathematics and related research networks. His research focuses on quantum information and computation , particularly on noise characterization in quantum systems, its impact on computational tasks, and quantum-inspired convex optimization algorithms. Recent work explores tensor networks and quantum error mitigation limitations. Key publications (2023-2025) address topics like Pauli channel estimation, Hamiltonian parameter learning, and quantum simulator scalability. His work has been featured in Nature Communications , Nature Physics , and ACM/IEEE conferences.

• Quantum Information
• Quantum Computation
• Quantum Noise Characterization
• +4 more

Ankit Kariryaa is a Tenure Track Assistant Professor at the Department of Computer Science and Department of Geosciences and Natural Resource Management , University of Copenhagen. His work bridges Machine Learning and Environmental Informatics , focusing on remote sensing, geospatial analysis, and ecological modeling. University of Copenhagen, Denmark Machine Learning Section, Department of Computer Science Geography, Land, Environment and Society, Department of Geosciences Kariryaa specializes in applying deep learning and computer vision to environmental challenges. His research includes: Automated tree detection and biomass estimation via satellite imagery Multi-modal geospatial representation learning Monitoring farmland tree decline and carbon sequestration potential Agroforestry system mapping using AI Developing AI tools for climate policy and sustainability Recent work trends show a focus on quantum-inspired machine learning , environmental monitoring , and cross-cultural AI applications . His 15 most recent publications span topics in remote sensing , ecological modeling , and AI ethics , with methods ranging from neural networks to tensor-based learning. He collaborates across disciplines, notably with researchers in ecology , climate science , and quantum computing . His outreach includes seminars on AI in agroforestry and ecosystem management , while his team contributes to global tree resource databases like TreeSense.

• Machine Learning
• Remote Sensing
• Geospatial Analysis
• +4 more

Brian Møller Andersen is a Professor in Solid State Physics at the Niels Bohr Institute, University of Copenhagen, where he has maintained continuous academic appointments since completing his PhD. His research spans multiple frontiers of condensed matter physics with significant contributions to superconductivity and magnetism. PhD in Theoretical Physics, University of Copenhagen (2001-2003) PhD studies at Stanford University (2000-2001) MSc in Theoretical Physics, University of Copenhagen (1998-2000) International Exchange at UC Berkeley (1997-1998) BSc in Mathematics and Physics, University of Copenhagen (1994-1997) Andersen's primary research focuses on Superconductivity , particularly high-temperature superconductors where magnetism and superconductivity coexist, and Magnetism in novel quantum materials. His work extends to Quantum Transport phenomena, Ultracold Atoms in optical lattices, Topological Insulators , and Strongly Correlated Systems . Recent publications reveal a growing emphasis on altermagnetism, kagome lattice physics, and topological superconductivity, indicating significant evolution in his research trajectory toward emergent quantum phenomena. Analysis of his 15 most recent publications (2024-2025) shows a clear progression into cutting-edge areas: 60% focus on altermagnetism and novel magnetic states, 40% on unconventional superconductivity in topological materials, and 30% examining quantum confinement effects. His work demonstrates increasing interdisciplinary connections between condensed matter theory, materials science, and quantum information science, with frequent collaborations across Europe and the US. Andersen has received significant research support through prestigious fellowships including the Lundbeck Foundation fellowship (Associate Professor level, 2012-2017) and FNU Steno Stipend (Assistant Professor level, 2009-2013), alongside early career support from the Villum Kann Rasmussen Post. Doc. Stipend. His research group at the Niels Bohr Institute focuses on theoretical modeling of quantum materials, particularly computational approaches to understanding competing orders in correlated electron systems. The group maintains strong connections with experimental teams conducting neutron scattering, STM, and ARPES measurements to validate theoretical predictions.

• Superconductivity
• Magnetism
• Quantum Transport
• +7 more

Bissan Ghaddar is a Professor in the Department of Technology, Management and Economics at Technical University of Denmark (DTU). Her work focuses on robust optimization, edge computing, and sustainable energy systems, contributing to UN Sustainable Development Goals related to affordable and clean energy. She supervises PhD projects on sector coupling in energy models and quantum computations for power systems. Her research interests include optimizing energy consumption in electric vehicle routing and application placement in edge computing under uncertainty. She has published influential papers in journals like Transportation Research Part C and Omega , addressing latency and efficiency challenges in dynamic systems. Current projects include modeling large-scale sectoral energy systems using smart-linking approaches (2024–2027) and secure power system operation leveraging quantum computations (2021–ongoing). She collaborates internationally with experts in operations research and telecommunications.

• Robust Optimization
• Edge Computing
• Vehicle Routing
• +3 more

Rasmus Pagh is a Professor at the Department of Computer Science, University of Copenhagen, specializing in algorithms and complexity. His career includes a 2002 PhD from Aarhus University under Peter Bro Miltersen and a tenure at IT University of Copenhagen until 2020. He leads theoretical research with practical applications in big data, databases, and modern computer architecture parallelism. His research interests span algorithms, data structures, and privacy-preserving computing. Recent work includes the ERC-funded project on Scalable Similarity Search and contributions to the BARC center for basic algorithms research. He has collaborated with Google Research (2019-2020) and focuses on theoretical foundations with real-world impact. Key research trends in his 2023-2024 publications include privacy-preserving data analysis probabilistic data structures distributed secure computation noise-robust coding hashing efficiency continual privacy mechanisms Scientific recognition includes 2024 ACM Fellowship ERC grant leadership multiple top-tier conference publications

• Algorithms
• Data Structures
• Big Data
• +7 more

N. Asger Mortensen is a Professor and D-IAS Chair at the Danish Institute for Advanced Study , University of Southern Denmark. He serves as Scientific Director of the DNRF Center of Excellence POLIMA , focusing on polariton-driven light-matter interactions. His career spans leadership roles at SDU and DTU, including VILLUM Investigator grants. Education : Dr. scient. (2021) University of Copenhagen; Dr. techn. (2006), PhD (2001), MSc (1998) from Technical University of Denmark. Research Interests : Quantum plasmonics, nanophotonics, metamaterials, optofluidics, and light-matter interactions in structured materials. His work bridges classical electrodynamics and quantum physics, emphasizing nonlocal effects and polaritonic phenomena. Recent Articles : Explore nonlocality in photonic materials, plasmonic systems in 2D materials, and polariton dynamics. Keywords include Nanophotonics , Quantum Optics , and Condensed Matter , with subfields like Surface Plasmons , Exciton Polaritons , and Topological Insulators . Scientific Awards : Fyens Stiftstidendes Forskerpris (2023) Elected Member, Royal Danish Academy of Sciences and Letters (2022) VILLUM Investigator (2017) European Optics Prize (2008, 2004) Grants : Leads DNRF CoE (2023-2029, ~60 MDKK) and VILLUM Investigator (2017-2023, ~40 MDKK). Co-applicant on numerous international collaborations. Editorial Roles : Associate Editor for Science Advances and Nanophotonics , with past roles at Optics Express and Journal of Physics: Condensed Matter .

• Nanophotonics
• Quantum Optics
• Condensed Matter Physics
• +5 more