جست‌وجوی استاد و پژوهشگر

Peter C. Petersenمشاهده پروفایل

دانشیار

• Systems Neuroscience
• Computational Neuroscience
• Electrophysiology
• +۳ مورد دیگر

Peter C. Petersen is an Associate Professor in the Department of Neuroscience within the Faculty of Health and Medical Sciences at the University of Copenhagen. Holding a Civilingeniør (MSc) in Technical Physics from DTU and a PhD in Neuroscience, he specializes in systems-level neural mechanisms using electrophysiological approaches. His educational background includes: Civilingeniør (MSc) in Technical Physics, DTU PhD in Neuroscience Petersen's research focuses on neural dynamics in memory and motor systems, combining in vivo electrophysiology with computational modeling. He investigates hippocampal place cells for spatial working memory and rotational dynamics in spinal cord networks, while developing neurotechnology tools like CellExplorer for single-neuron analysis. His work bridges experimental neuroscience, engineering, and data science to decode circuit-level computations. Recent publications (2020-2024) reveal a dual emphasis on hippocampal memory mechanisms (e.g., temperature effects on sharp wave ripples) and innovative methodology (e.g., 3D-printed microdrives). This trajectory demonstrates consistent advancement from tool development to fundamental discoveries in neural coding, with increasing collaboration intensity as evidenced by multi-institutional authorship. Scientific awards: No specific awards were documented in the source material. While explicit advising details are absent, his leadership in software/hardware development (CellExplorer, microdrive systems) implies active mentorship of technical researchers. Grant information isn't specified, though high-impact publications suggest sustained funding for neurotechnology and systems neuroscience projects. Petersen directs the Petersen Lab (https://petersenlab.org/), which employs chronic electrophysiology in rodent models to study memory and movement. The lab maintains strong ties with the Buzsáki lab (hippocampal research) and continues collaborations initiated during his NYU Langone Health tenure (2016-2022), reflecting an integrated approach to neural circuit analysis across institutions.

• Population Genetics
• Medical Genetics
• Statistical Genomics
• +۵ مورد دیگر

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.

Alvaro Torralbaمشاهده پروفایل

دانشیار

• Symbolic Search
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Alvaro Torralba is an Associate Professor in the Department of Computer Science at Aalborg University, Denmark, affiliated with the Technical Faculty of IT and Design. His research focuses on symbolic search, heuristic functions, and planning algorithms within artificial intelligence and machine learning. Notable projects include the ConAn initiative exploring contrastive analysis for state-space exploration. He has contributed extensively to classical planning, probabilistic planning, and automated planning competitions, earning awards such as the First Prize in the Agile Track of the 10th International Planning Competition (IPC’23). His work often bridges theoretical advancements with practical applications, including game-based network update synthesis and believable non-player character development. Research outputs include over 60 publications since 2011, with a focus on optimizing search algorithms and enhancing planning efficiency through techniques like operator-potential heuristics and bidirectional search strategies. His scientific contributions span algorithmic innovation, verification methodologies, and large-scale abstraction evaluation. Collaborations and datasets include foundational work on PDDL generators and pattern databases, with open-access resources available via Zenodo. As a program committee member and award-winning researcher, Torralba actively contributes to advancing the frontiers of AI planning and decision-making systems.

Carsten Schürmannمشاهده پروفایل

استاد

• Information Security
• Cryptographic Voting Protocols
• Security Analysis
• +۵ مورد دیگر

Carsten Schürmann is a Professor of Theoretical Computer Science at IT University of Copenhagen, where he serves as Center Manager for the Center for Information Security and Trust. His research spans information security, cryptographic voting protocols, identity management, and digital democracy, with significant contributions to security ceremonies and formal verification of protocols. Professor, Department of Computer Science Center Manager, Center for Information Security and Trust Principal Investigator for multiple DIREC projects through 2025 Active researcher with 64 publications and 20 projects listed His research focuses on the intersection of theoretical computer science and practical security challenges, particularly in voting systems and security ceremonies. Schürmann has developed formal methods for analyzing security protocols, with emphasis on human factors in security implementations and cryptographic voting systems. His work bridges logical frameworks with real-world security applications, addressing both technical and socio-technical aspects of security. Analysis of his recent publications reveals a strong emphasis on voting security, with multiple papers on risk-limiting audits, receipt-free voting, and election integrity. His work increasingly incorporates formal logical frameworks to verify security properties, while also addressing human factors in security ceremonies. The research spans theoretical foundations in linear logic to practical applications in election systems. As Principal Investigator, Schürmann leads several major projects funded by the Innovation Fund Denmark, including DIREC initiatives focused on Capacity Building, PhD School, Voting, and Entrepreneurship (2020-2025). He has also established working groups in Adversarial AI and Machine Learning. Organized workshops on Code Scanning (2014) and Verifying Security Protocols in Tamarin (2016) Active media commentator on security issues with 311 media appearances through 2025 Principal Investigator for 7 ongoing and 13 completed research projects Schürmann directs the Center for Information Security and Trust, which serves as a hub for interdisciplinary security research connecting theoretical computer science with practical security applications. His center focuses particularly on voting systems security and security ceremonies, bringing together researchers from multiple disciplines to address complex security challenges.

Jens Abildskovمشاهده پروفایل

دانشیار

• Thermodynamic Modeling
• Chemical Process Simulation
• Biocatalysis
• +۳ مورد دیگر

Jens Abildskov is an Associate Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark (DTU). He is affiliated with the KT Consortium PROSYS - Process and Systems Engineering Centre. His research focuses on thermodynamic properties of fluids, chemical process modeling, and simulation, with applications in biocatalysis, mixed solvents, and separation process optimization. Key areas include CO2 capture, biofuel processing, and energy-efficient separation systems. He collaborates extensively on integrating process modeling with control systems. His work aligns with UN Sustainable Development Goals addressing clean energy and responsible consumption. Recent projects include biogas upgrading technologies and open-source simulation tools like CADET-Julia. He supervises multiple PhD students in areas such as carbon capture, process digitalization, and safety engineering. Abildskov leads the PROSYS Centre, emphasizing process systems engineering. His lab develops models for fluid behavior in non-ideal systems, leveraging statistical mechanical methods and molecular correlation functions. He also explores applications in organic rankine cycles and heat integration for energy savings. Publications emphasize practical solutions for industrial challenges, such as solvent systems for CO2 capture and dynamic feeding strategies in separations. His research bridges theoretical and applied aspects of chemical engineering, with a focus on sustainability and innovation.

Tara Maria Bolandمشاهده پروفایل

پژوهشگر ارشد

• Computational Materials Science
• Materials Discovery
• Database Integration
• +۳ مورد دیگر

Tara Maria Boland is a Postdoc in the Department of Physics at the Technical University of Denmark, specializing in Computational Atomic-scale Materials Design. She maintains an active research profile with significant contributions to materials science infrastructure. Her research spans critical areas of modern computational science: Computational Materials Science and Atomic-scale Modeling Materials Discovery and Design Database Integration and Data Exchange Systems API Development for Scientific Applications 2D Materials and Heterostructures Machine Learning Applications in Materials Science Boland's publication record reveals a dual focus on fundamental materials research and practical computational tools. Her work on the OPTIMADE API has established new standards for materials data exchange, while her contributions to GPAW provide essential infrastructure for electronic structure calculations. The research demonstrates strong international collaboration across 10+ institutions with notable media coverage. As part of DTU Physics' Computational Atomic-scale Materials Design group, Boland collaborates extensively on projects advancing computational methodologies for materials science, with particular emphasis on creating accessible research infrastructure for the global community.

Thomas Olsenمشاهده پروفایل

دانشیار

• Magnetism in 2D Materials
• Spin Spiral Order
• Multiferroic Properties
• +۴ مورد دیگر

Thomas Olsen is an Associate Professor in the Department of Physics at the Technical University of Denmark (DTU). His research focuses on computational atomic-scale materials design, particularly in the areas of magnetism in 2D materials, spin spiral order, and multiferroic properties. He actively contributes to the development of the GPAW software package for electronic structure calculations. Olsen holds a Master in Physics from the University of Copenhagen (2001–2006) and a PhD from DTU. His work spans theoretical condensed matter physics, with expertise in density functional theory and its extensions. He has supervised multiple PhD students on topics like thermodynamics of 2D magnetism, itinerant magnetism, and hysteresis heating in nanoparticles. His research interests include predicting magnetic properties using first-principles methods, such as the magnetic force theorem and time-dependent density functional theory. Recent publications highlight advancements in calculating Curie temperatures, exploring electron-hole crystals in Mott insulators, and analyzing antiferromagnetism in 2D systems. Olsen collaborates extensively on projects involving van der Waals heterostructures, computational screening of materials, and the theoretical underpinnings of magnon dynamics. Education: PhD, Technical University of Denmark Master in Physics, University of Copenhagen Key Projects: Thermodynamics of 2D Magnetism (2022–2025) Itinerant magnetism in 2D materials (2022–2025) Ab-initio optical response calculations (2023–2027) His work aligns with sustainable development goals through contributions to advanced materials science and computational methods. He leads a vibrant research group focused on pushing the boundaries of materials design and theoretical physics.

• Declarative Process Modeling
• Process Mining
• Formal Verification
• +۴ مورد دیگر

Paul Cosma is a Postdoctoral Researcher at the Department of Computer Science (DIKU), University of Copenhagen, specializing in the Software, Data, People & Society (SDPS) section. His work focuses on declarative process modeling, formal verification, and explainable AI systems, with strong connections to process mining and Petri net theory. He completed his PhD at the University of Copenhagen's Faculty of Science in 2024 with a thesis on declarative process models as verifiable AI. His research interests center on declarative process modeling and formal verification of complex systems. Cosma develops techniques for improving model simplicity through nested group discovery and creates frameworks like BERMUDA for participatory mapping of domain activities to event data. His work bridges theoretical computer science with practical applications in business process management and AI explainability, emphasizing human-centered design principles where software systems are developed with societal impact in mind. Cosma's publication record shows a clear trajectory in process modeling research, with recent work focusing on transforming Dynamic Condition Response Graphs to Safe Petri Nets (2023) and improving declarative model simplicity (2024). His research demonstrates strong interdisciplinary connections between formal methods, AI verification, and human-computer interaction, particularly in making complex process models accessible and verifiable. Cosma actively collaborates with researchers including Thomas Hildebrandt, Tijs Slaats, and Axel Christfort, primarily within the SDPS section at DIKU. His work receives consistent citations in process mining literature, with his 2023 PETRI NETS paper accumulating 1 citation and his CAiSE 2024 paper gaining 2 Scopus citations. He maintains an ORCID profile (0000-0001-8022-6402) and contributes to open-access research through the university's Pure repository. Based in Sigurdsgade 41, Copenhagen N, Cosma operates within DIKU's collaborative research environment that emphasizes industry partnerships and interdisciplinary work. His recent PhD defense (June 13, 2024) marks his transition from doctoral candidate to postdoctoral researcher, positioning him to expand his contributions to process-aware information systems and verifiable AI.

Martin Elsmanمشاهده پروفایل

استاد

• Programming Languages
• Theory of Computation
• Functional Programming
• +۵ مورد دیگر

Martin Elsman is a full-time Professor in the Programming Languages and Theory of Computation section at the Department of Computer Science, University of Copenhagen (DIKU). He serves as head of the PLTC section and head of studies for the BSc education in Computer Science and Economics. Elsman is also an active maintainer of several software tools including the MLKit and SMLtoJs. Joined DIKU in 2012 after 4 years at SimCorp (2008-2012) and previous Associate Professorship at IT University of Copenhagen (2003-2008). Co-developer of Futhark, TAIL APL compiler, SMLtoJs, and SMLserver. Education: M.Sc. in Engineering, Technical University of Denmark Ph.D. in Computer Science, University of Copenhagen (DIKU), supervised by Mads Tofte. Research Interests: Elsman works on programming language design and implementation, with a focus on functional programming, module systems, domain-specific languages for financial contracts, region-based memory management, compilation techniques for parallelism, program optimization, and static type systems. His work spans both theoretical and applied domains, including blockchain-based financial contract execution, web technology, and GPU programming using functional languages. Publication Trends: His recent articles focus on functional programming, array programming, parallelism, and memory management. Topics include region inference, type systems for data-parallelism, program optimization techniques, and domain-specific compilation for financial and quantum computing. He frequently collaborates with Troels Henriksen and others on tools like Futhark and MLKit.

Jens Myrup Pedersenمشاهده پروفایل

استاد

• Cybersecurity
• Network Security
• Machine Learning
• +۵ مورد دیگر

Jens Myrup Pedersen is a Professor at Aalborg University's Department of Electronic Systems within The Technical Faculty of IT and Design. He is affiliated with the Cyber Security Group and focuses on improving digital wellbeing through cybersecurity research. His primary research interests include botnets, network security, machine learning applications in cybersecurity, and cybersecurity education. He leads or participates in projects such as Cyber Safe Robotics , AI:SECURITY , and GAMESS , addressing topics like AI-driven security, gamification in education, and secure software development. Pedersen has contributed to over 235 publications since 2003, emphasizing cybersecurity threats, network analysis, and educational methodologies. His work extends to cybersecurity training platforms like Haaukins and The Privacy Universe , designed to enhance user awareness through gamification. Pedersen collaborates internationally, engaging in initiatives like the European Cyber Security Challenge and cybersecurity hackathons. He holds roles in professional organizations such as the Danish Cybersecurity Board and the IDA association. Recent research highlights include NLP security ethics, OT cyber resilience, and cryptocurrency forecasting tools. His projects often bridge academia and industry, focusing on real-world impact through student-driven projects and cross-disciplinary collaborations.

Frederik Marinus Trudslevمشاهده پروفایل

پژوهشگر ارشد

• Privacy Metrics
• Synthetic Data Generation
• Metagenomics
• +۳ مورد دیگر

Frederik Marinus Trudslev is a PhD Fellow at the Department of Computer Science, The Technical Faculty of IT and Design, Aalborg University, Denmark, focusing on critical challenges at the intersection of data privacy and bioinformatics. His research bridges computer science and computational biology through innovative work in synthetic data generation and genomic analysis. Trudslev's primary research domains include privacy-preserving synthetic data, where he develops rigorous metrics and evaluation frameworks to balance data utility with individual privacy protection. In bioinformatics, he pioneers ensemble methods for metagenomic binning, significantly improving microbial genome reconstruction from complex environmental samples through advanced clustering techniques. His 2023-2025 publications reveal a strategic pivot toward privacy-enhancing technologies, evolving from metagenomic binning (BinChill, 2023) to comprehensive privacy metric frameworks (2025 review) and practical evaluation tools (PrivEval, 2025). This progression demonstrates increasing specialization in synthetic data validation while maintaining cross-disciplinary relevance. As a key participant in the HEREDITARY project (2024-2027) on gut-brain interplay data integration, Trudslev collaborates with international researchers including Dell'Aglio and Lissandrini. Though no student advising is documented, his project leadership in this major EU-funded initiative highlights significant research impact. His work shows strong potential for future applications in healthcare data sharing and microbiome research.

Markus Strohmaierمشاهده پروفایل

استاد

• Computational Social Science
• Data Science
• Machine Learning
• +۷ مورد دیگر

Markus Strohmaier is Professor and Chair of Data Science in the Economic and Social Sciences at the University of Mannheim, with affiliations as Scientific Coordinator at GESIS – Leibniz Institute for the Social Sciences and External Faculty Member at the Complexity Science Hub Vienna. His interdisciplinary work bridges computer science, economics, and the social sciences. University of Mannheim – Chair for Data Science in the Economic and Social Sciences GESIS – Scientific Coordinator for Digital Behavioral Data Complexity Science Hub Vienna – External Faculty Former Professor at RWTH Aachen University and University of Koblenz-Landau Previous Post-Doc and Visiting Roles at Stanford University, Xerox PARC, University of Toronto, and Graz University of Technology His research focuses on computational social science , algorithmic fairness , network science , and the modeling of human behavior using machine learning and large-scale data. He develops methods to analyze textual, relational, and emerging data types to understand socioeconomic systems and digital societies. The recent articles reflect a strong trend in studying inequality in algorithmic systems , governance in decentralized organizations (DAOs) , and psychological profiling of AI . His work spans high-impact journals like Nature and Scientific Reports , emphasizing fairness, transparency, and societal impact of data-driven technologies. Notable scientific contributions include: Editor-in-Chief of EPJ Data Science (2018–2022) Founding co-chair of the Computational Social Science section of the German Informatics Society He advises students and leads research projects on algorithmic fairness, digital governance, and behavioral modeling. His team engages in both fundamental methodological development and applied studies in real-world digital platforms. He has been involved in significant grants and collaborative initiatives around digital behavioral data and computational social science infrastructure. His lab and projects include the Algorithmic Fairness initiative and the interactive visualization tool Planets of Disparity , which explores how algorithms behave on different network structures. These efforts aim to enhance public understanding and technical scrutiny of algorithmic systems.

Lisbet Tarpمشاهده پروفایل

دانشیار

• Digital Art History
• Materiality in Art
• Painting
• +۷ مورد دیگر

Lisbet Tarp is an Associate Professor in Art History at the School of Communication and Culture, Aarhus University. Her academic work bridges traditional art historical scholarship with digital methodologies and interdisciplinary research, particularly in the fields of painting, materiality, and conservation. She is actively engaged in several high-impact research projects exploring the intersections of art, science, and technology. Research Interests: Digital Art History and computational analysis of paintings Materiality and technique in historical and contemporary painting Conservation science and hidden layers in artworks Mathematics and geometry in visual art Early modern court culture and ceremonial representation Interdisciplinary practices between art and anatomy Her recent publications reflect a strong trend toward integrating digital tools into art historical inquiry, with a focus on uncovering the material and technical dimensions of paintings. Projects such as Digital Art History: Rediscovering the Painting and ANAT: Anatomical Theater demonstrate her innovative approach to visual culture through scientific and digital lenses. Her work often involves collaborative, peer-reviewed publications and digital dissemination. Scientific Projects & Activities: ANAT: Anatomical Theater (2023–2029) – Investigating dissection as aesthetic practice in early modern and contemporary contexts Digital Art History: Rediscovering the Painting (2019–2022) – Using digital methods to analyze painting techniques and material composition MoCMa: Mobility Creates Masters (2017–2019) – Studying transnational influences in European art LUMEN Center (2015–2025) – Researching Lutheran theology and its impact on confessional societies and visual culture Lisbet Tarp has contributed extensively to academic discourse through peer-reviewed journals, anthologies, and digital publications. While no formal students or awards are listed, her leadership in major research initiatives underscores her scholarly influence. She employs digital platforms for both research and pedagogy, including student-organized seminars and open-access digital versions of her work.

• Distributed Systems
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Brian Nielsen is an Associate Professor at Aalborg University's Department of Computer Science, under The Technical Faculty of IT and Design. His research focuses on Distributed Systems, Embedded Systems, Real-Time Systems, Model Checking, IoT Networks, and Autonomous Vehicles. He has been actively involved in projects such as domOS (operating system for smart buildings), FED (Flexible Energy Denmark), and compositional verification of multicore avionics systems. His work emphasizes model-based validation, formal methods, and industrial applications, particularly in safety-critical systems. Recent research highlights include energy-efficient motion planning for autonomous vehicles, comparative analysis of network simulators, and sigfox-based IoT modeling. He has received awards including the Application Coordinator Pool and START funds (both in 2007). Key Projects: domOS, FED, compositional verification of multicore systems Grants: Multiple EU-funded projects (e.g., Horizon Europe) and industry collaborations Awards: Application Coordinator Pool (2007), START funds (2007) His publications span over 80 articles, with a focus on real-time systems, IoT interoperability, and model-driven development. He has advised two PhD students and has been actively involved in organizing international conferences and workshops.

Sonia Corianiمشاهده پروفایل

استاد

• Quantum Chemistry
• Computational Spectroscopy
• Molecular Properties
• +۷ مورد دیگر

Sonia Coriani is a Professor in Physical Chemistry at DTU Chemistry, Technical University of Denmark, since 2017. She leads a research group focused on theoretical chemistry and computational spectroscopy. Her academic journey includes a PhD from Aarhus University (2000), a permanent research scientist position at the University of Trieste (1999-2014), and associate professorship there since 2014. She held an adjunct associate professor position at the Centre for Theoretical and Computational Chemistry in Oslo (2007-2011) and was a Marie Curie IEF fellow (2010-2012) and AIAS-COFUND senior fellow (2015-2016). Education: Chemistry, University of Modena (1993) PhD in Theoretical Chemistry, Aarhus University (2000) Her research centers on developing quantum-chemical methodologies for static and dynamic molecular properties, particularly for systems with high dimensionality, complex environments, or novel spectroscopic phenomena. Key areas include non-linear optical experiments, magnetic circular dichroism, X-ray spectroscopies, and quantum computing applications in chemistry. Her recent publications highlight advancements in quantum linear response theory, polarizable embedding environments, X-ray absorption in water, and quantum algorithms for molecular properties. Collaborative work spans interdisciplinary projects with experimentalists, covering gas-phase molecules to biomolecular systems. Scientific Awards: Marie Curie IEF fellowship AIAS-COFUND senior fellowship Her work addresses challenges in ultrafast dynamics, photoionization, and the intersection of chemistry with physics and computational science, emphasizing accuracy and novel experimental guidance.