جستجوی استاد راهنمای دانشگاهی

Martin Skovgaard Andersenمشاهده پروفایل

دانشیار

• Optimization
• Signal Processing
• Machine Learning
• +۱۲ مورد دیگر

Martin Skovgaard Andersen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), where he specializes in Scientific Computing. His research integrates numerical methods, optimization, and machine learning to solve complex computational problems in engineering and data science. Education: Ph.D., University of California, Los Angeles (2006–2011) M.Sc., Aalborg Universitet (2001–2006) Postdoc, Linköping University, Sweden (2011–2012) His research interests include optimization (particularly conic and stochastic programming), numerical algorithms, signal processing, system identification, and fast solvers for integral equations. He works extensively on matrix analysis, regularization, and low-rank approximations, contributing to both theoretical and applied advancements in computational mathematics. The recent publications highlight a strong trend in developing efficient numerical algorithms for large-scale optimization and solving integral equations. His work emphasizes preconditioning, matrix truncation, and Bayesian inversion, with applications in electromagnetics, structural health monitoring, and network identification. There is a consistent focus on improving computational efficiency and scalability of solvers. Scientific Awards: No specific awards mentioned in the provided text. Andersen actively supervises PhD students and leads multiple research projects, including those on non-symmetric conic optimization, data-sparse models, and fast direct solvers. He is the Principal Investigator (PI) on projects related to physics-informed structural health assessment. His collaborative network spans Denmark and international institutions, particularly in computational mathematics and engineering. Labs and Research Teams: He is affiliated with the Scientific Computing section at DTU, which focuses on high-performance computing, numerical algorithms, and mathematical modeling. His work is embedded in a collaborative environment involving researchers in optimization, control theory, and computational electromagnetics.

Jonas L. Juulمشاهده پروفایل

استادیار

• Network Science
• Social Networks
• Epidemiology
• +۵ مورد دیگر

Jonas L. Juul is an Assistant Professor in the Computer Science Department at the IT University of Copenhagen . With a background in network science and complex systems, he employs statistical methods, mathematical modeling, and computer simulations to study social networks, spreading processes, and human behavior. Focus areas include: information diffusion in social networks Disease spread mitigation in human populations Interdisciplinary collaboration with medical doctors, economists, and computer scientists Recent research highlights include improving statistical models for pandemic forecasting through the InForM project funded by the Novo Nordisk Foundation , and groundbreaking work on contact tracing optimization and information cascade dynamics. Notable recognitions: 2025 H.C. Ørsted Research Talent Prize 2024 Novo Nordisk Foundation Data Science Emerging Investigator Grant 2025 Young Academy membership He has contributed to mathematical modeling efforts during Denmark's COVID-19 reopening in 2020 and maintains active collaborations with institutions including Cornell University , Technical University of Denmark , and Niels Bohr Institute .

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.

Poul G. Hjorthمشاهده پروفایل

دانشیار

• Dynamical Systems
• Mathematical Modelling
• Industrial Applied Mathematics
• +۶ مورد دیگر

Poul G. Hjorth is an Associate Professor in the Department of Applied Mathematics and Computer Science (DTU Compute) at the Technical University of Denmark (DTU). He specializes in dynamical systems, mathematical modeling, and industrial applied mathematics, with strong interdisciplinary ties to neuroscience and industrial problem-solving. He has held visiting positions at the University of Southern Denmark and maintains affiliations with the University of Copenhagen as an External Lecturer. Ph.D. in Mathematical Physics, University of California, San Diego (1988) cand.scient in Mathematics, University of Copenhagen (1982) His research focuses on mathematical physics, classical mechanics, dynamical systems, and geometry , particularly in real-world industrial applications. He has been instrumental in organizing the European Study Groups with Industry (ESGI) in Denmark and is Executive Director of the European Consortium for Mathematics in Industry (ECMI). His recent work includes modeling the glymphatic system and cerebrospinal fluid dynamics in the brain, contributing to neuroscience and medical research. The most recent publications reflect a shift toward interdisciplinary applications, especially in neuroscience, fluid dynamics, and environmental modeling , while maintaining a strong foundation in pure and applied mathematics. Themes include brain efflux, phytoplankton dynamics, and philosophical explorations of probability and cosmology. DTU Teaching Award (2010) Hjorth has supervised students and led multiple long-term research projects since the 1990s. He serves as Editor for the Danish Mathematical Society Newsletter Matilde and the Fields Institute journal Mathematics in Industry Case Studies . His collaborative network spans institutions in Denmark, Israel, the UK, and the USA, reflecting his international engagement in both research and academic service.

Michael Sørensenمشاهده پروفایل

استاد

• Statistical Inference for Stochastic Processes
• Stochastic Differential Equations
• Financial Mathematics
• +۳ مورد دیگر

Michael Sørensen is a Professor at the Department of Mathematical Sciences, University of Copenhagen. His primary research focuses on statistical inference for stochastic processes, particularly stochastic differential equations and jump processes, with applications in finance, physics (e.g., wind-blown sand dynamics), and biology. He has authored/co-authored influential books such as Exponential Families of Stochastic Processes and edited volumes on empirical process techniques and statistical methods for stochastic differential equations. His work bridges theoretical statistics with applied problems in natural sciences and finance. Research interests include modeling turbulence, sand transport dynamics, and protein structure evolution. Collaborations with earth scientists like Keld Rømer Rasmussen have advanced understanding of aeolian processes. His methodologies emphasize likelihood-based inference and estimating functions, with contributions to high-frequency data analysis and diffusion bridge simulations. A comprehensive CV and full publication list are available on his profile. Key contributions span stochastic modeling in physics (e.g., sand dune dynamics), financial econometrics, and computational statistics. He has pioneered techniques for analyzing multi-modal diffusions and developed frameworks for mixed-effects stochastic differential equations. His work is widely cited in both theoretical and applied statistical literature.

• High-Energy Nuclear Physics
• Experimental Physics
• Particle Physics
• +۴ مورد دیگر

You Zhou is an Associate Professor at the Niels Bohr Institute , University of Copenhagen, leading the Experimental Subatomic Physics group. With a focus on Quark-Gluon Plasma (QGP) studies via the ALICE collaboration at CERN since 2010, his work leverages anisotropic particle expansion to probe QGP properties, including shear viscosity and thermalization. Principal Investigator of Villum Young Investigator project (2019–2024) on creating the "smallest droplet of early universe" Over 450 publications in experimental nuclear/particle physics Organized major international conferences including Initial Stages 2023 and Quark Matter workshops His research bridges high-energy nuclear physics , particle correlations , and collective flow , supported by grants from the Carlsberg Foundation , DFF-Sapere Aude , and Villum Foundation . He supervises students from bachelor projects to PhDs, including award-winning theses from Katarina Gajdosova and Vojtech Pacik . Key awards include the Villum Young Investigator (2019) and Carlsberg Postdoctoral Fellowship (2016). Recent lectures span the Nordic Winter School and Peking University . His work on femtoscopy, hypernuclei, and photon production has advanced understanding of early universe conditions and matter formation.

Tue Herlauمشاهده پروفایل

دانشیار

• Bayesian Methods
• Complex Networks
• Brain Imaging Data Analysis
• +۳ مورد دیگر

Tue Herlau is an Associate Professor at the Department of Applied Mathematics and Computer Science, Cognitive Systems, within the College of Engineering at Technical University of Denmark. His research focuses on modeling complex networks using Bayesian methods, particularly applied to brain imaging data. He explores multiscale structures in networks (ranging from individual nodes to large-scale temporal dynamics) and causal inference in social and biological systems. Education : Bachelor in Physics and Mathematics (University of Copenhagen), Masters in Informatics (DTU) Recent publications highlight work on generative AI for educational psychology, causal probability trees, Bayesian neural network training, and moral reinforcement learning. Key collaborations span institutions in Denmark and international partners in AI and neuroscience research. He supervises students in probabilistic methods and machine learning applications, including a 2019-2020 Master project on prognostics for carbon/epoxy composites. His network shows strong engagement with computational science, relational databases, and formal concept analysis.

David Pereñiguezمشاهده پروفایل

پژوهشگر ارشد

• Theoretical Particle Physics
• Cosmology
• Black Hole Physics
• +۲ مورد دیگر

David Pereñiguez is a Postdoctoral Fellow at the Niels Bohr Institute (NBI), affiliated with the Faculty of Science at the University of Copenhagen. He holds a PhD in Theoretical Physics from the Autonomous University of Madrid and joined NBI in October 2022. His research focuses on black hole physics and gravitational wave propagation , particularly how these waves encode information about black hole structure and new physics. Key themes include superradiant instability , ringdown signals , and electric-magnetic duality . Education PhD in Theoretical Physics, Autonomous University of Madrid Research Trends : His recent work explores gravitational wave dynamics in black hole spacetimes, nonlinear effects in ringdown, and constraints on massive gravity theories. Collaborations include researchers like Vitor Cardoso and Riccardo Brito. Contact : Email: david.pereniguez@nbi.ku.dk Office: Building C, Room Cc3a, Blegdamsvej 17, Copenhagen

Orimar Sauri Arreguiمشاهده پروفایل

دانشیار

• Mathematical Statistics
• Stochastic Processes
• Nonparametric Estimation
• +۷ مورد دیگر

Orimar Sauri Arregui is an Associate Professor in the Department of Mathematical Sciences at Aalborg University's Faculty of Engineering and Science, Denmark. His research lies at the intersection of mathematical statistics, stochastic processes, and financial modeling. Research Interests: His work focuses on ambit fields , trawl processes , Lévy and infinite divisible random fields , and nonparametric estimation in continuous time. He investigates asymptotic behavior, limit theorems, and statistical inference for complex stochastic models, with applications in financial market microstructure and energy flux modeling. The analysis of his recent publications reveals a strong trend in theoretical statistics and probability, particularly in developing and analyzing models driven by non-Gaussian noise and long-range dependence. His work often involves high-frequency data and contributes to the foundations of spatiotemporal modeling. Scientific Contributions: Developed mathematical frameworks for financial market microstructure. Advanced theory for nonparametric estimation of trawl processes. Derived asymptotic error distributions for numerical schemes in stochastic delay equations. Proved local limit theorems for energy fluxes in random fields. Advising and Research Activity: He has been involved in PhD supervision and maintains an active research output, primarily through preprints on arXiv and SSRN. His collaborations span topics in financial econometrics and statistical physics. Though specific grants are not listed, his consistent publication record suggests ongoing research funding. Laboratory and Teams: While no formal lab is mentioned, his work is part of the broader research network in mathematical statistics and financial mathematics at Aalborg University, with notable collaborations in stochastic modeling and econometrics.

Karl Michael Ziemsمشاهده پروفایل

پژوهشگر

• Quantum Computing
• Quantum Chemistry
• Linear Response Theory
• +۷ مورد دیگر

Karl Michael Ziems is a Postdoctoral Researcher in the Department of Chemistry, Physical Chemistry group at the Technical University of Denmark (DTU), where he conducts advanced research at the interface of quantum computing and quantum chemistry. He also holds an external part-time academic position as a Lecturer at the University of Southampton, effective from January 1, 2025. His research focuses on developing and refining quantum computational methods for accurate prediction of molecular properties. Key areas include quantum linear response theory, polarizable embedding for environmental effects, and noise mitigation strategies in quantum simulations. He actively contributes to bridging the gap between theoretical quantum chemistry and practical implementation on near-term quantum devices. The most recent publications (2024–2025) reveal a strong trend toward hybrid quantum-classical methodologies, particularly in simulating spectroscopic properties and molecular excitations. These works demonstrate applications in both model systems and real materials like ice polymorphs, with emphasis on validating quantum algorithms against classical benchmarks and improving robustness against hardware noise. He collaborates extensively with a core team including S. P. A. Sauer, J. Kongsted, and S. Coriani, publishing in high-impact journals such as Chemical Science , Journal of Chemical Physics , and Journal of Physical Chemistry A . His research is cited and discussed in academic networks, with Mendeley readership and social media mentions indicating scholarly engagement. While no formal scientific awards or grants are listed, his external lecturer role and consistent publication record reflect growing academic recognition. He advises no students listed in the provided information. His work is supported by computational infrastructure at DTU, and he is likely involved in collaborative quantum chemistry initiatives, though specific labs or research centers are not explicitly named in the text.

Jessica Mariana Carlssonمشاهده پروفایل

دانشگاهی

• Transcultural Psychiatry
• Trauma and PTSD
• Clinical Research
• +۷ مورد دیگر

Jessica Mariana Carlsson is a Research Associate Professor at the University of Copenhagen and Head of Research at the Competence Centre for Transcultural Psychiatry (CTP), Mental Health Services in the Capital Region of Denmark. She is also Co-PI of the CultMind project and leads a dynamic research group at both CTP and Trauma Research and Treatment (TREAT) at Mental Health Centre Ballerup. Her role integrates research leadership, clinical work, teaching, and supervision. Research Interests: Jessica's work centers on transcultural psychiatry and clinical research on trauma-affected populations, particularly refugees. Her primary focus includes PTSD, treatment development, cultural influences on mental health, and the integration of research with clinical practice through the Treatment and Research Integrated Model (TRIM). She employs both quantitative and qualitative methods and leads neurobiological studies using MRI and EEG. Research Trends: Her recent publications (2023–2025) show a strong emphasis on developing and validating assessment tools (e.g., ScoRE-SR), understanding sleep and pain in PTSD, refining diagnostic processes for migrants, and evaluating interprofessional care models. The studies often involve multidisciplinary collaboration and are published in high-impact journals in psychiatry, sleep research, and transcultural mental health. Scientific Awards: No specific awards mentioned in the provided text. Advising and Grants: Jessica supervises a growing research group and mentors junior researchers. While specific grant details are not listed, her leadership in multiple clinical trials and research initiatives (e.g., CultMind, TRIM) indicates substantial grant-funded work. She actively collaborates with national and international researchers and clinicians, contributing to a broad network in trauma and transcultural mental health. Labs and Teams: She leads research activities at the Competence Centre for Transcultural Psychiatry (CTP) and the Trauma Research and Treatment (TREAT) unit at Mental Health Centre Ballerup. These teams focus on clinical trials, diagnostic innovation, cultural assessment, and neurobiological research in trauma-affected refugees.

Jordan Andrew Snyderمشاهده پروفایل

مدرس

• Hematology
• Mathematical Biology
• Oncology
• +۳ مورد دیگر

Jordan Andrew Snyder serves as a Visiting Lecturer in the Department of Science and Environment at Roskilde University, Denmark, where he is affiliated with the Centre for Mathematical Modeling - Human Health and Disease. His academic work integrates advanced mathematical techniques with biomedical research, particularly in hematology and complex network dynamics. Dr. Snyder's research spans two primary domains: Biomedical Modeling : Focused on myeloproliferative neoplasms (MPNs), including stem cell dynamics during ruxolitinib treatment, CALR mutation progression from clonal hematopoiesis to myelofibrosis, and prognostic markers like neutrophil-to-lymphocyte ratios Network Science : Investigating oscillator synchronization, coarse-grained modeling of complex systems, cascading failures in modular networks, and emergent structures in mutualistic ecosystems His publication analysis reveals a distinctive interdisciplinary trajectory where mathematical frameworks bridge hematologic malignancies and fundamental network principles. Recent work demonstrates how amplitude dynamics stabilize oscillator clusters (2025) and how CALR mutations manifest in population screening (2024), showcasing dual expertise in theoretical dynamics and clinical translation. Dr. Snyder operates within Roskilde University's Centre for Mathematical Modeling - Human Health and Disease, an interdisciplinary hub where mathematical approaches address complex biomedical challenges through close collaboration with clinical researchers and international institutions including Memorial Sloan Kettering Cancer Center.

• Programming Languages
• Quantum Computing
• Reversible Computing
• +۳ مورد دیگر

Robin Kaarsgaard is an Assistant Professor (Tenure-track) specializing in Programming Languages, Quantum Computing, and Reversible Computing. His work bridges theoretical computer science with practical programming language design, focusing on foundational aspects of quantum algorithms, invertible computation, and algebraic structures. Research interests include quantum programming languages, reversible computing models, category theory applications in computer science, and formal semantics of programming constructs. He has contributed to frameworks like Jeopardy, an invertible functional language, and explored quantum computing's computational limits through mathematical abstractions. Key projects include the Landauer Meets von Neumann initiative (2020–2022), investigating reversibility in quantum semantics. His work has been featured in media discussions about academic life in Svendborg, Denmark. Publications span 28 peer-reviewed outputs in venues like ACM Proceedings and Lecture Notes in Computer Science, with recent focus on compositional approaches to quantum programming and invertible recursion mechanisms.

Mikael Andersen Langthjemمشاهده پروفایل

دانشیار

• Applied Mathematics
• Fluid Dynamics
• Structural Mechanics
• +۳ مورد دیگر

Mikael Andersen Langthjem is an Associate Professor at the Department of Mechanical and Production Engineering Mechanics and Materials, Aarhus University. His research focuses on fluid-structure interactions, wave propagation, and stability analysis in mechanical systems. Academic Rank: Associate Professor Department: Mechanical and Production Engineering Mechanics and Materials Email: ml@mpe.au.dk Langthjem's work spans applied mathematics, computational mechanics, and experimental validation, with recent publications on vortex dynamics, pipeline buckling, and rotating fluid systems. His research employs matched asymptotic expansions and multiple scales analysis for complex mechanical problems. He has contributed to studies on fluttering flags, ring tone mechanisms, and transient responses in rotating machinery with fluid balancers.

Hao Liمشاهده پروفایل

پژوهشگر ارشد

• Topology Optimization
• Mechanical Engineering
• Thermal Systems
• +۲ مورد دیگر

Hao Li is a MSCA Postdoc Fellow and Visiting Scholar at LIP6 , affiliated with the University of Southern Denmark in the Department of Mechanical Engineering . His research focuses on advanced computational methods for topology optimization in thermal, fluid, and structural engineering systems. Education: Not explicitly stated in the provided text. Current Projects: Leading EU-funded research on heat exchanger design using multiscale models and machine learning. Dr. Li's work spans multiscale topology optimization, level-set methods, and fluid-structure interaction, with applications in microchannel cooling, compliant mechanisms, and biodegradable composites. His recent publications highlight advancements in 3D conjugate heat transfer, adaptive meshing, and eigenfrequency maximization. The trends in his research output (2017–2025) emphasize thermal-fluid systems , high-resolution structural optimization , and manufacturable composite designs . Notable subfields include triply periodic minimal surfaces for cooling channels, nonlinear buckling analysis, and phasor-based dehomogenization techniques. Teaching & Supervision: Currently supervising projects on topology optimization frameworks for heat sinks and high heat flux cooling. His past projects (2018–2023) include research on piezoelectric transducers and thermal-fluid system design. Labs & Collaborations: Collaborates with institutions in Japan and France, focusing on experimental validation and industrial applications. His network includes partnerships with researchers in structural mechanics, computational fluid dynamics, and additive manufacturing.