جست‌وجوی استاد و پژوهشگر

• Cancer Epidemiology
• Gynaecological Oncology
• Epidemiology
• +۴ مورد دیگر

Susanne Krüger Kjær serves as Clinical Professor at the Department of Clinical Medicine, University of Copenhagen, under the Faculty of Health and Medical Sciences. She is based at the Department of Obstetrics and Gynaecology within Rigshospitalet (Copenhagen University Hospital), specifically affiliated with the Juliane Marie Centre and Gynaecological Clinic. Her work bridges clinical practice and population-based research using Denmark's comprehensive national health registries. Her research centers on cancer epidemiology with specialization in gynaecological malignancies, including ovarian, vulvar, penile, and thyroid cancers. Key interests encompass risk factor analysis of fertility treatments, hormonal contraception, HPV vaccination, and reproductive health impacts on cancer development. She employs large-scale cohort methodologies and Scandinavian registry data to investigate causal relationships and long-term outcomes. Recent 2025 publications reveal strong interdisciplinary trends across oncology, epidemiology, and digital pathology. Her work consistently addresses cancer prevention mechanisms through vaccination studies, algorithmic tumor assessment, and molecular epidemiology. The research demonstrates rigorous register-based methodology with international consortium collaborations, particularly in gynaecological cancer consortia. Professor Kjær maintains active clinical and research roles at Rigshospitalet's Gynaecological Clinic, contributing to both patient care and translational research. Her network includes extensive national collaborations within Danish healthcare institutions and international partnerships through multi-center studies like the Ovarian Cancer Association Consortium.

• Gastrointestinal Surgery
• Colorectal Disease
• Gallstone Disease
• +۵ مورد دیگر

Lars Tue Sørensen is a Clinical Associate Professor at the Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, specializing in gastrointestinal surgery and inflammatory bowel diseases. His clinical and research work focuses on surgical management of gallstone disease, inflammatory bowel disease, and gastrointestinal cancer, with strong connections to the Capital Region of Denmark healthcare system. Dr. Sørensen's research interests center around gastrointestinal surgery, with specific expertise in: Gallstone disease and its surgical management Inflammatory bowel disease (Crohn's disease and ulcerative colitis) Surgical outcomes and complications Clinical guidelines development Epidemiology of gastrointestinal conditions Comparative effectiveness of surgical and endoscopic procedures His recent research portfolio demonstrates a strong emphasis on population-based studies and randomized clinical trials in gastrointestinal surgery. Dr. Sørensen has contributed significantly to national clinical practice guidelines through the Danish Surgical Society, particularly for symptomatic gallstone disease management. His work often involves large-scale clinical data analysis and has practical implications for improving surgical care pathways and patient outcomes. Dr. Sørensen's research has received attention across academic platforms, with multiple publications being shared on social media, discussed in news outlets, and widely read by researchers on academic platforms like Mendeley. His collaborative network spans numerous Danish medical institutions, reflecting his integration within the national surgical research community.

• Nephrology
• Chronic Kidney Disease
• Acute Kidney Injury
• +۵ مورد دیگر

Lisbet Brandi is a Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen, specializing in Internal Medicine with a focus on Nephrology. Her dual institutional affiliations at Blegdamsvej 3, 2200 København N and Dyrehavevej 29, 3400 Hillerød reflect her integration of academic research with clinical practice within the Danish healthcare system (Region Hovedstaden). Her research spans multiple dimensions of kidney disease management with particular emphasis on: Chronic Kidney Disease treatment optimization Acute Kidney Injury diagnosis and prevention strategies Implementation of clinical guidelines in real-world settings Mathematical modeling of dialysis processes Healthcare provider perspectives on patient management Analysis of her publication record reveals a strategic focus on translating evidence into practice, particularly through innovative approaches like electronic nudges to improve guideline adherence. Her work bridges clinical medicine, health services research, and biomedical engineering, addressing critical gaps between theoretical recommendations and actual patient care. Dr. Brandi maintains extensive national collaborations across Danish medical institutions, as evidenced by her multi-author publications in high-impact journals including Circulation, American Heart Journal, and PLoS ONE. Her research demonstrates growing influence in both nephrology and cardiology communities, reflecting the significant cardiovascular comorbidities associated with kidney disease.

Freek Gerrit Witteveenمشاهده پروفایل

پژوهشگر ارشد

• Quantum Information Theory
• Tensor Networks
• Many-body Physics
• +۳ مورد دیگر

Freek Gerrit Witteveen is a Research Fellow in the Department of Mathematical Sciences at the University of Copenhagen's Faculty of Science. He maintains an active research profile in quantum information theory and mathematical physics with recent publications in high-impact journals. His research focuses on the theoretical foundations of quantum systems, particularly examining tensor networks and their applications to quantum gravity and quantum computing. Witteveen's work bridges mathematical rigor with physical insights, developing novel methods for quantum embedding and resource theories for tensor network representations. His publications have garnered significant attention in the research community, with multiple papers shared across X (formerly Twitter) and read by researchers on Mendeley. The collaborative nature of his work is evident through co-authorship with researchers from various institutions. Witteveen is based at Universitetsparken 5, 2100 København Ø, in building 1, room 01-4-05 at the University of Copenhagen. He can be contacted at fw@math.ku.dk and maintains a professional presence through his ORCID profile (https://orcid.org/0000-0002-3731-4455).

• Anaesthesiology
• Trauma Medicine
• Critical Care
• +۳ مورد دیگر

Johan Heiberg serves as a Clinical Associate Professor in the Department of Clinical Medicine at the University of Copenhagen, specializing in Anaesthesiology at Copenhagen University Hospital (Region H). His research focuses on critical advancements in trauma resuscitation, airway management, and perioperative care through rigorous clinical trials and systematic reviews. His primary research domains include Anaesthesiology , Trauma Medicine , and Critical Care , with specific expertise in awake nasal intubation techniques, oxygen therapy protocols for trauma patients, lymphatic function during anesthesia, and infection control in burn care. Current projects investigate robotic surgery outcomes and pediatric trauma imaging guidelines, reflecting his commitment to evidence-based practice improvement across diverse surgical contexts. Analysis of his 2024-2025 publications reveals a strong emphasis on multi-center randomized trials and systematic reviews addressing high-impact clinical questions. Key thematic clusters include airway management innovations (nasal intubation equipment, local anesthetic combinations), trauma oxygenation strategies, and burn unit infection protocols, with consistent collaboration across European academic medical centers evident in authorship patterns. Dr. Heiberg maintains active clinical-academic engagement through Copenhagen University Hospital, as demonstrated by his co-authorship in high-impact journals including JAMA and Acta Anaesthesiologica Scandinavica. His research receives significant attention in academic circles with 45 Mendeley readers and substantial social media dissemination (115 X posts, 39 Bluesky references), indicating strong relevance to contemporary anesthesiology practice.

Sonal Shreyaمشاهده پروفایل

استادیار

• Spintronics
• Neuromorphic Engineering
• Spintronic Devices
• +۷ مورد دیگر

Sonal Shreya is a Tenure Track Assistant Professor at the Department of Electrical and Computer Engineering, Aarhus University, within the Faculty of Engineering. Her research focuses on spintronics, neuromorphic engineering, and energy-efficient computing architectures. She explores applications in magnetic memory technologies, spintronic devices, and reservoir computing systems. Her work emphasizes developing novel circuits for in-memory computing, leveraging spintronic components like magnetic tunnel junctions (MTJs), STT-RAM, and spin-torque nano-oscillators. Key areas include energy-efficient data encryption, low-power pattern recognition, and multi-state memristor-based neuromorphic systems. She also investigates design thinking applications in engineering innovation, such as Tesla technology advancements. Recent studies highlight contributions to skyrmion dynamics for racetrack memory, vortex-based security solutions (PUF/TRNG), and thermal-induced memristor behaviors. Her publications span from 2014 to 2025, demonstrating a progression toward advanced spintronic applications in computing and sensing. Dr. Shreya collaborates on compact device modeling for circuit simulations and explores granular materials for reservoir computing. Her research bridges fundamental spintronics physics with practical applications in low-power electronics and hardware security.

• Algorithms
• Data Structures
• Big Data
• +۵ مورد دیگر

Rasmus Pagh is a Professor in the Algorithms and Complexity section of the Computer Science Department at the University of Copenhagen, Denmark. He is an ACM Fellow and a core researcher at the BARC (Basic Algorithms Research Copenhagen) center, with additional affiliation at the DeLTA Lab. From January 2019 to December 2020, he served as a visiting faculty researcher at Google Research. His primary research interests focus on algorithms and data structures with emphasis on big data applications. His work spans information retrieval, the role of randomness in computing, database applications, knowledge discovery, and more recently, differential privacy. His research has practical implications across multiple domains requiring efficient data processing solutions. Pagh's recent work shows a strong emphasis on differential privacy, particularly exploring correlated noise mechanisms and multiple release scenarios that maintain privacy guarantees while maximizing utility. His research demonstrates how to create multiple privacy-preserving releases without degrading overall privacy protection. ACM Fellow As an active supervisor, Pagh currently mentors four PhD students (Sia Sejer, Lukas Retschmeier, Joel Andersson, and Johanna Düngler) and has successfully graduated twelve PhD students whose careers now span academia and industry at organizations including Akamai Technologies, Microsoft, and Oracle. He serves on numerous prestigious program committees including STOC, FOCS, and ICALP, and has held leadership roles such as steering committee chair for the European Symposium on Algorithms (ESA) from 2022-2024. His research is centered at BARC (Basic Algorithms Research Copenhagen) where he leads work on fundamental algorithmic problems with applications to real-world data challenges. The center provides a collaborative environment for theoretical and applied algorithm research.

Carsten Wittمشاهده پروفایل

استاد

• Evolutionary Algorithms
• Runtime Analysis
• Genetic Algorithms
• +۷ مورد دیگر

Carsten Witt is a Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), working within the Algorithms, Logic and Graphs section. His research is centered on theoretical aspects of evolutionary computation, with a strong emphasis on runtime analysis, genetic algorithms, and randomized search heuristics. He is actively involved in guiding PhD research and has a substantial publication record in top-tier conferences and journals. PhD in Computer Science, Technical University of Dortmund, Germany Postdoctoral research at Max Planck Institute for Informatics Professor at DTU since appointment His primary research interests lie in evolutionary algorithms , runtime analysis , and probability theory in algorithmics . He investigates how bio-inspired optimization techniques such as genetic and compact genetic algorithms perform on benchmark problems like OneMax and LeadingOnes. His work often involves rigorous mathematical analysis to derive bounds on expected runtime and convergence behavior. The recent articles show a consistent trend in the theoretical foundations of evolutionary computation , particularly focusing on multi-valued representations, dynamic mutation strategies, neuroevolution models, and self-adjusting mechanisms. These works span subfields such as stochastic optimization, adaptive parameter control, and algorithmic analysis under probabilistic models. The dominant keywords include Computer Science, Theoretical Computer Science, Optimization, and Artificial Intelligence. Carsten Witt has not been explicitly listed with any scientific awards in the provided text. He has supervised several PhD students, including Adak, Rajabi, and Gießen, in projects related to nature-inspired algorithms and theoretical analysis. While specific grant names are not listed, his involvement in multiple funded PhD projects indicates active participation in research funding and academic leadership. Supervision roles include both main supervisor and examiner positions across various DTU research initiatives. Carsten Witt is affiliated with the Algorithms, Logic and Graphs group at DTU, which functions as a research lab focusing on foundational aspects of computing. This team conducts high-level theoretical research in algorithm design, discrete mathematics, and computational complexity, particularly in the context of heuristic and evolutionary methods.

Bjarne Kjær Ersbøllمشاهده پروفایل

استاد

• Applied Statistics
• Data Analysis
• Image Analysis
• +۴ مورد دیگر

Bjarne Kjær Ersbøll is a Professor in Statistics and Data Analysis at the Department of Applied Mathematics and Computer Science, DTU Compute, Technical University of Denmark (DTU). He has held academic positions since 1983, progressing from Research Assistant (1983-1986) to Full Professor (2010-present). His research focuses on applied statistics, data analysis, and their applications in industrial and medical projects, emphasizing collaborative solutions with industry and institutions. He holds M.Sc. (1983) and Ph.D. (1990) degrees from DTU. Key research interests include image analysis, multivariate statistics, and big data methodologies. He has supervised numerous master’s and Ph.D. theses and organized conferences on image analysis and statistics. Notable projects include studies on environmental contaminants in food, cardiovascular mortality linked to drinking water magnesium, and interventions in childhood dietary habits. His work contributes to UN Sustainable Development Goals related to health, sustainable cities, and responsible consumption. Recent publications highlight trends in public health (e.g., dietary interventions), environmental science (e.g., PFAS in eggs), and machine learning applications (e.g., deep learning for quality assessment). He actively participates in academic activities, including lecturing on applied statistics and supervising interdisciplinary projects.

Bent Jesper Christensenمشاهده پروفایل

استاد

• Econometrics
• Finance
• Labor Economics
• +۵ مورد دیگر

Bent Jesper Christensen is a Professor at the Department of Economics and Business Economics, Aarhus University. He holds a Ph.D. in Economics from Cornell University (1990) and maintains affiliations as a Research Fellow at the Danish Finance Institute (DFI) and the Center for Research in Energy: Economics and Markets (CoRE), alongside an External Fellow role at the University of Essex's Centre for Financial Econometrics. Ph.D., Economics, Cornell University, 1990 His research spans econometrics, finance, labor economics, macroeconomics, and insurance, with notable contributions to fractional cointegration, fractional GARCH models, and structural estimation of dynamic programming/search models. Recent work focuses on climate-energy-economy interactions, asset pricing (term structure of interest rates), and machine learning applications in forecasting. Current teaching includes Masters-level courses in Applied Time Series Econometrics, Fixed Income Analysis, and Causal Inference. He has supervised over 45 Ph.D. and 170 Masters theses, primarily in finance and econometrics. Key awards include Research Fellowships at DFI and CoRE, and external assessor roles at Danish universities. Research Fellow, Danish Finance Institute Research Fellow, Center for Research in Energy: Economics and Markets External Fellow, University of Essex His academic activities include organizing conferences like the Danish Doctoral School of Finance and visiting Harvard University as an external researcher (2006-2007). Collaborations involve interdisciplinary work on emissions, energy markets, and financial risk modeling.

Claus Graffمشاهده پروفایل

استاد

• Atrial Fibrillation
• Electrocardiogram Analysis
• Cardiac Resynchronization Therapy
• +۴ مورد دیگر

Claus Graff is a Professor at Aalborg University, affiliated with the Department of Health Science and Technology within The Faculty of Medicine. He leads projects such as the Danish Nationwide ECG Cohort and The LOOP Study, focusing on atrial fibrillation, electrocardiography, and cardiovascular outcomes. His work contributes to UN Sustainable Development Goals related to health and well-being. He holds editorial roles at Scientific Reports (Cardiology) and serves on committees like the Videnskabsetisk Komite Nordjylland and Bestyrelsen for Danish Cardiovascular Academy. His research interests include atrial fibrillation mechanisms, implantable devices, and cardiac resynchronization therapy. Dr. Graff has published 284+ articles, emphasizing atrial fibrillation detection, ECG analysis, and stroke prevention. His work highlights circadian rhythm impacts, ECG biomarkers for dementia, and AI-driven ECG interpretation. Notable achievements include the Research Talent Award and Danish Medical Device Award. His grants include the Sapere Aude Award and collaborations with institutions like Aalborg University and the Independent Research Fund Denmark. He oversees datasets like PTB-XL+, advancing ECG feature analysis.

Peter Loof Møllerمشاهده پروفایل

پژوهشگر ارشد

• Coronary Artery Disease
• Genetics
• Proteomics
• +۵ مورد دیگر

Peter Loof Møller is a Research Fellow at the Department of Health Science and Technology, Faculty of Medicine, Aalborg University. His research focuses on the intersection of genetics, proteomics, and cardiovascular disease, particularly coronary artery disease. Dr. Møller's research interests span multiple areas of genomic medicine with emphasis on Coronary Artery Disease , Genetics , Proteomics , and Genome-Wide Association Studies . His work integrates genetic and proteomic data to improve risk prediction and diagnosis of cardiovascular conditions. His research has significant implications for precision medicine approaches in cardiology, particularly in identifying high-risk patients and developing personalized diagnostic strategies. Analysis of Dr. Møller's recent publications reveals a strong focus on integrating polygenic risk scores with proteomic data to enhance cardiovascular risk assessment. His work demonstrates how genetic variants influence plasma protein levels and how these relationships can be leveraged for early detection of coronary artery disease. The research spans multiple methodologies including genome-wide association studies, whole-genome sequencing, and targeted proteomics, with applications in patient stratification and diagnostic improvement. Dr. Møller has been actively involved in significant collaborative research projects, as evidenced by his extensive publication record and dataset contributions. His work has received attention across multiple platforms with news coverage and academic discussion. His research group focuses on genomic medicine applications in cardiovascular disease, utilizing advanced genomic and proteomic techniques to unravel the molecular mechanisms underlying coronary artery disease. The team employs multi-omics approaches to develop improved diagnostic and risk prediction tools for clinical implementation.

• Emergency Medicine
• Acute Medicine
• Risk Stratification
• +۱۰ مورد دیگر

Mikkel Brabrand is a medical doctor and active researcher in emergency and acute medicine, affiliated with the University of Southern Denmark (SDU) and Odense University Hospital (OUH). He serves as Head of Research at the Research Unit of Emergency Medicine (Odense) and also leads the SDU Climate Cluster. His work bridges clinical practice, epidemiology, and digital health innovation. His research interests focus on risk stratification using abnormal vital signs, emergency department operations, and the application of digital sensors and AI in acute care. He is deeply involved in randomized controlled trials and large-scale observational studies, with a strong emphasis on improving early diagnosis and treatment in emergency settings. The recent articles highlight a trend toward integrating advanced monitoring technologies—such as remote photoplethysmography, infrared thermography, and wearable sensors—into emergency care. His work spans clinical trials (e.g., BLOCK, VASOSHOCK), digital health protocols (FUSE), and climate-health modeling, reflecting a multidisciplinary approach to modern emergency medicine. AstraZeneca Research Prize in Acute Medicine (2013) Brabrand has supervised multiple PhD and research projects, including those on pulmonary embolism diagnostics and patient deterioration prediction. He has contributed to grant-funded research on vasopressor use, climate impacts on hospital demand, and point-of-care ultrasound. His teaching includes research methods and statistics at the Chinese University of Hong Kong and local training in acute care. He is involved in several research groups and projects, including the VASOSHOCK trial, PRIME ultrasound study, and climate-health modeling. His work is supported by cross-institutional collaborations and integrates data science, clinical medicine, and public health.

• Robotics
• Robotic Assembly
• Pose Estimation
• +۷ مورد دیگر

Aljaz Kramberger is an Associate Professor at the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), where he is a key member of SDU Robotics. His work bridges robotics, artificial intelligence, and industrial automation, with a strong focus on robotic assembly, vision-based pose estimation, and human-robot interaction. He actively contributes to both research and education within the robotics domain. Research Interests: His research spans several advanced topics in robotics, including reinforcement learning for robotic assembly, domain randomization, task planning under uncertainty, and low-code programming frameworks for robot motion. He investigates how robots can generalize skills across tasks and environments, particularly in industrial settings. His work emphasizes robust perception, decision-making under uncertainty, and seamless human-robot collaboration in manufacturing contexts. The recent articles reflect a strong trend toward intelligent, adaptive robotic systems that learn from simulation and generalize to real-world tasks. Key themes include policy learning for assembly, uncertainty-aware pose estimation, domain-specific languages for robot programming, and social aspects of HRI in industrial environments. These works demonstrate a consistent focus on bridging simulation and reality, improving task reliability, and enhancing usability in robotic automation. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: Dr. Kramberger supervises multiple PhD students and is involved in several major research projects. He is the principal supervisor for PhD projects on generative factory optimization in the industrial metaverse and robot control for deformable parts. He is also co-PI on a project focused on low-code programming for mobile robotics, and a project participant in EU-funded initiatives like Fluently and FERA, which aim to advance fast, efficient, and socially fluent robotic automation. These projects are supported by Novo Nordisk, EU funding, and national research councils. Labs and Teams: He is embedded in the SDU Robotics group at the Maersk Mc-Kinney Moller Institute, a leading center for robotics research in Denmark. He collaborates closely with researchers such as Norbert Krüger, Leon Bodenhagen, and Thiago R. Silva. His work is highly collaborative, involving interdisciplinary teams focused on industrial robotics, AI integration, and human-centered automation.

Jonas Petersمشاهده پروفایل

استاد

• Causality
• Machine Learning
• Earth System Science
• +۵ مورد دیگر

Jonas Peters is a Professor of Statistics at ETH Zurich, Switzerland, since 2023. Previously, he held positions at the University of Copenhagen and the Max Planck Institute for Intelligent Systems. His research focuses on causal inference, machine learning, and distribution generalization. He earned his PhD from ETH Zurich and the Max Planck Institute, with earlier studies at the University of Heidelberg and the University of Cambridge. His research interests span causal discovery, machine learning applications in Earth system science, and developing statistical methods robust to distributional shifts. Notable contributions include foundational work on causal inference frameworks, such as the Elements of Causal Inference book and the invariant prediction method. Peters has been recognized with awards like the Test of Time Award (runner-up) at ICML 2022 and the ASA Causality in Statistics Education Award. His work bridges theory and practice, emphasizing real-world applications. Peters has supervised numerous PhD students and postdocs, contributing to advancements in causal learning algorithms and statistical testing. His open positions and community service reflect his commitment to fostering academic collaboration and sustainability in academia. Education: PhD in Mathematics, ETH Zurich and Max Planck Institute (2012) MSc/MPhil Mathematics, University of Cambridge (2007) BSc Mathematics, University of Heidelberg (2006) Peters' publications address causal structure recovery, kernel methods for independence testing, and time series analysis. His work emphasizes causal reasoning in machine learning and climate science, with applications to policy learning and dynamical systems. He is an active member of statistical societies and serves on editorial boards of leading journals. His outreach efforts include popular science articles and books like The Raven's Hat , aiming to make complex concepts accessible. Peters advocates for sustainable academic practices, notably reducing travel for environmental reasons since 2020.