جست‌وجوی استاد و پژوهشگر

Jan Østergaardمشاهده پروفایل

استاد

• AI and Sound
• Acoustic Signal Processing
• Information Theory
• +۴ مورد دیگر

Jan Østergaard is a Full Professor in Information Theory and Signal Processing at Aalborg University's Department of Electronic Systems. He leads the AI and Sound research section and directs the CASPR center. His expertise spans AI-driven acoustic signal processing, information theory, and EEG signal analysis. Østergaard holds a M.Sc. from Aalborg University and a PhD (cum laude) from Delft University of Technology. Major awards include the Danish Young Researcher’s Award and a EURASIP Best Thesis honor. His work focuses on speech enhancement, sound zone technologies, and neural tracking of auditory attention. Recent research emphasizes low-latency speech transmission, deep learning for sound field control, and robust voice activity detection. He serves on editorial boards and national committees, advancing Denmark’s sound technology initiatives. Education: M.Sc. (Aalborg, 1999), PhD (Delft, 2007) Research interests emphasize practical AI applications in sound systems, including hearing aid improvements, data-efficient acoustic modeling, and feedback control in networked systems. Over 210 publications and 17 active projects reflect his interdisciplinary impact across academia and industry.

• Bioinformatics
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

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).

• Quantum Information
• Quantum Optics
• Quantum Communication
• +۳ مورد دیگر

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.

• Stochastic programming
• Two-phase and multi-phase models
• Scenario generation and reduction
• +۹ مورد دیگر

Trine Krogh Boomsma is a Professor in the Department of Insurance and Economics at the University of Copenhagen's Department of Mathematical Sciences. Her research focuses on optimization under uncertainty with significant applications in energy systems, particularly electricity markets, renewable energy investments, and power system planning. PhD in Mathematics-Economics, Aarhus University (2003-2007) Visiting PhD at University of Duisburg-Essen (2004) Academic career includes positions at Risø National Laboratory for Renewable Energy and Imperial College London Her work spans stochastic programming, real options analysis, and dynamic programming to address energy sector challenges. Key areas include support schemes for renewables, market risk modeling, and operational optimization of hybrid conventional-renewable systems. Recent research explores policy impacts on investment decisions and advanced scenario generation techniques. Major publications (2012-2020) cover renewable energy policy frameworks, power plant valuation models, and sequential market bidding strategies. These works emphasize electricity market dynamics, investment risk quantification, and robust planning under uncertainty. She teaches linear programming, integer programming, and stochastic programming applications in operational analysis, contributing to energy economics education at the department.

• Neuroscience
• Alzheimer's Disease
• Metabolism
• +۲ مورد دیگر

Aisha Ameen is a Researcher in the Department of Veterinary and Animal Sciences (Pathobiological Sciences) at the University of Copenhagen's Faculty of Health and Medical Sciences, holding dual appointments as Research Assistant and Guest Researcher. Her research centers on Alzheimer's disease mechanisms with emphasis on astrocyte metabolism, glucose/glutamate dynamics, and short/medium-chain fatty acid roles. She employs functional metabolic mapping, dMRI, immunohistochemistry, and hiPSC models to investigate neurodegenerative processes at cellular and systemic levels. Analysis of her 2022-2025 publications reveals consistent focus on metabolic dysregulation in Alzheimer's pathology, particularly astrocyte energy substrate competition and fatty acid interventions. Her work bridges neuroscience, metabolism, and translational disease modeling with significant citation impact and media attention.

Seth Lloydمشاهده پروفایل

استاد

• Quantum Information Science
• Quantum Computation
• Quantum Communications
• +۵ مورد دیگر

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.

• RNA Biology
• Bioinformatics
• Plant Molecular Biology
• +۴ مورد دیگر

Peter Brodersen is a Professor at the Department of Biology, University of Copenhagen , specializing in Bioinformatics and RNA Biology . His research focuses on RNA modification (m6A), YTHDF proteins, and small RNA pathways in plants. Recent research trends from his group include: (1) molecular mechanisms of ARGONAUTE-small RNA interactions, (2) m6A-YTHDF regulatory systems in plant development, and (3) RNAi-independent roles of DICER-LIKE proteins in antiviral defense. Collaborations span Denmark and international institutions. Publications highlight cross-disciplinary work bridging computational biology and experimental plant genetics. Key subfields include RNA structure, epigenetic regulation, and antiviral immunity.

• Natural Language Processing
• Machine Learning
• Artificial Intelligence Ethics
• +۳ مورد دیگر

Anders Søgaard is a Professor at the University of Copenhagen , affiliated with both the Department of Computer Science and the Department of Communication. His research bridges Natural Language Processing and Machine Learning with a focus on AI ethics , explainability , and human-AI interaction . Primary Affiliation: Department of Computer Science, University of Copenhagen Secondary Affiliation: Department of Communication, University of Copenhagen Email: soegaard@di.ku.dk, soegaard@hum.ku.dk Research Interests His work spans Natural Language Processing , Machine Learning , and AI ethics , with recent studies addressing: Trustworthiness in AI systems Explainable AI (XAI) frameworks Multilingual model fairness and alignment Human-AI collaboration in reasoning tasks Ethical implications of social robots Mental health analytics using ML Recent Publications His 2025 output highlights trends in: AI ethics (e.g., fairness metrics, trustworthy systems) Multilingual model analysis (knowledge retention, cross-lingual transfer) Human-centric AI (gaze data, cultural considerations) Applications in healthcare and social good

Bhaskar Reddy Sudireddyمشاهده پروفایل

دانشیار

• Solid Oxide Fuel Cells
• Materials Science
• Electrochemistry
• +۴ مورد دیگر

Bhaskar Reddy Sudireddy is an Associate Professor in the Department of Energy Conversion and Storage at the Technical University of Denmark (DTU). His research focuses on advanced materials for energy technologies, including solid oxide fuel cells, electrocatalysts, and ceramic processing. He contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and industry innovation (SDG 9). His work emphasizes the development of high-performance electrodes, metal-supported solid oxide cells, and gas sensors. He leads projects on eco-friendly fabrication methods for energy storage systems and collaborates on piezoelectric materials sintered in humid air. His research group, Applied Ceramics and Processing, explores novel ceramic materials for applications in renewable energy and environmental monitoring. Advises five PhD students working on projects like high-temperature electrolysis cells and antiferroelectric materials. Supervises interdisciplinary research spanning electrochemistry, materials synthesis, and device fabrication. Located at DTU’s campus in Kgs. Lyngby, Denmark, with extensive international collaborations.

• Machine Learning
• Data Privacy
• Robust Learning
• +۳ مورد دیگر

Amartya Sanyal is a Tenure Track Assistant Professor at the Department of Computer Science (DIKU), University of Copenhagen, specializing in Machine Learning. He also serves as an Adjunct Professor at the Indian Institute of Technology Kanpur (2023–2025). His research focuses on critical areas of AI safety, data privacy, and robust learning. University: University of Copenhagen Department: Department of Computer Science Academic Rank: Assistant Professor Adjunct Role: IIT Kanpur (2023–2025) His work addresses challenges like differential privacy , data poisoning attacks , machine unlearning , and robust mixture learning . Recent publications analyze privacy-preserving techniques for large language models, fairness in collective action algorithms, and certified data release mechanisms. Amartya has received the Villum Young Investigator Award (2025). His research outputs emphasize online learning , adversarial robustness , and privacy-utility tradeoffs through rigorous theoretical frameworks and practical implementations. Scientific Award: Villum Young Investigator Award His collaborations span institutions like IIT Kanpur and involve interdisciplinary projects with industry partners. Current activities include talks on privacy with correlated data and machine unlearning advancements.

• Ethnology
• Migration Studies
• Refugee Studies
• +۳ مورد دیگر

Marie Sandberg is an Associate Professor in the Promotion Programme at the Saxo Institute, University of Copenhagen. She is affiliated with the Faculty of Humanities and participates in HUM:Global initiatives focused on interdisciplinary global studies. Her research emphasizes ethnological analyses of migration, borders, and refugee policies, particularly exploring temporal governance, state-civil society interactions, and the paradoxes of welfare-state frameworks. Her work examines the everyday practices of refugees and volunteers in contexts of temporary protection status, as well as the ethical challenges in digital migration studies. She contributes to debates on deterrence policies, repatriation agendas, and the precarity of academic labor. Sandberg’s research methodologies often combine ethnography with critical analysis of policy frameworks. Key Research Themes: Refugee temporariness, border studies, humanitarianism, and academic precarity Professional Roles: Member of the Professional Project Group (PPG) in HUM:Global, coordinating interdisciplinary projects Geographic Focus: Europe, with emphasis on Denmark, Poland, and Germany Recent publications highlight her focus on the interplay between state policies and grassroots efforts, as well as the temporal dimensions of displacement. She has co-edited special issues on migration and authored studies on volunteerism in refugee relief work.

Aberham Hailu Feyissaمشاهده پروفایل

دانشیار

• Food Process Engineering
• Heat and Mass Transfer
• Transport Phenomena in Porous Media
• +۷ مورد دیگر

Aberham Hailu Feyissa is an Associate Professor at the National Food Institute of the Technical University of Denmark , specializing in process modeling and sustainable food engineering. His research bridges complex transport phenomena with practical food manufacturing challenges. Ph.D. in Food Process Engineering, Technical University of Denmark MSc in Food Science, K.U.Leuven and Universiteit Gent BSc in Chemical Engineering, Bahir Dar University His work focuses on coupled mass and heat transfer during solid food processing, aiming to develop robust first-principles models for predictive process optimization. Key applications include Ohmic heating , digital twin technology , and bioactive ingredient extraction . Recent publications highlight his contributions to sustainable food processes , including insect-based feed modeling , seaweed bread kinetics , and clean-label cheese formulation . His methodological innovations span FTIR spectroscopy , computational fluid dynamics , and kinetic modeling . Supervisor for PhD students S. S. Turgut , M. E. Jabali , and Dahal S. Principal Investigator for projects like Modelling and Digitalisation of Food Processes and Sustainable Extraction of Bioactive Insect Fractions Active in conference presentations and peer review , he drives advancements in food process understanding through mechanistic modeling and mathematical simulation .

Arthur Merkelمشاهده پروفایل

پژوهشگر ارشد

• Membrane Technology
• Dairy Science
• Electrochemical Processes
• +۳ مورد دیگر

Arthur Merkel is a Research Fellow in the Department of Food Science at the University of Copenhagen, specializing in membrane and electromembrane processes for the dairy industry. His research focuses on electro-chemical membrane systems, including electrodialysis and bipolar membrane electrodialysis, for applications in dairy processing and sustainable food production. His primary research interests include membrane technology for dairy science, particularly in the areas of whey processing, electro-acidification, and demineralization. He investigates fouling and scaling of ion-exchange membranes and promotes green and sustainable science in food engineering. His work bridges fundamental electrochemical processes with industrial dairy applications. Recent publications (2021-2025) demonstrate a strong trend in applying electrodialysis and bipolar membrane electrodialysis to dairy streams such as skim milk and whey, with a focus on improving process efficiency, valorizing byproducts, and addressing challenges like fouling and scaling. His research integrates experimental and modeling approaches to optimize membrane processes for sustainable dairy production. Merkel actively contributes to the scientific community through peer review for several journals: Desalination Separation and Purification Technology Future Foods He is a member of the European Membrane Society and the Czech Membrane Platform, and has participated in conferences including EuroMembrane 2022 and the European Membrane Summer School (2024).

Allan Larsenمشاهده پروفایل

استاد

• Operations Research
• Supply Chain Management
• Logistics
• +۴ مورد دیگر

Allan Larsen is a Professor and Deputy Head of Division at the Department of Technology, Management and Economics (DTU Management) at the Technical University of Denmark. He heads the Operations and Supply Chain Management Section. His academic background includes an MSc in Applied Mathematics and a PhD in Operations Research, both from DTU. He teaches courses in Operations Management and Simulation at both undergraduate and graduate levels. Research Focus: His work applies operations research methodologies to complex planning problems in supply chain management, logistics, healthcare operations, and public transport. Key areas include urban freight transport, healthcare supply chains, and optimization of public transport resources like crew and fleets. Collaborations with industries, especially in freight transport, have been extensive. He previously co-directed the Transport DTU research center and co-chaired Denmark’s Transport Innovation Network. Education: MSc in Applied Mathematics (1989–1995), PhD in Operations Research (1997–1999), both from DTU. Recognition: Recipient of the Hedorf’s transportpris award in 2022 for contributions to transport research. Research Projects: Supervises multiple PhD students (e.g., on electric freight transport, healthcare resource optimization, and Industry 4.0 applications). Active in projects like 'Pioneering Electric Heavy-Duty Freight Transport' and 'Resource optimization in healthcare.' Labs/Teams: Leads the Operations and Supply Chain Management research group and collaborates in initiatives like the Transport Innovation Network, focusing on sustainable transport solutions.

Torben M. Andersenمشاهده پروفایل

استاد

• Nordic welfare model
• Public Economics
• Labour Economics
• +۳ مورد دیگر

Torben M. Andersen is a Professor at the Department of Economics and Business Economics, Aarhus University. He holds an M.Sc. from the London School of Economics (1981), a Lic. Oecon from Aarhus University (1994), and a PhD from CORE, Université Catholique de Louvain (1986). His research focuses on the Nordic welfare model, public economics, labour economics, and pension economics. He has published over 400 articles in top journals and contributed to policy advisement for Denmark, the EU, OECD, and the World Bank. He currently chairs the DREAM modelling group, the Economic Council for Greenland, and the Danish pension fund ATP. He also serves on boards of Aarhus University Research Foundation, Systemic Risk Council Faroe Islands, and others. Key research areas include welfare state sustainability, public expenditure prioritization, and pension reform impacts. His recent work explores mortality risk hedging and wealth inequality dynamics. He is a fellow at CEPR, IZA, and CESifo.