جست‌وجوی استاد و پژوهشگر

• 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).

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.

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 .

• Natural Language Processing
• Interpretability of Language Models
• Explainability Methods
• +۴ مورد دیگر

Pepa Kostadinova Atanasova is a Tenure Track Assistant Professor in the Natural Language Processing Section of the Department of Computer Science , University of Copenhagen. She co-leads the CopeNLU group with Isabelle Augenstein and has special teaching duties for industry practitioners. Research Interests: Interpretability of Language Models Explainability Methods Factuality in Language Models Parametric Knowledge Analysis Human-AI Alignment Trustworthy AI Scientific Awards: Marie Skłodowska-Curie Fellowship ELLIS Best PhD Thesis Award Informatics Europe Best PhD Thesis Award Collaborations: Active in interdisciplinary research, including partnerships with Meta and Google, and a postdoctoral project combining language model explanations with trading behavior analysis.

Olga Saukhمشاهده پروفایل

دانشیار

• Efficient Machine Learning
• Deep Learning
• Embedded Systems
• +۱۲ مورد دیگر

Olga Saukh is an Associate Professor at the Institute of Technical Informatics, Graz University of Technology (TU Graz), and a Faculty member at the Complexity Science Hub Vienna (CSH). She leads the Embedded Learning and Sensing Systems research group, which operates across both institutions, focusing on the design and deployment of efficient AI-based systems on edge and mobile platforms. Her work bridges deep learning and embedded systems, with applications in environmental monitoring, precision agriculture, and digital health. Ph.D. in Computer Science, University of Bonn (2009) Habilitation in Embedded Systems, TU Graz (2020) Postdoctoral Training, ETH Zurich (2010–2016) B.Sc. in Applied Mathematics, Taras Shevchenko National University of Kyiv (2002) M.Sc. in Applied Computer Science, University of Freiburg (2004) Her research centers on efficient machine learning, particularly model optimization, neural network pruning, and contrastive learning for resource-constrained devices. She is deeply engaged in solving real-world challenges in IoT, sensor networks, and cyber-physical systems. Her work emphasizes data privacy, sustainability, and practical deployment of AI at the edge. The 15 most recent publications highlight a strong trend in efficient deep learning, including model compression, pruning, and transfer learning, applied to diverse domains such as environmental sensing (air quality, pollution tracking), digital agriculture (cattle farming), and embedded AI (sensor calibration, on-demand sensing). Her work frequently appears in top-tier venues like NeurIPS, ICLR, and IEEE/ACM IPSN, reflecting her leadership at the intersection of machine learning and embedded systems. Scientific awards include: CONET Ph.D. Academic Award (2010) Multiple Best Paper Awards at IEEE PerCom, ACM/IEEE IPSN, IEEE ICPADS, IEEE SECON, and UrbCom Spotlight and Oral presentations at ICML and CoLLAs workshops Ph.D. scholarship from IPVS, University of Stuttgart (2004–2005) Prizes in Ukrainian national mathematics competitions (1996–1998) Olga Saukh actively serves on program committees of leading international conferences in machine learning and embedded systems. She has advised multiple students and leads a collaborative research group spanning TU Graz and CSH Vienna. Her group develops practical AI systems for real-world deployment, with a focus on sustainability and privacy. She co-organizes the public EfficientML reading group and has secured recognition through numerous grants and awards. Her future work continues to explore the theoretical and practical challenges of deploying efficient, trustworthy AI in mobile and embedded environments. Her research group, Embedded Learning and Sensing Systems, operates jointly between TU Graz and CSH Vienna, fostering interdisciplinary collaboration across institutions. The team develops AI solutions for edge computing, sensor networks, and cyber-physical systems, with a strong emphasis on environmental sustainability and data privacy. Members work on joint challenges using advanced collaboration tools, reflecting the distributed nature of modern academic research.

Jan Madsenمشاهده پروفایل

استاد

• Embedded Systems
• Cyber-Physical Systems
• Microfluidic Biochips
• +۵ مورد دیگر

Jan Madsen is a Professor at DTU Compute, Technical University of Denmark, and Head of the Embedded Systems Engineering section. His research focuses on system-level modeling and design of embedded computing systems, particularly cyber-physical systems, microfluidic biochips, and synthetic biology applications. Develops design automation tools and methodologies for embedded systems Supervises numerous PhD students and leads major research projects Research Interests Key areas include: Embedded systems-on-a-chip Cyber-Physical Systems (Internet-of-Things) Microfluidic Lab-on-Chip devices Synthetic biology with molecular computing Design, modeling, and optimization of complex systems Scientific Awards DATE Fellow (2019) IEEE CEDA Outstanding Recognition (2019) DTU Scientific Advise Award (2013) Best Paper Awards at MECO (2013) and CASES (2009) Jorck’s Foundation Research Award (1995) Publications His 14+ journal papers and 115+ conference papers demonstrate expertise in: SystemC-based modeling frameworks Energy-aware sensor networks Self-healing eDNA architectures Microfluidic biochip synthesis RTOS modeling and MPSoC exploration

• Longitudinal Data Analysis
• Time-to-Event Analysis
• Survival Analysis
• +۵ مورد دیگر

Alessandra Meddis serves as an Assistant Professor in the Section of Biostatistics within the Department of Public Health at the University of Copenhagen's Faculty of Health and Medical Sciences. Her academic work centers on developing and applying advanced statistical methodologies for longitudinal and time-to-event data analysis, with significant contributions to public health research in Denmark and internationally. Her institutional affiliation is clearly established through university contact details and departmental listings. Her primary research interests include correlated survival data analysis, competing risk modeling, informative cluster size methodology, causal inference techniques for observational studies, and environmental epidemiology applications. Dr. Meddis has developed specialized expertise in handling complex survival data structures while maintaining focus on real-world public health problems, particularly in HIV comorbidity patterns, environmental exposure effects, and pandemic-related mortality analyses. Her methodological innovations directly address challenges in clustered and censored data common across medical research domains. Analysis of Dr. Meddis's recent publication record reveals a consistent trajectory of high-impact interdisciplinary research spanning clinical medicine, epidemiology, and statistical methodology. Her work appears in leading journals across biostatistics, infectious diseases, and public health, demonstrating strong collaborative networks with clinical researchers and epidemiologists. Key thematic areas include HIV treatment outcomes, environmental health exposures, and critical care applications during the pandemic, with recent methodological papers advancing survival analysis techniques for complex data structures. Scientific Awards: No scientific awards were specified in the available institutional profile. Advising and Grants: The institutional profile does not provide details regarding graduate student supervision or specific research grant funding. Her collaborative publications suggest involvement in multi-investigator projects including the COCOMO HIV cohort study and pandemic-related research initiatives. Labs and Teams: Dr. Meddis is affiliated with the Section of Biostatistics within the Department of Public Health, though specific laboratory facilities or dedicated research teams are not described in the source material. Her extensive co-authorship patterns indicate active participation in multiple research consortia across medical specialties.

Aage Hill-Madsenمشاهده پروفایل

دانشیار

• Translation Studies
• Medical Communication
• Systemic Functional Grammar
• +۵ مورد دیگر

Aage Hill-Madsen is an Associate Professor at the Department of Culture and Learning, Aalborg University (Denmark), affiliated with the Communication, Language, and Discourse (CLD) research unit. His work focuses on translation studies, medical communication, and systemic-functional linguistics. He holds a Cand.mag. et ling.merc. and a PhD in English linguistics. Research Interests: Translation theories (especially intralingual translation) Medical terminology simplification and communication Systemic-functional grammar applications Legitimation Code Theory in educational contexts Genre analysis of specialized texts Semiotic approaches to knowledge transmission Recent Publications Trends: His 2024-2025 work emphasizes medical translation between technical and lay audiences, with studies on EPAR summaries, patient information leaflets, and historical East-West medical terminology exchanges. He combines functionalist translation theory with systemic-functional frameworks to analyze textual transformations. Grants & Projects: Participated in the 2024-ongoing project Udvikling af kommunikative kompetencer gennem frivilligt brobygningsarbejde i NGO’en Social Sundhed , exploring communication skills through NGO activities. Academic Engagement: Active peer reviewer for journals like Globe and Across Languages and Cultures , with conference presentations on intralingual translation strategies and medical text accessibility.

Roberta Sinatraمشاهده پروفایل

استاد

• Computational Social Science
• Network Science
• Data Science
• +۳ مورد دیگر

Roberta Sinatra is a Professor in Social Data Science at the University of Copenhagen, with part-time affiliations at ITU Copenhagen, ISI Foundation (Italy), and CSH (Austria). She co-founded the NERDS Research Group at ITU and co-leads the Pioneer Centre for AI in Copenhagen. Research Interests: Her work spans computational social science, network science, and data science, focusing on fairness in AI, scientific careers, and human mobility. Recent projects include analyzing child protection algorithms and modeling urban bicycle networks. Scientific Awards: ERC Consolidator Grant Villum Young Investigator Grant Complex Systems Society Junior Prize DPG Young Scientist Award for Socio- and Econophysics Sapere Aude: Starting Grant Publications: Her research, often in top-tier venues like Nature and Science , explores interdisciplinary themes, including AI ethics, gender disparities in science, and social network dynamics. Labs & Teams: She leads research initiatives at the Center for Social Data Science (KU) and co-founded the NERDS Research Group at ITU, fostering international collaboration in network science and AI ethics.

Sascha Struweمشاهده پروفایل

پژوهشگر ارشد

• Service Innovation
• Service Design
• Value Co-Creation
• +۴ مورد دیگر

Sascha Struwe serves as a Postdoctoral Researcher at Aalborg University Business School within the Faculty of Social Sciences and Humanities, actively contributing to the International Business Research Group. Based at Fibigerstræde 11 in Aalborg Øst, Denmark, Struwe operates at the intersection of service innovation theory and business practice with international focus. Research expertise centers on service innovation , value co-creation , and digital servitization , particularly examining B2B contexts and open banking ecosystems. Work consistently explores institutional influences through German-Chinese case studies, addressing how cultural and regulatory frameworks shape service design. Recent trajectories reveal evolution from foundational service design challenges (2019-2021) toward digital transformation implications (2022-2023), with emphasis on value co-destruction mechanisms in financial ecosystems. Struwe led the PhD project Innovating the Invisible and Intangible: Value Creation in B2B service (2018-2021) investigating co-creation capabilities across industrial sectors. Academic engagement includes conference participation at EIBA and CICALICS events, plus a visiting researcher appointment at Fudan University's Nordic Centre (2019-2020). Current work continues through the International Business Research Group, focusing on digital literacies and service ecosystem resilience.

Diego Garlaschelliمشاهده پروفایل

استاد

• Network Theory
• Statistical Physics
• Econophysics
• +۷ مورد دیگر

Diego Garlaschelli is Professor of Theoretical Physics at the IMT School for Advanced Studies in Lucca, Italy, and at the Lorentz Institute for Theoretical Physics, University of Leiden, the Netherlands. He leads the NETWORKS research unit at IMT and the Econophysics and Network Theory group at Leiden. He is also an external faculty member at the Complexity Science Hub in Vienna and an associate member of the Enrico Fermi Research Center in Rome. His affiliations reflect a strong international and interdisciplinary research profile in network science and statistical physics. He holds a master's degree in theoretical physics from the University of Rome III (2001) and a PhD in Physics from the University of Siena (2005). His postdoctoral experience includes positions at the Australian National University, the University of Siena, the University of Oxford, and the Sant’Anna School of Advanced Studies in Pisa. Garlaschelli’s research spans network theory, statistical physics, econophysics, financial complexity, ecological networks, and social dynamics. He applies maximum entropy models, information theory, and random graph frameworks to understand complex real-world systems. His teaching includes courses in Network Theory, Econophysics, and Complex Systems at both PhD and MSc levels. The 15 most recent publications highlight a consistent focus on network reconstruction, ensemble inequivalence, renormalization, and applications to financial and socio-economic systems. Key themes include statistical inference in networks, resilience, and multi-scale modeling, with publications in top journals such as Nature Reviews Physics , Physics Reports , Science , and Physical Review Letters . His scientific awards include the Best Paper Award at the 6th International Workshop on Self-Organizing Systems (2012) and the Jan Kijne Prize (2013) as supervisor. He has secured multiple grants from NWO, the European Union, and the Royal Society, and has supervised over 40 students at PhD, master’s, and bachelor’s levels. He also mentors postdocs and visiting scientists. Garlaschelli leads and organizes major international workshops and schools in network science and complex systems. He serves on scientific committees and is an active referee for journals like Nature and Physical Review Letters , as well as funding agencies including the ERC and NWO.

• Comparative Public Policy
• Innovation Studies
• Science of Science
• +۴ مورد دیگر

Claudia Acciai is a Guest Researcher at SODAS (Sociology Department) at the University of Copenhagen, where she works on the research project "Quantifying institutional and country-related Matthew effects in science." She holds a PhD in Political Science and Sociology from the Scuola Normale Superiore, with a dissertation focused on policy design in the Research and Innovation sector. Her academic journey includes research visits at Alliance Manchester Business School, Science Po Paris, and Copenhagen Business School. Her research interests lie at the intersection of comparative public policy, innovation studies, and science of science. She combines computational and experimental methods with qualitative content analysis techniques to examine policy design, institutional effects in science, and research evaluation. Her work frequently addresses how policy instruments function in complex governance environments and investigates gender-related differences in academic publishing. Analyzing her recent publications reveals a strong focus on the science of science, with particular attention to bibliometrics, policy instrument effectiveness, and gender dynamics in academic careers. Her work spans multiple disciplines including political science, sociology of science, and innovation studies, often employing mixed-methods approaches that combine quantitative analysis with qualitative insights. Acciai is an active member of the Knowledge, Organization and Politics research group at the Department of Sociology. Her collaborations span multiple countries and institutions, reflecting the international nature of her research on comparative policy and science studies. She has conducted significant work for research projects funded by the Italian Ministry of Education, including analyses of policy analysis capacity in Italian policymaking and governance changes in higher education systems.

Jens S. Andersenمشاهده پروفایل

استاد

• Proteomics
• Quantitative Mass Spectrometry
• Cell Biology
• +۱۱ مورد دیگر

Jens S. Andersen is a Professor in the Department of Biochemistry and Molecular Biology at the University of Southern Denmark, where he leads research in Biomedical Mass Spectrometry and Systems Biology. His work is centered on the development and application of quantitative mass spectrometry and microscopy-based proteomics to study human cell biology, particularly the structure and function of organelles such as centrosomes, cilia, autophagosomes, and mitochondria. His research focuses on determining the protein composition and dynamic properties of cellular organelles, the roles of specific protein groups, and their contributions to biological processes and diseases. He investigates cell signaling mediated by post-translational modifications, especially within the DNA damage response, autophagy, and immune systems. His lab, the Jens S. Andersen Lab, is part of the Research Section of Biomedical Mass Spectrometry. The analysis of his recent publications reveals a strong interdisciplinary trend combining proteomics, structural biology, and cell signaling. His work spans cilia biology, RNA metabolism, DNA repair, and cancer mechanisms, with frequent use of advanced techniques like mass spectrometry, CRISPR, and live-cell imaging. The integration of systems biology approaches is evident across his research outputs. Professor, Department of Biochemistry and Molecular Biology, University of Southern Denmark Head of Research, Biomedical Mass Spectrometry and Systems Biology Principal Investigator, Jens S. Andersen Lab ORCID: 0000-0002-6091-140X While no specific scientific awards are mentioned in the provided texts, his extensive publication record in high-impact journals such as Science , Nature Communications , Molecular Cell , and EMBO Journal reflects significant scholarly contributions. He has supervised research projects and collaborated widely across Europe, though specific names of students are not listed. His research is supported by multiple ongoing projects, reflecting sustained funding and academic leadership. The Jens S. Andersen Lab operates at the intersection of proteomics and cell biology, contributing to fundamental understanding of organelle dynamics and disease mechanisms. The lab's work is highly collaborative, involving partnerships with groups in structural biology, RNA research, and cancer biology.

• Machine Learning
• Bioinformatics
• Deep Generative Models
• +۳ مورد دیگر

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

Francesco Rosatiمشاهده پروفایل

دانشیار

• Sustainable Entrepreneurship
• Business Model Innovation for Sustainability
• Corporate Sustainability Management
• +۳ مورد دیگر

Francesco Rosati is an Associate Professor at the Department of Management Engineering, Technical University of Denmark (DTU), affiliated with the Centre for Technology Entrepreneurship. His work focuses on the intersection of entrepreneurship, innovation, and sustainable development, particularly addressing the UN Sustainable Development Goals (SDGs). He holds academic qualifications in management and engineering and has mentored numerous Danish and international startups. Rosati has been recognized with the Tietgen Award 2020 for early-career contributions to business-oriented social sciences. Research interests include corporate sustainability management, business model innovation for sustainability, and organizational silos analysis. His work spans multiple sectors, including healthcare and construction industries. Rosati teaches courses on strategy, entrepreneurship, and sustainability at both Master’s and executive education levels, and actively participates in global conferences. Key projects include accelerating SDG-aligned entrepreneurship education, circular business model innovation in construction, and building climate resilience for vegetable farmers in Ghana. His research has been published in journals like Business Strategy and the Environment , Journal of Cleaner Production , and Organization and Environment . Rosati has supervised several PhD students exploring topics such as entrepreneurial resilience, SDG reporting, and business model innovation. His work emphasizes bridging management and engineering disciplines to address global sustainability challenges.