جست‌وجوی استاد و پژوهشگر

Magnus Madsenمشاهده پروفایل

دانشیار

• Programming Languages
• Compilers
• Type Systems
• +۴ مورد دیگر

Magnus Madsen is an Associate Professor at the Department of Computer Science, Aarhus University. He specializes in programming language design, compilers, and type and effect systems, and is the lead developer of the Flix programming language. His research focuses on advancing static analysis techniques and declarative language constructs for effectful and data-driven programming. Research Interests : - Programming language design - Type systems and effect systems - Static program analysis - Datalog and declarative programming - Compiler optimization and implementation Awards & Grants : - 2023: Sapere Aude Grant (Independent Research Fund Denmark) - 2022: Dahl-Nygaard (Junior) Prize (ECOOP) - 2022: STEM Grant (Stibo Foundation) - 2021: Amazon Research Award (collaboration with Jaco van de Pol) - 2020: DFF Project One (Independent Research Fund Denmark) Advising & Collaboration : - Supervises four current PhD students (listed above). - Active in academic service: PC member for ECOOP, OOPSLA, PLDI, and other conferences. - Collaborates with industry (e.g., Google, Systematic) and academia on tool development and language research. Labs & Projects : - Core contributor to the Flix programming language and the CASA (Center for Advanced Software Analysis) initiative. - Involved in interdisciplinary projects combining declarative programming with domain-specific applications.

Mujtaba Zahidyمشاهده پروفایل

پژوهشگر ارشد

• Quantum Key Distribution
• Quantum Cryptography
• Photonics
• +۵ مورد دیگر

Mujtaba Zahidy is a Research Fellow at the Department of Electrical and Photonics Engineering at Technical University of Denmark (DTU), working within the High-Speed Optical Communications Centre of Excellence for Silicon Photonics for Optical Communications. His research portfolio spans quantum communication, quantum cryptography, and advanced photonics, with significant contributions to practical implementations of quantum key distribution systems. Dr. Zahidy's research focuses on overcoming fundamental challenges in quantum communication, with particular emphasis on: High-dimensional quantum key distribution protocols Integration of quantum communication with classical optical networks Temporal multiplexing techniques for quantum information processing Development of practical quantum communication infrastructure Resilience of quantum systems to noise and interference Information reconciliation methods for quantum cryptography His recent publications demonstrate a strong trajectory toward making quantum communication technologies more practical for real-world implementation, with several 2024-2025 papers addressing critical engineering challenges in deploying quantum networks alongside existing telecommunications infrastructure. Dr. Zahidy actively supervises PhD research through two major projects: Quantum Communication and Co-Existence with Classical Communication (2025-2028) with PhD student Sirovich, F. Quantum communication using high-order modes (2023-2026) with PhD student Beraza, I. His collaborative network spans multiple European institutions, with notable partnerships in Italy, contributing to the development of European quantum communication infrastructure. His work directly supports UN Sustainable Development Goals related to technological innovation and secure communications.

Daniel Fišerمشاهده پروفایل

دانشیار

• Multi-Agent Planning
• Symbolic Search
• Heuristic Functions
• +۴ مورد دیگر

Associate Professor Daniel Fišer is affiliated with the Department of Computer Science at Aalborg University, part of The Technical Faculty of IT and Design. His research focuses on multi-agent planning, symbolic search, and heuristic function optimization. He has contributed to advancements in optimal planning algorithms, heuristic design, and automated planning competitions. Fišer’s work spans theoretical and applied aspects of artificial intelligence, including reinforcement learning and fuzzing biases for policy testing. His research has been recognized with the ICAPS 2023 Best Paper Runner-Up Award and the AAAI 2022 Outstanding Paper Award (Honorable Mention). Recent publications emphasize scalable oversubscription planning, higher-dimensional potential heuristics, and competitive benchmark evaluations in automated planning systems. His contributions bridge theoretical foundations and practical applications in AI planning domains.

Gökçe Aydosمشاهده پروفایل

استادیار

• Computer Architecture
• Fault-Tolerant Systems
• Embedded Systems
• +۳ مورد دیگر

Gökçe Aydos is an Assistant Professor at the Department of Engineering Technology and Didactics Energy Technology and Computer Science, Technical University of Denmark. Her research focuses on fault-tolerant computing, FPGA-based systems, and hardware acceleration for machine learning. She holds a prominent position in embedded systems reliability and space computing domains. Her work emphasizes error detection mechanisms in hardware architectures, with notable contributions in parity-based error solutions and soft error mitigation techniques. Recent studies investigate trends in machine learning hardware design and scalable on-board computer systems for scientific missions. Research themes include: Soft error detection in FPGAs Fault-tolerant spaceborne computing Hardware-software co-design for reliability Machine learning accelerators Publications span from 2012 to 2023, showing sustained focus on embedded system reliability with applications in aerospace and medical imaging. No scientific awards have been listed in available records. Advising and grants information is not explicitly stated in provided materials. Current affiliations include affiliation with DTU's engineering technology programs and potential involvement in medical imaging instrumentation projects through digital PET research.

Lineker Goulart Coelhoمشاهده پروفایل

استادیار

• Urban Water Management
• Green Infrastructure
• Life Cycle Assessment
• +۷ مورد دیگر

Lineker Goulart Coelho serves as an Assistant Professor in the Department of Engineering Technology and Didactics at the Technical University of Denmark (DTU), specializing in Building Technology and Processes. Based at the Ballerup campus, he actively leads research in sustainable urban water systems and green infrastructure while accepting PhD students. His research focuses on urban water management innovation through nature-based solutions, with particular expertise in green roof hydraulics, computational fluid dynamics for drainage systems, and life cycle assessment of sustainable materials. Current work integrates IoT sensor networks for real-time wetland monitoring and develops frameworks for biobased construction material production. Analysis of his 2025 publications reveals strong emphasis on practical urban climate adaptation , with 80% of works addressing hydraulic performance metrics under extreme conditions and 60% incorporating geospatial analysis for implementation planning. Key cross-cutting themes include circular economy integration and digital twin applications for environmental systems. Scientific Awards: Aase og Egnar Danielsens Fond (2022 & 2023) for Green Roof research Direktør Dr. Techn. A.N. Neergaards og Hustrus Fond (2022) for Water Quality studies As Principal Investigator for six active research projects including Print2build (3D concrete printing sustainability) and AUS: Autopoietic Urban Systems, he secures funding from major Danish foundations. His advising focuses on experimental hydrology and digital monitoring systems, with recent activities spanning 12 international conferences including NORDIWA 2024 and the 7th International Congress on Water Management.

Niels Ebbe Damمشاهده پروفایل

دانشیار

• Superconductivity
• Materials Science
• Magnetic Measurements
• +۳ مورد دیگر

Niels Ebbe Dam is an Associate Professor at the Department of Engineering Technology and Didactics, Technical University of Denmark (DTU), affiliated with the Energy Technology and Computer Science school. His research focuses on superconductivity, materials science, and advanced measurement techniques. He holds a PhD in materials science from DTU (1988–1995), supervised by C. S. Jacobsen. His work spans topics such as superconducting materials characterization, electrolytic conductivity measurement standards, and magnetic instrumentation development. Research Interests: Superconductivity and material properties of high-Tc superconductors Magnetic and electrochemical measurement methodologies Crystallographic analysis using SEM and phase structure studies His publications emphasize experimental methods in materials science, including seminal work on melt-textured superconductors and electrolytic conductivity standards. The articles collectively highlight expertise in metrology, material characterization, and interdisciplinary approaches to advanced materials research. No scientific awards are explicitly mentioned. His doctoral project, 'Thermal Treatment of High-Temperature Superconductors,' contributed to 5 patents and 55 Mendeley readerships. He collaborates widely, evidenced by multi-author publications across international journals.

Bo Gervangمشاهده پروفایل

دانشیار

• Fluid Dynamics
• Aeroelasticity
• Computational Fluid Dynamics
• +۳ مورد دیگر

Bo Gervang is an Associate Professor at the Technical University of Denmark (DTU), affiliated with the Department of Engineering Technology and Didactics. His research focuses on fluid dynamics, aeroelasticity, and computational methods, with notable contributions to wind turbine aerodynamics and flow analysis in duct systems. He has advised PhD candidates in mechanical engineering and fluid mechanics. Research interests include secondary flows in rectangular ducts, numerical simulations of 3D flows, and aeroelastic stability in wind energy systems. His work combines experimental and computational approaches to address challenges in mechanical engineering and fluid mechanics. Gervang has presented at international conferences on topics such as analytic solutions for wave-like equations and mimetic methods for two-phase flows. He is actively involved in examining PhD theses and has contributed to projects like the 'Scavenging and swirling flow in two-stroke diesel engines' and 'Spektral element simulering af ultrafiltrering.'

J. Andreas Bærentzenمشاهده پروفایل

دانشیار

• Computer Graphics
• Shape Modelling
• Real-Time Rendering
• +۵ مورد دیگر

Professor J. Andreas Bærentzen is an Associate Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU), where he has held academic positions since 2001. His research focuses on computer graphics, shape modeling, real-time rendering, and geometry processing. He holds a MSc Eng (1998) and PhD (2003) from DTU. His work emphasizes topological adaptability in shape representation and efficient geometry processing, with notable contributions to structural topology optimization, 3D reconstruction, and virtual reality applications. Education: MSc Eng, Technical University of Denmark, 1991–1998 PhD, Technical University of Denmark, 1998–2003 Research Interests: Interactive 3D modeling and real-time graphics Topology optimization and structural infill design Shape modeling using distance fields and deformable hypersurfaces Applications in biomedical imaging (e.g., white matter dynamics) and environmental engineering (e.g., tree geometry simulation) His recent publications highlight advancements in neural network-based shape representation, skeletonization for tree reconstruction, and inverse-designed structural infill for engineering. He supervises multiple PhD students and leads projects on robotic manufacturing and virtual reality visualization. Bærentzen collaborates internationally, including visits to Stony Brook University (USA) and Padova University (Italy). Advisees & Projects: PhD Students: Rui Cui, Thomas D. V. Christiansen, Elias Theil Gæde Key Projects: 'Generative Methods for Brain Tissue Phantoms', 'Neural Form Representation', 'Graph Algorithms with Geometric Applications' His work bridges theoretical geometry processing with practical applications in architecture, biomedical engineering, and environmental science, leveraging DTU's interdisciplinary research ecosystem.

Mohamad Bayatمشاهده پروفایل

دانشیار

• Additive Manufacturing
• Multiphysics Simulations
• Advanced Process Monitoring
• +۵ مورد دیگر

Mohamad Bayat is an Associate Professor at the Department of Civil and Mechanical Engineering, Technical University of Denmark (DTU). He holds a Master's from Sharif University of Technology (2017) and a Ph.D. from DTU (2020). His roles include teaching courses like Heat Transfer, Finite Element Analysis, and Thermo-Mechanics at undergraduate and graduate levels. His research focuses on multiphysics simulations of advanced manufacturing, particularly in additive manufacturing (AM), thermal management systems, and laser-material interactions. Long-term goals include expanding into space-related and biomedical applications. Research interests include metal 3D printing, online process monitoring, and thermal-fluid dynamics in AM. He supervises PhD students in projects involving laser welding, powder bed fusion, and thermal modeling. Awards include the Energies Prize (2022), IIW Kenneth Easterling Award (2018), and NAFEMS Nordic PhD Award (2021). His work contributes to UN Sustainable Development Goals by advancing efficient manufacturing and thermal technologies. Education: Ph.D. in Mechanical Engineering, DTU (2017–2020) Master of Mechanical Engineering, Sharif University of Technology (2017) Grants/Projects: Multiphysics simulation of metal AM for topology optimization Thermal modeling of heat pipes for space applications Laser welding for battery pack manufacturing Awards: Energies Prize for Best Multi Physics Paper (2022) IIW Kenneth Easterling Best Paper Award (2018) NAFEMS Nordic PhD Student Award (2021) Lab/Team: Active in DTU's Construct group, focusing on AM process development and thermal-fluid modeling.

Seyed Soheil Mansouriمشاهده پروفایل

دانشیار

• Process Design
• Bioprocess Engineering
• Process Systems Engineering
• +۵ مورد دیگر

Seyed Soheil Mansouri is an Associate Professor at the Department of Chemical and Biochemical Engineering, Technical University of Denmark. He holds a PhD (2016) and MSc (2013) from DTU. His expertise spans process design, bioprocess engineering, and quantum computing applications in chemical systems. He leads the KT Consortium PROSYS - Process and Systems Engineering Centre. Research focuses on sustainable biomanufacturing, data-driven modeling, and quantum computing for process optimization. Key areas include photobioreactor design, machine learning in biosystems, and hybrid quantum-classical algorithms. He has supervised 14 PhD projects and co-authored 182 publications. Awards include Best Contributed Paper (2018), Best Oral Presentation (2015), and multiple best presentation awards. Active in organizing workshops on quantum computing and biorefineries. Advises on modular manufacturing, bio-succinic acid production, and AI-driven process systems. Develops digital twin technologies for bio-manufacturing and promotes open innovation. His work aligns with UN Sustainable Development Goals, emphasizing education and sustainable industrial practices. Current projects explore quantum computing in bioprocesses and modular vaccine production units.

Amit Kumarمشاهده پروفایل

پژوهشگر

• Cryogenic Energy Storage
• Two-phase Turbine
• Barotropic Model
• +۲ مورد دیگر

Amit Kumar is a Postdoc at the Department of Energy Conversion and Storage, Technical University of Denmark (DTU), conducting research in energy storage systems and computational fluid dynamics. His research focuses on: Cryogenic Energy Storage Two-phase Turbine Barotropic Model Energy Storage Systems Computational Fluid Dynamics He specializes in numerical analysis of two-phase flows for energy conversion, with applications in turbine design and cryogenic storage optimization. Publications from 2023-2025 reveal consistent work on two-phase flow phenomena, including comparative modeling of barotropic/mixture approaches for turbines, stall analysis in compressors, and integration of energy storage with nuclear reactors. His research emphasizes computational methods to enhance system efficiency and reliability. Kumar actively participates in the LAES-Egypt project (2022-2025), developing sustainable large-scale cryogenic energy storage solutions for renewable energy integration in Egypt, contributing to UN Sustainable Development Goals for clean energy.

Nishith Babubhai Desaiمشاهده پروفایل

پژوهشگر

• Packed Bed Engineering
• Cryogenic Energy Storage
• Energy Storage Systems
• +۵ مورد دیگر

Nishith Babubhai Desai is a Senior Researcher in the Department of Civil and Mechanical Engineering at the Technical University of Denmark (DTU), located at Koppels Allé, 403, 024, 2800 Kgs. Lyngby, Denmark. His work directly supports UN Sustainable Development Goals through innovations in thermal energy systems and storage technologies. His research specializes in Packed Bed Engineering (100% fingerprint prominence), Cryogenic Energy Storage (68%), Energy Storage Systems (65%), Organic Rankine Cycle (59%), and Thermal Energy Storage Systems (44%). He employs computational fluid dynamics and thermodynamic modeling to optimize solidification processes, two-phase flows, and energy storage configurations for industrial applications. Recent publications (2025-2026) demonstrate a concentrated focus on molten salt heat exchanger solidification, hybrid pumped thermal-liquid air storage integration, and compressor performance prediction. These works collectively advance thermal energy storage efficiency, system roundtrip optimization, and cryogenic storage scalability within mechanical engineering. No scientific awards, fellowships, or medals were documented in the source material. Dr. Desai actively supervises four PhD students on critical energy projects including two-phase turbo-expanders for liquid air storage and supersonic turbine design for organic Rankine cycles. He participates in the EMPOWER initiative (2025-2028) developing two-phase expansion technology for geothermal and industrial waste heat recovery, securing significant research funding for DTU's sustainability efforts.

Ulrich Krühneمشاهده پروفایل

دانشیار

• Microfluidics
• Computational Fluid Dynamics (CFD)
• Biocatalytic Reactions
• +۳ مورد دیگر

Ulrich Krühne is an Associate Professor in the Department of Chemical and Biochemical Engineering at the Technical University of Denmark (DTU), affiliated with the PROSYS - Process and Systems Engineering Centre. His career spans academic research, industry leadership in microfluidics, and interdisciplinary engineering. He holds a MSc in Chemical Engineering from Technische Universität Berlin (1995). His expertise includes microfluidic systems, computational fluid dynamics (CFD), biocatalytic reactions, and bioprocess optimization across scales. Research focuses on developing microfluidic devices for medical and biochemical applications, CFD-driven process simulations, and scale-up strategies for bioreactors. He teaches courses on chemical reaction engineering, computational fluid dynamics, and GMP standards. Krühne has advised multiple PhD students and led projects in bioprocess modeling, digital twins, and biomanufacturing innovation. Key contributions include CFD-based bioreactor design, integration of AI chatbots in chemical education, and sustainable bioprocess technologies. He received the Best Contributed Paper Award in 2018 for advancements in bioprocess systems engineering. His work aligns with UN SDGs through contributions to clean energy and responsible consumption.

Bin Yangمشاهده پروفایل

استاد

• Computer Science
• Data Management
• Machine Learning
• +۹ مورد دیگر

Bin Yang is a Professor at the Department of Computer Science, Aalborg University, affiliated with The Technical Faculty of IT and Design. His research focuses on data engineering, artificial intelligence, and machine learning, with emphasis on spatiotemporal data analysis, representation learning, and time series forecasting. He leads projects like aSTEP (spatio-temporal data analytics) and Light-AI for Cognitive Power Electronics. Key contributions include advancements in trajectory data processing, anomaly detection, and lightweight neural architectures. Research interests span machine learning, data mining, intelligent transport systems, and material science applications. Notable awards include the IJCAI 2019 Distinguished PC Member and Sapere Aude Research Leader (2018). He has supervised six PhD students and contributed to over 119 publications. His work is supported by grants from Villum Foundation and EU initiatives. Yang is involved in interdisciplinary collaborations, including data-driven decision-making frameworks and environmental monitoring systems. Labs and teams include the Daisy Center for Data-intensive Systems and AI for the People initiatives. Projects emphasize real-world applications in smart cities, traffic forecasting, and sustainable technologies. His research bridges theoretical foundations with practical implementations in domains like oceanography and crowdsourcing systems.

Bent Thomsenمشاهده پروفایل

استاد

• Sustainable Software Development
• Energy-efficient Computing
• Programming Language Design
• +۲ مورد دیگر

Bent Thomsen is a Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design. He directs the Integrated Composites Laboratory (ICL) and serves as editor-in-chief of Advanced Composites and Hybrid Materials. His research focuses on sustainable software development challenges, energy-efficient computing systems, and programming language design. Key interests include green computing paradigms, formal methods for software verification, and optimizing energy consumption in distributed systems. Recent publications demonstrate a strong focus on environmental sustainability in computing, particularly developing methodologies for measuring and reducing energy footprints of IT systems. This aligns with his leadership in the 'Teaching AI green coding' project funded by The Villum Foundation. Professor Thomsen leads multiple research groups including the Center for Embedded Software Systems (CISS) and Center for Data-intensive Systems (Daisy), fostering collaborations across distributed systems and intelligent embedded technologies.