جست‌وجوی استاد و پژوهشگر

Mohammad Hassan Khoobanمشاهده پروفایل

دانشیار

• Power Systems
• Renewable Energy
• Control Systems
• +۴ مورد دیگر

Mohammad Hassan Khooban is an Associate Professor at the Department of Electrical and Computer Engineering, specializing in Electrical Energy Technology at Aarhus University . His research emphasizes advanced control strategies for power systems, renewable energy integration, and smart grid technology. While specific educational background details are not explicitly stated, his work demonstrates expertise in power electronics, control systems, and machine learning applications. His projects include pioneering initiatives like QuantumEcoCircuits (2024–2027) and Smart Synergy Mechanism (2023–2025), focusing on sustainable energy systems, electric vehicle charging dynamics, and resilient grid operations. His research interests span adaptive control methodologies, grid resilience under cyber threats, and the optimization of energy storage systems. He has contributed to peer-reviewed journals such as IET Renewable Power Generation and IEEE Transactions on Smart Grid , exploring topics ranging from PID controllers to fractional-order sliding mode control for unmanned aerial vehicles. No scientific awards are listed, but his work is supported through grants and collaborative projects. He is actively involved in lab initiatives related to power systems and renewable energy technologies.

• Applied probability theory
• Markov chain Monte Carlo methods
• Spatial statistics
• +۴ مورد دیگر

Jesper Møller is a Professor in the Department of Mathematical Sciences at Aalborg University's Faculty of Engineering and Science, specializing in Statistics and Mathematical Economics. His research focuses on advanced statistical methodologies with applications across various scientific domains. His educational background includes extensive training in mathematical sciences, though specific degree details aren't provided in the current materials. His research interests span: Applied probability theory Markov chain Monte Carlo methods (MCMC) Spatial statistics Stochastic geometry Stochastic simulation Point process modeling Professor Møller's recent publication record shows consistent productivity with 239 research outputs including journal articles, reports, and book chapters. His work demonstrates strong focus on spatial point processes, Bayesian inference methods, and applications of stochastic geometry. The research trends indicate increasing sophistication in modeling complex spatial patterns and developing computational methods for statistical inference. His scientific contributions have been supported by numerous research projects, with 28 projects documented including the current "Peculiar Distribution Functions and Interesting Stochastic Processes" (2022-2026). His work has generated significant scholarly impact with citations across multiple disciplines. Professor Møller has supervised 8 PhD students and maintains active collaborations across international research networks. His current projects suggest continued research activity in developing novel statistical methodologies for complex spatial data analysis with applications in materials science, neuroscience, and environmental statistics.

Mihaela Bejenariمشاهده پروفایل

پژوهشگر

• Molecular Microbiology
• Heterologous Biosynthesis
• Polyketide Chemistry
• +۴ مورد دیگر

Mihaela Bejenari serves as a Researcher at Aalborg University's Department of Chemistry and Bioscience within the Faculty of Engineering and Science, specializing in fungal metabolic engineering and polyketide biosynthesis. Her research bridges microbiology, biochemistry, and sustainable biotechnology through innovative work with Yarrowia lipolytica as a chassis organism. Her research focuses on heterologous biosynthesis pathways for valuable metabolites, particularly examining how 6-methylsalicylic acid (6-MSA) functions as a distribution hub for diverse fungal secondary metabolites including mycotoxins and polyketides. She investigates horizontal gene transfer mechanisms in fungal evolution and develops sustainable approaches for producing electrolytes in oleaginous yeasts for energy storage applications. Analysis of her recent publications reveals strong thematic continuity in fungal polyketide engineering, with increasing emphasis on practical applications for sustainable chemistry and energy storage. Her work demonstrates sophisticated manipulation of fungal metabolic pathways while maintaining relevance to industrial biotechnology challenges. Awarded a Tuition Fee award in November 2024, her scholarly impact is reflected in citations across her publications, with particular recognition for her educational contributions to molecular microbiology pedagogy. Bejenari actively contributes to academic discourse through conference presentations at major international forums including the European Conference on Fungal Genetics (2025), International Mycological Congress (2024), and Synthetic Biology Australasia Conference (2023), where she presented her work on heterologous production of fungal polyketides.

Ole Madsenمشاهده پروفایل

استاد

• Robotics
• Automation
• Industry 4.0
• +۶ مورد دیگر

Ole Madsen is a Professor at the Department of Materials and Production within The Faculty of Engineering and Science at Aalborg University . His research focuses on Robotics and Automation , particularly in 5G Smart Production , AI for Manufacturing , and Industry 4.0 applications. He also holds a part-time position at Adding Robotics , applying his expertise in robot integration for industrial and healthcare settings. Research Interests : Robotics, Automation, AI, Sensor Systems, Modular Manufacturing, Welding Technology, Digital Twins, Human-Centered Robotics, Industry 4.0 His work spans 35+ years with over 205 publications , emphasizing smart production systems and robot-assisted processes . Key contributions include Swarm Production Architectures , 5G-Enabled Robotics , and Human-Robot Collaboration frameworks. He has supervised 10 PhD students and led major projects like RAU (Robot-Assisted Ultrasound) and GINP: Robotics & AI Innovation Network . Scientific Awards : SCAP2020 Best Presentation Award (2020) Ole's 31 projects include AP2030: Aseptic Factory 2030 (pharma production), AddSmart (robotics R&D), and 5G-Enabled Autonomous Systems . His 127 press/media mentions highlight advancements in robotic welding , industrial metaverse , and swarm production . He maintains an ORCID: 0000-0003-2133-2541 with extensive publication records across Swarm Robotics , Modular Manufacturing , and AI-Driven Production .

Peyman Afzali Gorouhمشاهده پروفایل

پژوهشگر

• Power Engineering
• Smart Grids
• Renewable Energy Systems
• +۵ مورد دیگر

Peyman Afzali Gorouh is a Postdoctoral Researcher in the Applied Power Electronic Systems group within the Faculty of Engineering and Science at Aalborg University, Denmark. His research focuses on developing innovative models for energy communities, smart grids, and renewable energy integration. Dr. Afzali's research interests span power engineering, smart grid technologies, renewable energy systems, and energy communities. His work particularly emphasizes prosumer economics, peer-to-peer energy trading, risk modeling in power systems, and energy democracy frameworks. He has developed novel approaches for optimizing energy communities while considering socio-economic-environmental factors, demand response, and uncertainty management. His recent publications (2020-2024) demonstrate a consistent focus on energy community modeling, with particular emphasis on peer-to-peer trading mechanisms, risk-constrained optimization, and multi-objective planning. His work bridges technical power system challenges with socio-economic considerations, creating integrated models that address both engineering and human aspects of modern energy systems. Dr. Afzali maintains an active research profile with numerous publications in high-impact journals including IEEE Transactions on Engineering Management, Energy and Buildings, Applied Sciences, and Sustainable Cities and Society. His research shows strong international collaboration, particularly with researchers from Iranian institutions.

Majid Khazaeeمشاهده پروفایل

استادیار

• Energy Harvesting
• Piezoelectric Engineering
• Biomedical Engineering
• +۳ مورد دیگر

Majid Khazaee is an Assistant Professor at the Department of Thermal Engineering, Faculty of Engineering and Science, Aalborg University. His research focuses on energy harvesting technologies, particularly leveraging piezoelectric materials and cardiac kinetic energy for biomedical applications such as self-powered leadless pacemakers. He leads projects like NeoPEH-LP (2023-2025) and SelfPace (2021-2023), advancing innovations in energy harvesting for medical devices. Khazaee's work integrates mechanical, biomedical, and materials engineering to optimize energy conversion systems. Notable projects include the development of impact-based piezoelectric harvesters and low-power solutions for intracardiac devices. His research also explores vibration-based energy capture from diverse sources like automotive and industrial systems. Key collaborations include partnerships with Aalborg University’s Energy Harvesting group and industry partners such as Systemize ApS. His publications emphasize practical applications of energy harvesting, including patents on harvester designs. Despite no explicit awards listed, his work has been highlighted in media for contributions to medical device innovation and energy efficiency. Grant activities span €1.2M+ in funded projects, with a focus on translating research into clinical and industrial applications. His lab’s current efforts target durable, high-performance harvesters for long-term medical use, bridging the gap between theoretical models and real-world biomedical challenges.

Pedram Raminمشاهده پروفایل

پژوهشگر

• Process Systems Engineering
• Wastewater Treatment
• Bioprocess Modeling
• +۱۲ مورد دیگر

Pedram Ramin is a Senior Researcher 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 work contributes to UN Sustainable Development Goals related to clean water and sustainable cities. His research focuses on process systems engineering, particularly in wastewater treatment, bioprocess modeling, and digital twin development. Key areas include fault detection using machine learning, anaerobic digestion, industrial fermentation, and sewer system modeling. He applies data-driven techniques like Random Forest and Long Short-Term Memory networks to address challenges in imbalanced big data from wastewater systems. His recent publications highlight trends in integrating artificial intelligence with process engineering for environmental applications, especially in monitoring and optimizing wastewater and biomanufacturing systems. These works span fault diagnosis, life cycle assessment, and hybrid modeling for industrial-scale processes. Senior Researcher, DTU Chemical and Biochemical Engineering Supervisor, Mathematical modelling for digital twins of fermentation processes (2023–2026) PhD Graduate, DTU (2013–2017) He has contributed to multiple research projects and has presented at international conferences on topics such as wastewater-based epidemiology and biogas reactor optimization. While no formal scientific awards are listed, his work is widely published and cited in the field of process engineering and environmental technology. He supervises PhD students, including M. Lemperle, and collaborates extensively within DTU and with external partners. His lab environment is centered around the PROSYS research group, focusing on advanced modeling and simulation for sustainable industrial processes. Future work appears directed toward enhancing digital twins and improving wastewater monitoring through AI-driven analytics.

• Combustion
• Microscale Systems
• Laser Diagnostics
• +۴ مورد دیگر

Christopher Cadou is a Professor and Director of Undergraduate Studies in the Department of Aerospace Engineering at the University of Maryland. He holds a B.S. in Mechanical Engineering and B.A. in History from Cornell University, and M.S. and Ph.D. in Mechanical Engineering from UCLA. His research focuses on combustion at micro and conventional scales, laser diagnostics, compact power systems, and fuel cells. He has led interdisciplinary projects in micro-gas turbine engines, microfluidics, and energy innovation. Professional affiliations include the American Society of Mechanical Engineers (ASME), American Institute of Aeronautics and Astronautics (AIAA), and The Combustion Institute. He has reviewed for journals like Combustion and Flame, and government agencies such as the National Science Foundation. His work includes pioneering infrared diagnostics for micro-combustors and developing analytical models for heat transfer in mini/microchannels. He has organized conferences including the 2009 AIAA Joint Propulsion Conference. His contributions span technical reports on microturbomachinery and scramjet inlet flows, and collaborations with industry through initiatives like the Maryland Energy Innovation Institute.

• Construction Engineering
• Structural Health Monitoring
• Concrete Structures
• +۵ مورد دیگر

Muhammad Usman Hanif is an Assistant Professor at the Department of Technology and Innovation within the Faculty of Engineering at the University of Southern Denmark (SDU). His research focuses on structural health monitoring , concrete durability , and damage assessment in civil engineering systems. Research Highlights Advanced signal processing for bridge damage detection Acoustic Emission techniques in CFRP-concrete debonding Machine learning applications in concrete durability prediction Augmented Reality integration with bridge monitoring systems Recent Publications (2023-2025) 2025: Machine learning in concrete durability 2024: Novel ΔT mapping for debonding detection 2023: FBG sensors in CFRP retrofitted beams 2022: MEMS accelerometers for damage assessment Teaching Activities Finite Element Method (2025) Non-linear Finite Element Method (2025) Advanced Finite Element Analysis (2024)

Paul Popمشاهده پروفایل

استاد

• Embedded Systems
• Systems Engineering
• Time-Sensitive Networking
• +۷ مورد دیگر

Paul Pop is a Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). He holds the position of Professor within the Embedded Systems Engineering group at DTU Compute. His academic journey includes a Ph.D. in Computer Systems from Linköping University, Sweden (2003), followed by roles as an Assistant Professor there before joining DTU in 2006. Dr. Pop's research focuses on systems engineering methodologies for embedded and cyber-physical systems, with emphasis on modeling, analysis, optimization, and real-time guarantees. His work addresses challenges in time-sensitive networking (TSN), automotive systems, industrial automation, and fog computing. Key application areas include safety-critical systems, mixed-criticality architectures, and sustainable industrial IoT solutions aligned with UN SDGs. He leads major research projects such as G3C (Green Computing & Communication Continuum), TRANSACT (Safety-Critical Cyber-Physical Systems), and AgroRobottiFleet (Agricultural Robotics). His contributions span 194 publications in journals/conferences and 31 active/completed projects, emphasizing interdisciplinary collaboration. Dr. Pop advises doctoral students in embedded systems and serves as Principal Investigator on EU-funded initiatives. His technical expertise includes TSN configuration tools (TSNConf), fog computing platforms (FORA), and microfluidic biochip design. He actively contributes to industry standards through IEEE 802.1 TSN working groups and collaborates internationally with institutions like Nordic Innovation and EU Horizon programs.

• Energy Engineering
• Home Automation
• Learning Algorithms
• +۱۲ مورد دیگر

Per Printz Madsen is an Associate Professor in the Department of Computer Science at Aalborg University, under The Technical Faculty of IT and Design. His research focuses on distributed, embedded, and intelligent systems with applications in energy efficiency, smart buildings, and renewable energy integration. His research interests span energy engineering, home automation, learning algorithms, fuzzy systems, neural networks, and intelligent control systems. He applies computational intelligence to optimize energy consumption in buildings and district heating systems, with a strong emphasis on real-world implementation through digital twin technology and supervisory control. The recent publications highlight a consistent trend in energy management systems, particularly in forecasting, load control, and energy brokerage in smart grids and buildings. The work emphasizes the integration of renewable generation and storage, leveraging machine learning and distributed control architectures to improve energy efficiency and reduce CO 2 emissions. He has been involved in several major research projects including ENCOURAGE, Homeport, Flexnet, and Mediterranean Virtual University, funded by entities such as Artemis JU and the Danish Enterprise and Construction Authority. These projects demonstrate sustained external funding and collaborative research across Europe. Madsen contributes regularly through technical reports and conference proceedings, primarily through Aalborg University. His work is applied and systems-oriented, targeting practical deployment in energy infrastructure. He is affiliated with the Distributed, Embedded and Intelligent Systems research group at Aalborg University, where he conducts interdisciplinary research bridging computer science and energy engineering to develop intelligent solutions for sustainable energy systems.

Pawel Wargockiمشاهده پروفایل

استاد

• Indoor Air Quality
• Air Pollution Control
• Thermal Comfort
• +۶ مورد دیگر

Pawel Wargocki is a Professor at the Department of Environmental and Resource Engineering, Technical University of Denmark (DTU). His research focuses on indoor environmental quality, air quality management, and human health impacts of building systems. He leads projects addressing airborne infection risk, thermal comfort, and ventilation strategies in schools, offices, and healthcare settings. Key research areas include: Optimization of ventilation systems for infection control Thermal insulation in sleep environments Low-cost sensor validation for pollutant exposure CFD modeling of aerosol dynamics Public health implications of CO₂ levels Healthy building frameworks Notable projects include: IEA EBC Annex 86: Energy-Efficient IAQ Management in Residential Buildings WHO Collaborations on Airborne Infection Risk Assessment International sleep quality studies funded by Danish Research Councils His 396+ publications emphasize interdisciplinary approaches, with recent work published in Building and Environment , Infectious Disease Modelling , and Indoor and Built Environment . He supervises PhD students exploring cognitive performance in classrooms and HVAC energy savings.

Luisa Siniscalchiمشاهده پروفایل

استادیار

• Cryptography
• Secure Multiparty Computation
• Post-quantum Cryptography
• +۷ مورد دیگر

Luisa Siniscalchi is an Assistant Professor (tenure track) in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), affiliated with the Cybersecurity Engineering Center and the Center for Quantum Technologies. Her research lies at the intersection of cryptography, cybersecurity, and theoretical computer science. Her research interests focus on secure multiparty computation (MPC) , zero-knowledge proofs , non-malleable and deniable protocols , post-quantum cryptography , and cryptographic primitives . She investigates foundational aspects of secure computation under minimal assumptions, aiming to achieve optimal round complexity and strong security guarantees in both synchronous and asynchronous settings. The recent publications highlight a consistent trend in designing efficient, secure, and practical cryptographic protocols, particularly in MPC and deniable authentication. Her work often appears in top-tier venues such as EUROCRYPT, CRYPTO, and TCC, demonstrating strong theoretical rigor and innovation. Key themes include black-box constructions, post-quantum security, and privacy-preserving mechanisms. Scientific Awards: No awards listed in the provided text. Luisa Siniscalchi is actively supervising PhD students in cutting-edge projects related to proactive post-quantum cryptography, long-term security of protocols, and dynamic graph algorithms. She collaborates with principal investigators such as Claudio Orlandi, Ivan Damgård, and Carsten Baum, indicating integration into major research initiatives at DTU. While specific grants are not detailed, her involvement in multi-year PhD projects suggests active grant funding. Labs and Research Groups: Cybersecurity Engineering Center, DTU Center for Quantum Technologies, DTU Active research in cryptographic protocols and algorithms

Zhe Chenمشاهده پروفایل

استاد

• Wind Turbine Engineering
• Power Engineering
• Control Strategy
• +۷ مورد دیگر

Professor Zhe Chen is a distinguished academic at Aalborg University's Faculty of Engineering and Science, where he leads research in Electric Power Systems and Microgrids within the Intelligent Energy Systems and Flexible Markets department. With an extensive publication record spanning over two decades and more than 1,200 publications, he has established himself as a leading expert in power engineering and renewable energy systems. Professor Chen's research focuses on Wind Turbine Engineering, Power Engineering, Control Strategy, Wind Power Engineering, Energy Engineering, and Reinforcement Learning. His work bridges theoretical advancements with practical applications in smart grid technology and microgrid systems. His research interests center around developing innovative solutions for renewable energy integration, power system stability, and efficient energy management. His recent publications demonstrate a strong trend toward integrating artificial intelligence with traditional power engineering, particularly in applying deep reinforcement learning to power system control, state estimation with noisy data, and optimization of power electronic converters. His work shows increasing focus on carbon emissions optimization, thermal management in power electronics, and the application of advanced neural network architectures to energy systems. MPCE 2023 Best Paper Award for research on reinforcement learning applications in electric vehicles MPCE 2022 Best Paper Award for distribution network optimization MPCE 2021 Best Paper Award for reinforcement learning in energy systems WATAB Best Paper Award 2005 for offshore wind farm research IEEE Fellow recognition for contributions to power electronics and renewable energy systems Professor Chen has supervised 27 PhD students throughout his career, demonstrating his commitment to academic mentorship. His current research is supported by significant grants including the Erasmus+ funded S3SF project (Smart Energy Solutions for a Sustainable Future) and multiple projects focused on machine learning-based stability analysis for multi-energy systems. His collaborative work spans numerous international partnerships, with recent projects involving researchers from China, Europe, and other global institutions. Professor Chen leads a research team focused on intelligent energy systems, working on advanced control strategies for microgrids, power quality analysis, and the integration of renewable energy sources into existing power infrastructure. His team is particularly known for innovative approaches to wind power integration and DC microgrid technologies.

Jakob Egholt Søgaardمشاهده پروفایل

استادیار

• Public Finance
• Labor Economics
• Applied Microeconometrics
• +۵ مورد دیگر

Jakob Egholt Søgaard is an Assistant Professor (Tenure Track) at the Department of Economics , University of Copenhagen, and affiliated with the Center for Economic Behavior and Inequality (CEBI) . He holds a PhD in Economics (2015) and an MSc in Economics (2011) from the University of Copenhagen, with visiting studies at the London School of Economics and University of Vienna. Research Interests His work spans public and labor economics , focusing on taxation , labor supply , optimization frictions , and income/gender inequality . Key contributions analyze earmarked parental leave , tax reform responses , and child penalty drivers . Publications in top journals like the American Economic Review and Journal of Public Economics examine how policy shapes economic behavior. Scientific Awards Best Paper of 2016 in Scandinavian Journal of Economics Best Paper of 2019 in American Economic Journal: Applied Economics Additional Roles Active in policy evaluation during 2011–2017 at the Danish Ministry of Finance and Taxation. Current Carlsbergfondet Infrastructure Grant funds parental leave research. Teaching includes Public Finance (BSc/MSc) and Econometrics .