جست‌وجوی استاد و پژوهشگر

Francesco Ferriمشاهده پروفایل

دانشیار

• Wave Energy Engineering
• Power Converter Systems
• Offshore and Coastal Engineering
• +۳ مورد دیگر

Francesco Ferri is an Associate Professor at Aalborg University’s Department of the Built Environment, within The Faculty of Engineering and Science. He specializes in ocean and coastal engineering, with a focus on wave energy systems, mooring solutions, and control systems for renewable energy technologies. Ferri is affiliated with the Ocean and Coastal Engineering Research Group and has been involved in multiple high-impact projects, including COmposites, Hybrid testing and SImulations (CHS) and EXOWAVE, which aim to advance wave energy converter (WEC) technology and offshore platform sustainability. His research interests span wave energy engineering, power converter optimization, and the dynamic analysis of mooring systems for floating structures. Ferri has contributed to the development of advanced numerical models for wave propagation and has pioneered experimental validation methods for WEC control systems. He has collaborated on projects funded by the Danish Energy Agency (EUDP) and the North Sea Region Programme, demonstrating expertise in both academic and applied research. Key projects include leadership roles in EXOWAVE (2022–2024) and OESA (2019–2021), focusing on wave energy scale-up and hybrid systems. Ferri has also supervised two PhD students and contributed to over 80 peer-reviewed publications, addressing topics like mooring system optimization, wave-to-wire modeling, and offshore platform multi-use concepts. His work emphasizes interdisciplinary solutions, integrating computational fluid dynamics, control engineering, and experimental testing to enhance the efficiency and reliability of marine renewable energy systems.

Simon Pommerencke Melgaardمشاهده پروفایل

استادیار

• Fault Detection and Diagnosis
• HVAC Systems
• Energy Optimization
• +۳ مورد دیگر

Simon Pommerencke Melgaard is an Assistant Professor at the Department of the Built Environment, Faculty of Engineering and Science, Aalborg University. His research focuses on building management systems, fault detection and diagnosis in HVAC systems, energy optimization, and building simulation. He has contributed to EU Horizon projects like SATO (building performance analysis) and HEATWISE (waste heat reuse in buildings), as well as initiatives like HYBRIDENE (hybrid ventilation in Nordic climates) and COVOCHA (high-resolution occupancy datasets). Key research areas include fault detection algorithms, HVAC performance monitoring, and energy-efficient building systems. His work integrates computational methods like Monte Carlo simulations and data-driven approaches to improve building operational efficiency. Projects such as Self Assessment Towards Optimization in Building Energy emphasize key performance indicators and automated diagnosis. Recent contributions include datasets on office room environments and studies on thermal comfort aggregation. He has presented at conferences on topics like real-time energy management and novel ventilation control strategies. His activities include organizing workshops on occupant-centric building controls and visiting research institutions such as the University of Lisbon.

Chen LIمشاهده پروفایل

دانشیار

• Human Robot Interaction
• Industrial Robotics
• AI for Manufacturing
• +۳ مورد دیگر

Chen LI is an Associate Professor in the Department of Materials and Production at Aalborg University, Denmark. His work focuses on advancing smart manufacturing through AI-driven robotics and 5G-enabled production systems. He leads research projects involving historical figure emulation in robotics, human-robot interaction, and AI at the edge for industry 5.0. His interdisciplinary approach bridges software architecture, industrial automation, and cognitive modeling. Key projects: Time-Traveling Conversations (Villum Foundation), Human Robot Interaction dialog systems, and AI REDGIO 5.0 for SME manufacturing Collaborations span institutions like Seoul National University and industry partners Research interests include: AI ethics in dialogue systems Edge computing for real-time manufacturing Virtual assistant architectures Robot speaking style imitation Over 70 publications (2009-2025) span topics like anomaly detection frameworks, defect prediction models, and hybrid power system analysis. Active in conferences such as HRI2021 and workshops on AI in performing arts.

Jun Liمشاهده پروفایل

استاد

• Biomass Conversion
• Renewable Hydrogen Production
• Advanced CFD Modelling
• +۳ مورد دیگر

Dr. Jun Li is a Reader in the Department of Chemical and Process Engineering at the University of Strathclyde. He leads a bioenergy research group focused on decarbonizing energy systems through biomass and waste valorization, green hydrogen production, and advanced computational fluid dynamics (CFD) modeling. His work contributes to UN Sustainable Development Goals related to clean energy and climate action. Education: PhD from KTH Royal Institute of Technology (2014), MEng from North China Electric Power University (2010) Research interests span thermochemical processes, bioenergy technologies, hydrogen-rich syngas utilization, and techno-economic assessments. Key projects include biomass electrolysis for green hydrogen and leadership roles in the UK Supergen Bioenergy Impact Hub. Recent publications address hydrogen-LPG boiler performance, PEM fuel cell diagnostics, and lithium-ion battery health prediction. Awards include Best Presentation Prizes at ETP Annual Conferences (2022). Teaching modules include Clean Combustion Technologies and Chemical Engineering fundamentals. Supervised over 10 PhD students and research associates, with active roles in editorial and advisory boards.

Stephanie Forrestمشاهده پروفایل

استاد

• Computational Immunology
• Computer Security
• Automated Software Repair
• +۱۲ مورد دیگر

Stephanie Forrest is a Professor in the School of Computing and Augmented Intelligence (SCAI) at Arizona State University (ASU), where she also serves as Director of the Biodesign Center for Biocomputation, Security and Society. She is an External Faculty member of the Santa Fe Institute (SFI), where she previously held leadership roles including Co-Chair of the Science Board (2010–2013) and Interim Vice President for Academic Affairs (1999–2000). Prior to joining ASU, she was a Regents Distinguished Professor and Department Chair of Computer Science at the University of New Mexico (2006–2011). B.A., St. John's College M.S., Ph.D., University of Michigan, Computer Science Her research lies at the intersection of biology and computation, focusing on computational immunology, automated software repair, evolutionary computation, and modeling complex systems such as cancer and immune responses. She pioneers bio-inspired algorithms for cybersecurity and develops evolutionary techniques for software optimization and repair. Her work integrates principles from immunology, genetics, and complex adaptive systems to solve problems in computer science. The trends in her recent publications reveal a sustained focus on automated program repair using evolutionary computation, GPU code optimization, and modeling biological systems. Her work increasingly combines machine learning with mutation-based search, explores semantic representations in code repair, and applies bio-inspired models to real-world software and security challenges. ACM/AAAI Allen Newell Award (2011) Presidential Young Investigator Award (1991) Stanislaw Ulam Memorial Lectures, SFI (2013) IEEE Fellow UNM Annual Research Lecture (2012) IEEE S&P Test of Time Award (2020) ICSE Most Influential Paper Award (2019) ACM/SIGEVO Impact Award (2019) SEAMS Best Paper Award (2019) WEIS Best Paper Award (2015) Stephanie Forrest has advised numerous students and researchers, often in collaboration with W. Weimer, C. Le Goues, and M. Moses. Her research is supported by major funding agencies including the National Science Foundation (NSF), Defense Advanced Research Projects Agency (DARPA), Air Force Research Laboratory (AFRL), and the Santa Fe Institute. She has also contributed to public policy as a Jefferson Science Fellow at the U.S. Department of State (2013–2014), advising on cyber-policy. She currently chairs the Government Affairs Committee of the Computing Research Association (CRA). She leads the Biodesign Center for Biocomputation, Security and Society, which brings together interdisciplinary teams to study the co-evolution of technology and society. Her research group has developed tools for intrusion detection (e.g., STIDE, pH, RISE), automated software repair (e.g., GenProg), and biological modeling (e.g., CancerSim). Current projects include engineering diversity for enhanced cybersecurity, measuring internet censorship, and modeling immune and cancer systems.

Henrik Olssonمشاهده پروفایل

دانشیار

• decision making
• judgment under uncertainty
• social cognition
• +۶ مورد دیگر

Henrik Olsson is a cognitive scientist and Associate Professor in the Department of Psychology at the University of Warwick. He serves as co-leader of the Collective Minds research group at the Complexity Science Hub in Vienna alongside Mirta Galesic, a position he has held since 2023. Additionally, he is External Faculty at the Santa Fe Institute, demonstrating his significant contributions to complexity science and interdisciplinary research. Olsson earned his PhD in Psychology from Uppsala University and has held academic positions at several prestigious institutions including Uppsala University, Umeå University, the Max Planck Institute for Human Development, and the University of Warwick where he currently serves as Associate Professor. Dr. Olsson's research focuses on understanding the cognitive and social processes underlying human decision making. His work spans several interconnected domains including decision making under uncertainty, social cognition, belief dynamics, categorization, and visual perception. A distinctive feature of his research approach is the development of formal mathematical models to explain psychological processes, coupled with an ecological perspective that examines how environmental structures shape adaptive behavior. His current work integrates insights from psychology, physics, statistics, and machine learning to investigate how individual decision strategies and social network structures influence belief dynamics and collective performance. Analysis of Olsson's recent publications reveals a strong focus on belief dynamics and collective cognition. His work frequently bridges theoretical frameworks from cognitive psychology with methods from complexity science and network analysis. A notable trend is his exploration of how social network structures affect information flow and collective judgment, particularly in the context of societal challenges and political forecasting. His research demonstrates increasing interdisciplinary collaboration, drawing on expertise from physics, computer science, and social sciences to develop integrative models of human cognition in social contexts. While specific awards are not detailed in the provided information, Olsson's affiliation with prestigious institutions like the Santa Fe Institute as External Faculty and his publication record in high-impact journals like Nature suggest recognition of his scholarly contributions. Olsson actively collaborates with researchers across disciplines and institutions, as evidenced by his extensive co-authorship network. His work with the Collective Minds group at the Complexity Science Hub involves mentoring early-career researchers through initiatives like the CSH PostDoc Program. While specific grant information isn't provided, his research on topics like election prediction and collective intelligence likely involves significant external funding given the scope and interdisciplinary nature of his projects. As co-leader of the Collective Minds research group at the Complexity Science Hub, Olsson directs a vibrant team focused on understanding collective cognitive processes. The group appears to be involved in multiple projects including CollAdapt (Collective Adaptation) and ESSENCSE (Building Critical Mass at the Complexity Science Hub Vienna). These projects suggest a strong emphasis on applying complexity science to real-world societal challenges, with research spanning healthcare, economic transformation, and digital ecosystems.

Andrea Rapisardaمشاهده پروفایل

استاد

• Complex Systems
• Statistical Mechanics
• Deterministic Chaos
• +۷ مورد دیگر

Andrea Rapisarda is a Full Professor of Theoretical Physics at the University of Catania, Italy, affiliated with the Department of Physics and Astronomy "Ettore Majorana" and INFN Catania. He is the coordinator of the PhD program in Complex Systems for Physical, Socio-economic and Life Sciences and serves as co-director of the International School on Complexity at the Ettore Majorana Foundation in Erice. Additionally, he is an External Faculty member at the Complexity Science Hub Vienna, reflecting his international academic engagement. His research spans Complex Systems, Statistical Mechanics, Deterministic Chaos, Nonlinear Dynamics, Complex Networks, and Agent-Based Models , with a strong emphasis on applications to socio-economic systems. He investigates the role of randomness, luck, and inefficiencies in hierarchical organizations, drawing from interdisciplinary methods in physics and computational modeling. His work has demonstrated how random strategies can outperform merit-based ones in organizational efficiency and democratic design. The 15 most recent publications highlight a consistent focus on modeling randomness in success, inequality, and decision-making across domains such as sports, economics, politics, and public health. His work integrates agent-based simulations, network analysis, and statistical physics to understand complex phenomena, often with policy-relevant implications. Ig Nobel Prize for Management (2010) Ig Nobel Prize for Economics (2022) Rapisarda is an active advisor and researcher, though specific student names are not listed in the provided texts. He has contributed to numerous editorial boards, including Physica A, Entropy, Frontiers in Physics (Social Physics) , and Complexity . He has also been involved in public outreach, policy discussions on democratic reform via sortition, and science communication through media interviews and public lectures. He leads research projects on improving organizational and societal systems using insights from complexity science.

• Quantum Chromodynamics
• Gauge Theory
• Lattice Theory
• +۷ مورد دیگر

Martin Lundquist Hansen is a Researcher at the Department of Mathematics and Computer Science, University of Southern Denmark's Faculty of Science, with a focus on lattice field theory and high-energy physics. His work intersects Quantum Chromodynamics (QCD) Standard Model Gauge theory Perturbation theory as evidenced by his fingerprint in Fermion physics, broken symmetry, and boundary conditions. Publications since 2018 highlight advancements in radiative leptonic decays of pseudoscalar mesons chiral perturbation theory with scalars gauge-invariant mass determination QCD+QED simulation code through OpenQ∗D and collaborative lattice calculations.

Søren Krogh Andersenمشاهده پروفایل

استاد

• Cognitive Neuroscience
• Visual Perception
• Selective Attention
• +۷ مورد دیگر

Søren Krogh Andersen is a Professor and Head of Unit in the Department of Psychology at the University of Southern Denmark, where he leads research in Health and Cognitive Psychology. He holds a PhD and is actively engaged in empirical and theoretical research on human visual cognition and attentional mechanisms. Research Interests: Cognitive Neuroscience Visual Perception Selective Attention Feature-based Attention Multiple Object Tracking Steady-State Visual Evoked Potentials (SSVEPs) EEG Fingerprinting His research investigates how attention modulates neural activity in early visual areas, with a focus on the temporal dynamics and spatial distribution of attention across visual features such as color and motion. He uses electrophysiological techniques, particularly EEG, to explore the neural basis of perception and attention. Recent publications show a consistent trend in studying attentional modulation in the visual cortex, the separation of luminance and contrast signals in SSVEPs, and the enhancement of perceptual abilities in specialized populations such as video game players. His work combines rigorous experimental design with advanced signal analysis to uncover fundamental principles of visual cognition. Scientific Engagement and Recognition: Active contributor to high-impact journals including PNAS , Journal of Cognitive Neuroscience , and Cerebral Cortex . Featured in media outlets such as TV 2 Fyn, indicating public engagement. ORCID: 0000-0002-7612-0127 Research widely accessed on platforms like Mendeley and Pure. He advises on cognitive neuroscience research and collaborates internationally, though specific students or grant funding are not listed. His work contributes significantly to the understanding of attention and perception, with potential applications in human-computer interaction, clinical psychology, and cognitive training.

Antonio Ragoمشاهده پروفایل

مدرس

• Computational Science
• Lattice Gauge Theory
• Quantum Chromodynamics
• +۵ مورد دیگر

Antonio Rago is a Lecturer in the Department of Mathematics and Computer Science at the University of Southern Denmark (SDU), where he contributes to computational science with a focus on lattice field theories and high-performance computing. His research bridges theoretical physics and advanced computational techniques. Research Interests: His work centers on lattice gauge theory , particularly SU(2) and QCD simulations using Wilson fermions. He specializes in GPU-accelerated algorithms and the HiRep framework for scaling simulations across thousands of GPUs. His interests also extend to fermion formulations, chiral symmetry, and numerical stability in lattice field theories. The recent publications show a strong trend toward scalable computational methods in fundamental physics, emphasizing GPU parallelism, algorithmic efficiency, and non-perturbative quantum field theory. His media contributions reflect growing engagement with science policy, particularly advocating for national AI and supercomputing infrastructure. Scientific Contributions: Active in advancing lattice QCD with novel fermion discretizations. Core developer in HiRep for distributed GPU simulations. Advocate for national investment in academic AI computing. Advising and Grants: While no formal students are listed, his research output suggests mentoring within collaborative projects. He participates in large-scale computational initiatives, likely supported by Danish or EU research grants, though specific funding sources are not disclosed in the text. Labs and Teams: Works within a computational physics group at SDU, collaborating with researchers across Europe on lattice field theory projects. His team leverages GPU clusters for large-scale simulations, focusing on algorithmic scalability and physical observables in gauge theories.

• Artificial Intelligence
• Machine Learning
• Bayesian Mathematics
• +۳ مورد دیگر

Petr Taborsky is a postdoctoral researcher affiliated with the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). His work focuses on artificial intelligence, machine learning, and computational methods within the Cognitive Systems group. Research interests include Bayesian inference , deep learning generalization , and graph-based learning , with applications in high-performance computing and federated learning . Key contributions involve developing the Bayesian Cut method for clustering and analyzing gradient noise in AI models. Recent publications highlight trends in European HPC/AI collaboration (2025) Bayesian graph cut techniques (2022) Statistical modeling in machine learning (2021)

Riccardo Rivaمشاهده پروفایل

پژوهشگر

• Wind Turbine Engineering
• Aeroelastic Stability
• Structural Analysis
• +۳ مورد دیگر

Riccardo Riva is a Special Consultant at the Department of Wind and Energy Systems at the Technical University of Denmark , specializing in wind turbine engineering and aeroelastic stability analysis. His work focuses on combining high-fidelity numerical modeling with machine learning for wind farm optimization, structural response prediction, and control system development. Key research areas: Wind turbine structural dynamics, surrogate modeling, and data-driven control systems Active supervisor in 4 PhD projects (2024-2027) related to wind farm co-design and structural modeling Recent publications address uncertainty propagation, vortex-induced vibrations, and multi-fidelity modeling approaches His research contributes to UN Sustainable Development Goals 7 (Affordable Energy) and 9 (Infrastructure Innovation). Current projects emphasize digital twin technology and floating offshore wind farm optimization.

Luciana Tavaresمشاهده پروفایل

دانشیار

• Dielectrics
• Capacitor Technology
• Additive Manufacturing
• +۵ مورد دیگر

Luciana Tavares is an Associate Professor at the Institute of Mechanical and Electrical Engineering, University of Southern Denmark. Her research focuses on advanced capacitor technologies, dielectric materials, and additive manufacturing processes, with significant contributions to polymer electrolyte membrane fuel cells, nanocomposite thin films, and surface engineering. Institute of Mechanical and Electrical Engineering, University of Southern Denmark Center for Industrial Electronics Her research spans dielectric material optimization , metallized film capacitors , and additive manufacturing of metallic components , aiming to improve energy storage efficiency, mechanical integrity, and surface properties in power electronics. She explores the interplay between microstructure and performance in 316L stainless steel and develops surfactant-modified nanocomposite capacitors. Recent work includes helium-ion irradiation for dielectric enhancement , flow plate roughness in fuel cells , and high-voltage aluminum polymer capacitors . Her projects are supported by foundations like Norlys Vækstpulje and Villum Experiment. Scientific Awards : Villum Grant - Villum Experiment (2021) She supervises projects on dielectric properties , metallization ratios , and UV treatment of biaxially oriented polypropylene , while participating in conferences like PCIM Europe and Hydrogen & P2X. Collaborations include institutions in Germany and Denmark, with expertise in nanofibers, thin films, and surface science.

Martin Frandsenمشاهده پروفایل

پژوهشگر

• Energy-efficient building design
• Indoor environment
• Domestic hot water systems
• +۵ مورد دیگر

Martin Frandsen is a Researcher at Aalborg University 's Department of the Built Environment , within the Faculty of Engineering and Science. His work focuses on energy-efficient building design , indoor environment , domestic hot water systems , and building performance simulations , combining laboratory/field measurements with computational methods. Education: Civil Engineer, MSc in Indoor Climate and Energy (2016-2021) Key Collaborations: Project PRELUDE (2020-2024), ORCID holder His research in building energy systems and hydraulic network optimization is reflected in 13 publications (2022-2025), with 5 in 2024 alone. He specializes in smart meter data analysis and district heating integration , producing datasets with sub-hourly monitoring of office buildings. Frandsen's teaching involves laboratory experiments on indoor environments and building energy simulation , mentoring bachelor/master groups. He has contributed to 10 research datasets and collaborated with 12+ peers on energy informatics and NZEB buildings.

Markus Schafferمشاهده پروفایل

پژوهشگر

• Energy Engineering
• Smart Meter
• Building Performance Simulation
• +۱۲ مورد دیگر

Markus Schaffer is a Researcher at Aalborg University, affiliated with the Department of Construction, Urban and Environmental Engineering under the Faculty of Engineering and Science. His work focuses on leveraging commercial smart heat and water meter data to drive building-specific renovation strategies, integrating these datasets with existing building information to create actionable insights for the scientific community. PhD-level contributions to energy data integration Automated disaggregation of space heating and domestic hot water demands at city scale Non-intrusive large-scale occupancy detection via water meter analytics Advanced clustering for energy data distillation His research portfolio extends to school renovation concepts, where he explores double-skin facades with diffuse ceiling ventilation through parametric simulations. He applies machine learning to Indoor Environmental Quality sensor data collaboration, and teaches master's courses in IT System Development and Sensitivity/Uncertainty Analysis. 2025: Residential Household Dataset publication 2024: 4 peer-reviewed journal articles across Energy, Data in Brief, and REHVA Journal 2023: 2 datasets and 3 conference participations 2022: District Heating data time-series publication Markus' scientific contributions align with UN Sustainable Development Goals 7 (Affordable Energy) and 11 (Sustainable Cities), with ongoing roles in IEA EBC Annex 84 (2020-2025) and FOREFRONT (2021-2024) projects.