جست‌وجوی استاد و پژوهشگر

Miguel Angel Fernandez Sanjuanمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Chaos Theory
• Complex Systems
• +۵ مورد دیگر

Miguel Angel Fernandez Sanjuan is a Full Professor of Physics at Rey Juan Carlos University (since 2002) and holds a Professor position in Applied Informatics at Kaunas University of Technology (since 2016). He has held visiting roles at University of Maryland (Fulbright Scholar), Beijing Jiaotong University, and Lanzhou University. Current affiliations: Rey Juan Carlos University (Physics), Kaunas University of Technology (Applied Informatics) Previous institutions: University of Maryland, Beijing Jiaotong University, Universidad Politécnica de Madrid His research spans nonlinear dynamics, chaos theory, and complex systems with applications in: Physics: Chaotic oscillators, Hamiltonian scattering, time-delay systems Neuroscience: Map-based neuron models, synchronization dynamics Engineering: Fault diagnosis, image processing via resonance phenomena Mathematics: Basin entropy, Wada basin analysis Recent publications focus on AI-driven chaos control, aperiodic resonance mechanisms, and biomedical applications. He has over 605 publications and 141k reads on ResearchGate. Scientific honors include: 2024: Foreign Academician, Serbian Academy of Nonlinear Sciences 2023: Full Academician, Spanish Royal Academy of Sciences 2022: James Yorke Award 2020: Chieh-Su Hsu Award Active in editorial roles (International Journal of Bifurcation and Chaos) and international collaborations. Leads the Miguel A.F. Sanjuan Lab researching complex systems and nonlinear phenomena.

• Power Systems
• Smart Grids
• Transient Stability
• +۷ مورد دیگر

Cavit Fatih Küçüktezcan is an Assistant Professor in the Department of Electrical Engineering at Istanbul Technical University, College of Engineering. His research focuses on power system security, optimization methods, and smart grid technologies. He actively contributes to advancements in electric vehicle energy systems, battery modeling, and resilience of renewable-rich power grids. Research Interests: His work spans power system dynamic security , preventive and corrective control , heuristic and evolutionary optimization (e.g., differential evolution, mean-variance mapping, genetic algorithms), and the application of machine learning for transient stability prediction. He also investigates electric vehicle battery systems , including optimal cell selection and real-time energy consumption modeling. The publication trends show a shift toward data-driven and AI-enhanced approaches in power systems, especially in modeling cyber-attack impacts and improving grid resilience. His recent articles emphasize practical applications in sustainable transportation and secure grid operation under uncertainty. Scientific Contributions: Developed optimization frameworks for preventive control with search space reduction. Applied mean-variance mapping optimization to enhance dynamic security. Explored machine learning benchmarks for transient stability under cyber threats. Contributed to battery modeling and energy efficiency in electric buses. Advising and Grants: While specific details on students or funded projects are not available in the provided text, his collaborative research patterns suggest active supervision and team-based research in power systems and energy technology. He frequently co-authors with researchers from Istanbul Technical University, indicating strong institutional collaboration. Labs and Teams: Though no specific lab or research group is named, his work aligns with smart grid, energy systems, and optimization research teams within the Department of Electrical Engineering at ITU. His focus on real-time data and cyber-physical systems suggests potential involvement in intelligent grid monitoring and control initiatives.

Athanasios Koliosمشاهده پروفایل

استاد

• Wind Turbine Engineering
• Offshore Wind Turbines Engineering
• Offshore Wind Farms Engineering
• +۳ مورد دیگر

Athanasios Kolios serves as Professor and Head of the Structural Integrity and Loads Assessment section within the Department of Wind and Energy Systems at the Technical University of Denmark (DTU). His work focuses on advancing wind energy technology through structural analysis, materials science, and system optimization for both onshore and offshore applications. His primary research domains include wind turbine structural integrity, offshore wind farm layout optimization, and structural health monitoring systems. He investigates critical challenges in operation and maintenance strategies, techno-economic metrics for wind projects, and materials behavior under dynamic loading conditions. His fingerprint analysis reveals dominant expertise in Wind Turbine Engineering (100%), Offshore Wind Turbines Engineering (45%), and Offshore Wind Farms Engineering (36%). Recent publications demonstrate strong emphasis on data-driven approaches for wind energy systems, including structural optimization algorithms, virtual sensing techniques, and techno-economic assessments of offshore projects. His work consistently bridges theoretical engineering principles with practical industry applications, particularly in Brazilian and European offshore wind contexts. Scientific Awards: No scientific awards were documented in the provided information Professor Kolios actively supervises five PhD candidates across major research initiatives while mentoring Master's students in structural wind energy applications. His research portfolio includes six significant projects addressing critical industry needs: PhD Supervision: Chopard (anomaly interpretation), Piovesan (risk-based technology qualification), Yildirim (floating turbine uncertainty), Rodrigues Faria (autonomous operation), Al-Hagri (offshore structure maintenance) Master's Supervision: Rushil S. Mahajan (monopile buckling analysis) Current Projects: Decision support systems, life cycle cost modeling, floating wind turbine modeling, autonomous operation frameworks, sustainable offshore structure design As section head at DTU Wind and Energy Systems, he leads an internationally collaborative research group focused on structural integrity assessment, load prediction methodologies, and materials innovation for next-generation wind turbines. The team maintains strong industry partnerships and contributes to global wind energy standards development through participation in initiatives like ISSC.

• Cloud Computing
• Distributed Computing
• Parallel Computing
• +۱۰ مورد دیگر

Professor Javid Taheri is a leading academic at Karlstad University (2019–present), previously serving as Associate Professor (2015–2019) and Senior Lecturer (2015). His research focuses on cloud computing, edge computing, distributed systems, and AI-driven networking. He holds a Ph.D. in Information Technologies from The University of Sydney (2007) and an M.Sc./B.Sc. in Electrical Engineering from Sharif University of Technology (2000/1998). Research interests include cloud-edge continuum systems , resource optimization , 5G/6G networking , and AI for IoT . Notable contributions include frameworks like PerfSim (microservice performance simulation) and MultiScaler (auto-scaling for cloud applications). Publications highlight innovations in edge computing optimization, security for distributed systems, and machine learning for resource management. He has co-authored over 150 papers across top venues like IEEE Transactions and ACM conferences. Academic leadership includes roles as conference chair (IC2E 2023) and editorial work for journals on cloud and edge computing.

Abdullah Karamanمشاهده پروفایل

استاد

• Geophysical Engineering
• Hydrothermal Systems
• Seismic Data Analysis
• +۳ مورد دیگر

Abdullah Karaman is a Professor at the Department of Geophysical Engineering, Istanbul Technical University (ITU). His research focuses on geophysical modeling, subsidence due to longwall mining, hydrothermal systems, and seismic data analysis. He leads projects on geothermal applications using particle swarm optimization and collaborates internationally. Dr. Karaman has supervised 8 ongoing theses and has authored/co-authored over 17 publications since 1997. His work spans geophysical exploration, environmental geohazards, and subsurface imaging techniques. Education: Master of Science in Geophysics (1989) Research Interests: Hydrothermal system characterization using magnetotelluric methods Seismic inversion and diffraction imaging Geophysical monitoring of coal mine subsidence Optimization algorithms in geophysical data analysis Awards: None explicitly mentioned. Grants & Projects: Geothermal Applications of Particle Swarm Optimization Modeling Technique (2016–2021) Kordil Engineering Company: Geophysical consulting for international projects (2021) His lab focuses on integrating geophysical techniques with machine learning for high-resolution subsurface imaging.

Lynda A. Khalafمشاهده پروفایل

استاد

• Econometrics
• Energy Economics
• Financial Economics
• +۶ مورد دیگر

Lynda A. Khalaf is a Full Professor and Co-Director of the CMFE at Carleton University's Department of Economics, part of the Faculty of Public and Global Affairs. She holds a B.A. and M.B.A. from Beirut and a Ph.D. from Université de Montréal. Her research focuses on econometrics, energy econometrics, and financial econometrics, with expertise in simulation-based inference, identification-robust methods, and multivariate models. Khalaf has over 40 publications in top journals like the Journal of Econometrics and Review of Economic Studies, and her work has been cited over 1,300 times. She served as Canada Research Chair (Tier II, 2004–2008), and her contributions include groundbreaking work on Monte Carlo tests and exact simulation-based inference. She has advised numerous students, many of whom have won awards for their thesis work. Khalaf has held editorial roles, organized major conferences, and chaired committees such as the SSHRC Adjudication Committee for Economics. Her research addresses challenges in financial, macroeconomic, and environmental models, emphasizing methodological innovations and practical applicability.

• Structural Engineering
• Energy Efficiency in Buildings
• Sustainable Architecture
• +۳ مورد دیگر

Juliana Felkner is an academic affiliated with ETH Zurich, primarily associated with the Department of Architecture within the School of Architecture, Civil and Environmental Engineering. Her research focuses on integrating structural efficiency with energy performance in tall buildings, emphasizing multi-objective optimization and sustainable design principles. Key contributions include studies on embodied vs. operational energy in buildings, structural design frameworks balancing sustainability and efficiency, and interactive optimization techniques using NURBS curves and Particle Swarm Optimization (PSO). Her doctoral thesis (2016) explored multi-objective design strategies addressing structural, environmental, and architectural considerations. Felkner has published extensively on topics such as energy lifecycle analysis, natural ventilation potentials, and computational design methods. Her work highlights the importance of reducing operational energy in existing building stocks to mitigate greenhouse gas emissions. Awards and grants are not explicitly mentioned in the provided texts, but her peer-reviewed publications indicate active engagement in academic research and collaboration across disciplines.

• Battery Management Systems
• Electric Vehicles
• Lithium-ion Batteries
• +۱۴ مورد دیگر

Professor Weixiang Shen is a full Professor in the Department of Engineering Technologies at the School of Engineering, Swinburne University of Technology, Melbourne, Australia. He holds a PhD in Electrical Engineering and has extensive academic experience across China, Germany, Singapore, and Malaysia. Bachelor of Engineering (BEng), Electrical Engineering Master of Engineering (MEng), Electrical Engineering Doctor of Philosophy (PhD), Electrical Engineering His research focuses on battery management systems for electric vehicles and renewable energy integration. Key areas include battery capacity estimation, charging strategies, fault diagnosis, thermal and mechanical management, and grid integration of EVs. He employs advanced techniques such as physics-informed machine learning, electrochemical modeling, and multidimensional sensing to enhance battery safety and performance. His recent publications (2024–2025) reveal a strong trend toward intelligent battery health monitoring, degradation modeling, and innovative thermal management using origami-inspired designs. These works appear in top journals like Applied Energy , IEEE Transactions , and Journal of Energy Chemistry . Associate Editor, IET Power Electronics Editorial Board Member, Journal of Energy Storage Founding Board Member, Vehicles Guest Editor, Applied Energy , Journal of Cleaner Production , Energy General Chair, ICEEE2018 Program Chair, CoEEPE2023 Professor Shen actively supervises PhD and Master’s students in areas such as battery fault diagnosis, energy storage, and control systems. His research is supported by grants from the Australian Research Council, Department of Industry, Science and Resources, and industry partners. He leads projects on intelligent energy management, battery testing, and EV control systems. His lab explores cutting-edge topics including solid-state batteries, multidimensional sensing, and origami-based thermal solutions for battery packs.

Kyle J. M. Bishopمشاهده پروفایل

استاد

• Active Matter
• Colloidal Assembly
• Soft Matter Physics
• +۳ مورد دیگر

Kyle J. M. Bishop is Professor of Chemical Engineering at Columbia University's Fu Foundation School of Engineering and Applied Science (Columbia Engineering), where he leads research at the intersection of active matter, soft materials, and micro-robotics. Appointed in 2016 after serving as Assistant Professor at Penn State and postdoctoral fellow with George Whitesides at Harvard, his work focuses on non-equilibrium assembly of colloidal systems. Education: BS in Chemical Engineering (highest distinction), University of Virginia PhD, Northwestern University Professor Bishop's research pioneers strategies for directing colloidal assembly outside thermodynamic equilibrium, with emphases on magnetic micro-robot navigation, synchronization phenomena in active matter, and electrochemical control of soft materials. His lab develops fundamental principles for programming collective behavior in synthetic systems, bridging chemical engineering, physics, and robotics to create materials with lifelike functionalities. Recent work explores biomolecular condensates, field-driven transport, and non-equilibrium information processing. Analysis of his 2023-2025 publications reveals a cohesive trajectory toward autonomous control of active systems: magnetic micro-robots navigate complex landscapes through field programming, enzymatic coacervates implement biological feedback loops, and oscillator networks achieve emergent synchronization. These studies span soft matter physics, electrochemistry, and microfluidics, consistently targeting applications in programmable materials and environmental engineering while advancing non-equilibrium thermodynamics. Scientific Awards: 3M Non-tenured Faculty award NSF CAREER award for 'Contact Charge Electrophoresis for Mobile Microfluidics' Professor Bishop secures substantial research funding including his NSF CAREER grant developing contact charge electrophoresis for microfluidic applications. While current students aren't listed in source materials, his lab trains graduate researchers in experimental soft matter physics and micro-robotics. His group collaborates across disciplines to translate fundamental discoveries into technologies for targeted delivery and environmental remediation. The Bishop Lab at Columbia Engineering operates as an interdisciplinary hub where chemical engineers, physicists, and materials scientists develop experimental platforms for manipulating colloids at fluid interfaces, with recent work focusing on magneto-capillary dynamics and field-programmable micro-robot swarms.

Pedro Nardelliمشاهده پروفایل

استاد

• Cyber-physical Systems
• IoT in Energy Systems
• Smart Grids
• +۵ مورد دیگر

Pedro Nardelli is a Full Professor (tenured) of IoT in Energy Systems at the LUT School of Energy Systems, Lappeenranta University of Technology (Finland). He holds a double doctoral degree in electrical engineering from the University of Campinas (Brazil) and communications engineering from the University of Oulu (Finland). As a Docent in Information Processing and Communications Strategies for Energy Systems, he leads research in cyber-physical systems, smart grids, and 6G-enabled energy networks. Research Interests : His work focuses on integrating IoT, AI, and communication technologies into energy systems. Key areas include cyber-physical systems, UAV-enabled networks, sustainable energy management, and cybersecurity in critical infrastructure. He emphasizes interdisciplinary approaches to address challenges in the green-digital transition. Projects & Leadership : He is Principal Investigator for projects such as 'Energy-Conscious Operation: Network Efficiency for Wireless Sustainability' (2024–2026) and coordinates the Finnish-Brazilian AI and 5G training program. Past roles include leadership in the 'Hydrogen and Carbon Value Chains in Green Electrification' initiative (2021–2024). Publications : Recent work explores topics like hybrid optimal power flow models, UAV-IRS NOMA systems, and energy-centric analysis. His research bridges theoretical frameworks with practical applications, emphasizing sustainability and resilience in energy networks. Labs & Teams : Leads the IoT Solutions group within LUT's MORE SIM research platform, focusing on simulation-driven innovation for energy systems.

• Edge Computing
• Fog Computing
• Cloud Computing
• +۴ مورد دیگر

Dragi Kimovski is a Habilitated Assistant Professor in Distributed Systems at Klagenfurt University, Austria, focusing on Edge Computing and AI. He previously held roles at the University of Innsbruck and the University of Information Science and Technology in Macedonia. His research spans Edge/Fog/Cloud computing, multi-objective optimization, and high-performance computing. He has coordinated major projects like 6GContinuum and KärtnerFog, and led initiatives such as DataCloud and ASPIDE. His teaching includes courses on Distributed Computing, Cloud Computing, and IoT. He is the co-creator of the Carinthian Computing Continuum and maintains a blog on Edge AI World. His work emphasizes sustainable and efficient computing solutions for emerging technologies. Education: Not explicitly listed in the provided text. Research Interests: Edge Computing, Fog Computing, Cloud Computing, Multi-objective Optimization, High-Performance Computing, AI in Distributed Systems. His work addresses challenges in resource management, latency reduction, and scalability across heterogeneous environments, with applications in healthcare, IoT, and 6G networks. Projects: 6GContinuum (Coordinator): Focuses on AI services over 6G networks. KärtnerFog (Scientific Coordinator): Develops adaptive Fog infrastructures over 5G. DataCloud (WP5 Leader): Manages Big Data pipelines on the Computing Continuum. ASPIDE (Scientific Coordinator): Advances exascale programming models for data processing. Teaching: Klagenfurt University: Courses include Distributed Computing, IoT, Cloud Computing, and Advanced Programming. University of Innsbruck: Taught Advanced Parallel and Distributed Systems. University of Information Science and Technology: Courses in High-Performance Computing and Network Architectures. Labs/Teams: Co-created the Carinthian Computing Continuum, an automated SDN testbed for Edge computing research. Active in interdisciplinary teams addressing extreme data processing and sustainable computing.

Liping Wangمشاهده پروفایل

استاد

• Building Performance Modeling
• HVAC Fault Detection and Diagnosis
• Energy Efficiency in Indoor Agriculture
• +۹ مورد دیگر

Liping Wang is a Professor in the Department of Civil and Architectural Engineering at the University of Wyoming, part of the College of Engineering and Physical Sciences. She also serves as the Director of the Center for Controlled Environment Agriculture, highlighting her leadership in sustainable building and agricultural systems. Her work bridges engineering, energy efficiency, and environmental resilience. Academic Background: B.S., Xi’an University of Architecture and Technology, China M.S., Xi’an University of Architecture and Technology, China Ph.D., National University of Singapore Her research interests focus on building performance modeling, fault detection and diagnosis for HVAC systems, energy efficiency in indoor agriculture, and the development of resource-efficient and resilient future communities. She applies data-driven and adaptive modeling techniques to enhance building energy systems and indoor environmental quality. The analysis of her recent publications reveals a strong trend toward intelligent building systems, with recurring use of machine learning (e.g., Gaussian mixture models, particle swarm optimization) for HVAC modeling, fault detection, and energy optimization. Her work increasingly integrates controlled environment agriculture, reflecting a shift toward sustainable food-energy-water nexus solutions. Topics span from fundamental thermodynamics to applied field evaluations of ASHRAE standards. Scientific Awards: NSF CAREER Award (1944823), National Science Foundation, 2019 Appreciation Award, Advisor of ASHRAE Student Branch, University of Wyoming, 2019 Liping Wang has secured competitive research funding, notably the NSF CAREER Award, and mentors students through research and professional engagement. She actively contributes to the academic community as an Associate Editor of the International Journal of Sustainable Energy Technologies and Assessments and a guest editor for Energy and Buildings . Her work involves interdisciplinary collaboration, with co-authors from diverse engineering and environmental science backgrounds. She has served as an ad hoc reviewer for top journals including Building and Environment , Energy and Buildings , and Applied Energy . She leads the Center for Controlled Environment Agriculture, which likely involves a research team focused on energy-efficient indoor farming technologies, greenhouse modeling, and sustainable building-agriculture integration. Her lab appears to utilize low-cost sensor systems (e.g., Arduino-based platforms) for real-time monitoring of environmental conditions.

BÜLENT HAZNEDARمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Fuzzy Logic
• +۵ مورد دیگر

Bülent Haznedar is an Associate Professor in the Department of Computer Engineering at Gaziantep University's Faculty of Engineering, a position he has held since 2024. Previously, he served as Doctor Lecturer at Gaziantep University (2021-2024) and held academic positions at Hasan Kalyoncu University (2013-2021) and Erciyes University (2011-2013), where he progressed from Lecturer to Department Head. His educational qualifications include: Doctorate in Computer Engineering from Erciyes University (2011-2017) Master's degree in Computer Engineering from Erciyes University (2007-2010, with thesis) Licence degree in Computer Engineering from Erciyes University (2003-2007) Dr. Haznedar's research centers on Artificial Intelligence and Machine Learning applications, with significant contributions in hydrological modeling (streamflow forecasting using hybrid ANFIS algorithms), renewable energy (solar radiation optimization), medical diagnostics (thyroid nodule classification and cancer detection), and cultural heritage informatics (3D point cloud segmentation for historical buildings). His work consistently integrates fuzzy logic systems with metaheuristic optimization techniques to solve complex prediction problems. Analysis of his 29 journal articles (2016-2024) reveals a dominant focus on Adaptive Neuro-Fuzzy Inference Systems enhanced by evolutionary algorithms (PSO, GA, ABC) across hydrology and medical domains, with recent expansion into sustainable energy and heritage preservation. His publications show increasing interdisciplinary collaboration, particularly in TUBITAK-funded projects. His scientific recognition includes: TUBITAK Publication Encouragement Awards (2018, 2023) TUBITAK PhD Scholarship (2011) TUBITAK Master's Scholarship (2008) Dr. Haznedar has supervised eight master's theses on AI applications in streamflow forecasting, energy prediction, cancer classification, and heritage modeling. His research is supported by seven projects, most notably the TUBITAK 1001 project (2019-2023) developing Heritage Building Information Modeling for Turkey's cultural heritage restoration. He also contributed to TUBITAK's Digital Prosthesis Workshop initiative. While specific laboratory affiliations aren't detailed, his leadership in the TUBITAK cultural heritage project indicates active collaboration with multidisciplinary teams spanning engineering, computer science, and heritage conservation disciplines.

• Supply Chain Management
• Sustainable Operations
• Reverse Logistics
• +۵ مورد دیگر

Devika Kannan is an Associate Professor at the Department of Technology and Innovation , University of Southern Denmark, and a member of the SDU Centre for Sustainable Supply Chain Engineering . Her work focuses on integrating sustainability into supply chain practices, particularly for SMEs. Research Interests : Supply Chain Management, Reverse Logistics, Green Supply Chain, Multi-Criteria Decision-Making, Closed Loop Systems, Circular Economy, and SMEs. Recent Projects : Circular economy to minimize waste challenges in Indonesia (IndoCircularWaste) (2021-2024), SDG Tools - Toolkit for the implementation of SDGs through the Circular Economy Practices (2020-2023). Scientific Awards : Emerald Citations of Excellence for 2017 Grants : Recipient of DKK 5 million from the Carlsberg Foundation (2021) to study female entrepreneurs in the green economy. Publications highlight trends in sustainable reverse logistics, smart waste management frameworks, blockchain integration in manufacturing, and machine learning applications in healthcare and supply chain optimization. Editorial Roles : Editor for the International Journal of Advanced Operations Management and International Journal of Business Performance and Supply Chain Modelling (since 2016).

Glenford Mappمشاهده پروفایل

دانشیار

• Intelligent Transportation Systems
• Networking Protocols
• Cybersecurity
• +۶ مورد دیگر

Dr. Glenford Mapp is an Associate Professor in the Department of Computer Science at Middlesex University. His research focuses on Cooperative Intelligent Transportation Systems (C-ITS), transport protocols for mobile environments, and edge computing frameworks such as the Y-Comm system. He explores intelligent algorithms for caching, network memory servers, and energy-efficient resource allocation in vehicular edge networks. His work emphasizes cybersecurity in healthcare, digital forensics for big data networks, and smart city infrastructure. Notable contributions include frameworks for secure service ecosystems, decentralized digital forensics, and AI-driven network design integrating IoT and cloud computing. He collaborates on projects involving vehicular communications, wireless medical networks, and post-pandemic healthcare security. Publications span topics like edge computing, vehicular networks, and smart city technologies. His research bridges theoretical models (e.g., queuing theory, particle swarm optimization) with practical implementations, including prototypes for traffic management and secure cloud-based services.