جست‌وجوی استاد و پژوهشگر

Janusz Kacprzykمشاهده پروفایل

استاد

• Computational Intelligence
• Fuzzy Logic
• Decision Theory
• +۸ مورد دیگر

Janusz Kacprzyk is a Professor of Computer Science at the Systems Research Institute of the Polish Academy of Sciences and Professor of Automatic Control at PIAP – Industrial Institute of Automation and Measurements. He also holds the title of Honorary Professor of Mathematics at Yli Normal University, Xinjiang, China. With a career spanning multiple institutions and international roles, he is a distinguished figure in computational intelligence and systems research. M.Sc. in Automatic Control and Computer Science, Warsaw University of Technology (1977) Ph.D. in Systems Analysis (1977) D.Sc. in Computer Science (1991) His research focuses on computational intelligence , including fuzzy logic , granular computing , decision theory , optimization , and mobile robotics . He has contributed extensively to soft computing applications in economics and management, data mining, and systems modeling. He has received numerous honors, including: 2006 IEEE CIS Pioneer Award in Fuzzy Systems 2006 Kaufmann Prize and Gold Medal 2007 IEEE CIS Silicon Valley Pioneer Award IFSA 2013 Lifetime Achievement Award 2014 World Automation Congress Lifetime Award Kacprzyk is a Full Member of the Polish Academy of Sciences, Member of Academia Europaea, and holds fellowships from IEEE, IET, IFSA, and other organizations. He has served as President of the Polish Operational and Systems Research Society and Past President of the International Fuzzy Systems Association.

Mahdi Farnaghiمشاهده پروفایل

استادیار

• Artificial Intelligence
• Machine Learning
• Data Mining
• +۹ مورد دیگر

Mahdi Farnaghi is an Assistant Professor at the University of Twente , specializing in the Department of Geo-Information Processing . His research spans Artificial Intelligence , Machine Learning , and Geospatial Analysis , with applications in Environmental Monitoring , Public Health , and Urban Mobility . He leads the NWO-NGF IntelliGeo project (2024-2025), integrating Large Language Models into GIS workflows. Focus areas: Wastewater-based epidemiology , AI-powered environmental modeling , and spatiotemporal analysis Recent work: Machine learning frameworks for pollutant mapping , crop water needs , and infectious disease distribution The 2025 TU Delft Water for Impact Best Paper Award recipient for collaborative research on wastewater modeling. His projects include EO AFRICA R&D Innovation Lab and software tools for reproducible geospatial research .

• Artificial Intelligence (AI)
• Cyber-Physical Systems (CPS)
• Mobile Health (mHealth)
• +۷ مورد دیگر

Anne Håkansson is a Professor at the Department of Informatics , UiT The Arctic University of Norway . Her research bridges Artificial Intelligence and Cyber-Physical Systems with applications in mHealth and Smart Energy Systems . Current research focuses on proactive health promotion via digital twins and wearables. Explores robust reasoning in autonomous systems and smart nudging for behavioral change. Recent work includes AI for battery digitalization and multi-agent collision avoidance in dynamic environments. She contributes to Springer and Procedia Computer Science publications, with emphasis on context-aware AI and sustainable technologies . Active in the Open Distributed Systems (ODS) and Computational Analytics and Intelligence (CAI) research groups, and involved in projects like Better Balance in Informatics (BBI) and the Nudge Project .

• Data Mining
• Big Data
• Fuzzy Systems
• +۹ مورد دیگر

Carlos Jesús Fernández Basso is a Post-Doc Researcher at the Universidad de Granada in the Department of Computer Science. His work focuses on the intersection of Big Data, Data Mining, and Fuzzy Systems, with applications in energy efficiency, social network analysis, and medical diagnostics. His research interests include: Energy-efficient building management using IoT and Big Data Distributed frequent itemset mining and association rule discovery Fuzzy logic for data interpretability in complex systems Text mining and pattern detection in social media Recent publications highlight his contributions to Spark-based distributed algorithms, predictive control systems, and visualization of fuzzy association rules. He collaborates with researchers across disciplines, including applications in healthcare and cybersecurity.

• Artificial Intelligence
• Fuzzy Linguistics
• Decision-Making Systems
• +۴ مورد دیگر

Núria Agell Jané is a Full Professor at the Department of Operations, Innovation and Data Sciences within Esade School of Business Administration and Management at Universitat Ramon Llull. She leads the Institute for Data-Driven Decisions (ESADE D3) and has maintained an active research agenda since 1984 with 178 scientific productions and 26 projects. Her Scopus profile shows an h-index of 20 and 98 citations in her 2023 publication on Production Planning and Control. Research Interests: Artificial Intelligence Fuzzy Linguistic Methodologies Decision-Making Systems Human-Computer Interaction Food Waste Reduction Industry 4.0 Technologies Scientific Awards: Scopus h-index of 20 98 citations in 2023 publication Recent Research Trends: Applying hesitant fuzzy linguistic term sets to conflict analysis (2025) Developing qualitative reasoning frameworks for environmental concerns (2025) Innovating in health sector malpractice detection using deep learning (2024) Advancing food waste reduction through data-driven models (2023) Integrating lean-agile manufacturing with Industry 4.0 (2023)

Lipika Dekaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Data Science
• Concurrency Control
• +۵ مورد دیگر

Dr. Lipika Deka is an Associate Professor and Faculty Head of Research Students at De Montfort University's School of Computer Science and Informatics. She is affiliated with multiple research groups including The Institute of Artificial Intelligence, The De Montfort University Interdisciplinary Group in Intelligent Transport Systems (DIGITS), and the Software Technology Research Laboratory. Dr. Deka holds a PhD in Computer Science and Engineering from Indian Institute of Technology (IIT) Guwahati, an MTech in Computer Science and Information Technology, and a BEng in Computer Science and Engineering. Her academic journey began with a passion for operating systems and network programming, which led to her PhD work on transactional file systems and online backup algorithms. Dr. Deka's research spans multiple interdisciplinary domains at the intersection of computer science and real-world applications. Her primary areas of expertise include: Concurrency control techniques for consistent, architecture-preserving online software updates in autonomous vehicles and IoT devices Machine learning applications for Intelligent Transportation Systems Downstream space applications including smart agriculture (particularly for climate change adaptation) and soil/water analysis AI techniques for reducing e-waste by facilitating longer lifespans of digital items Analysis of Dr. Deka's recent publications reveals a strong focus on applying artificial intelligence and machine learning to solve critical transportation, environmental, and healthcare challenges. Her work demonstrates a trend toward interdisciplinary research that bridges computer science with practical applications in autonomous vehicles, environmental monitoring, precision agriculture, and public health infrastructure. Notably, her research shows increasing integration of satellite data with ground-level applications, particularly in agriculture and environmental monitoring. Dr. Deka has received the Faculty Staff Leadership Award in 2019 for her contributions to academia. Her leadership extends to professional organizations as well, where she served as Vice-Chair of the Association of Computing Machinery - UK Women's Chapter (2017-2020) and Lead of the European Volunteers Network, ACM Women's Chapter (2020-2022). As an academic supervisor, Dr. Deka has successfully guided numerous PhD students to completion while currently advising six doctoral candidates. Her research portfolio includes significant projects such as: Co-I on STAGE I (2022-23): EIT Food Seedbed pre-incubation for OPTIcut Advisory board member for a THIS Institute fellowship (2022-2026) Participant in a Spanish Government-funded project on photovoltaic systems (2022-2026) Project Partner on an EPSRC Discipline Hopping Award for smart water treatment (2020-2024) Entrepreneurial Lead on INNOVATE UK's ICURe project for OPTIcut (2020) Academic Supervisor for a Knowledge Transfer Partnership with Geospatial Insight Ltd (2018-2020) De Montfort University PI for the Transport Catapult-sponsored IMPART project (2015-2018) Dr. Deka's research is conducted through multiple collaborative frameworks including The Institute of Artificial Intelligence, the De Montfort University Interdisciplinary Group in Intelligent Transport Systems (DIGITS), and the Software Technology Research Laboratory. These groups facilitate cross-disciplinary collaboration between computer scientists, transportation engineers, environmental scientists, and healthcare professionals to address complex societal challenges through technological innovation.

Pedro Martín Vallejo Llamasمشاهده پروفایل

استاد

• Control Systems
• Automation
• Process Control
• +۳ مورد دیگر

Professor Pedro Martín Vallejo Llamas serves in the Department of Computer Science and Automation at the University of Salamanca, specializing in process supervision and control systems with emphasis on industrial applications. His research profile centers on advanced control methodologies, particularly evidenced by his 2021 doctoral work supervised by Dr. Pastora Isabel Vega Cruz. Key focus areas include: Real-time process monitoring Model-based predictive control frameworks Fuzzy logic integration for complex system management Water treatment infrastructure optimization He actively contributes to the PROCESS SUPERVISION AND CONTROL research group, driving innovation in automation technologies for critical infrastructure systems.

• Robotics
• Artificial Intelligence
• Mechatronics
• +۶ مورد دیگر

Dr. Theodoros Theodoridis serves as Associate Professor (Reader) in Robotics and Intelligent Systems and Head of the Department of Aeronautical and Mechanical Engineering at the University of Salford's School of Science, Engineering & Environment. He leads the Intelligent Mobility research area at the North England Robotics Innovation Centre (NERIC) and is a key member of the Autonomous Systems and Advanced Robotics (ASAR) research group. His research has secured over £1.8 million in funding from EC FP5-7, EPSRC, MRC, Innovate UK, and the Regional Growth Fund. Dr. Theodoridis completed his academic training with the following qualifications: BEng in Automation Engineering from Technological Educational Institute of Piraeus, Greece MSc in Embedded Systems and Robotics from University of Essex, UK PhD in Intelligent Crime-Recognition Surveillance Robots from University of Essex, UK His research spans three primary domains with significant technical depth. In Service Robotics, he develops specialized robots including nurses, maids, guards, companions, and entertainers. His Artificial Intelligence work integrates classical AI, machine learning, deep learning, fuzzy logic, and probabilistic reasoning to create intelligent robotic systems. His Embedded Systems and Mechatronics expertise covers mechanical modeling, electronic/PCB design, and embedded programming, with applications across multiple disciplines. Recent publications (2023-2025) demonstrate a strategic shift toward practical applications in healthcare rehabilitation and industrial automation. His work on cable-driven exosuits and soft sensors for gesture recognition addresses critical challenges in upper limb rehabilitation. Earlier research (2018-2020) established foundational work in pneumatic actuators and continuum robotics that now informs his current applied research directions. His publications consistently bridge theoretical robotics with real-world implementation across medical, manufacturing, and construction sectors. Dr. Theodoridis maintains active industry collaborations that translate research into practical solutions. His grant portfolio demonstrates consistent success in securing competitive funding across multiple research councils and funding bodies. As an educator, he teaches Mechatronics, Advanced Embedded Systems, Mobile Robotics, and supervises final year projects and dissertations. His leadership extends to directing departmental operations while maintaining an active research program through the Centre for Future Engineering and NERIC.

• Mathematics
• Differential Equations
• Composite Materials
• +۴ مورد دیگر

Jüri Majak is a Tenured Full Professor at Tallinn University of Technology's School of Engineering, Department of Mechanical and Industrial Engineering since 2019. Previously, he served as a Leading Research Fellow (2017-2019) and in various research positions since 2005. His academic career spans multiple institutions including Tartu University (1992-2002) and Audentes University (2003-2005). He holds a Doctor's Degree in Mathematics from the University of Tartu (1993). Majak earned his Applied Mathematics degree from the University of Tartu in 1984, followed by a Doctor of Science in Mathematics in 1993. His doctoral thesis focused on "Optimization of plastic axisymmetric plates and shells in the case of von Mises material" under the supervision of Jaan Lellep. Professor Majak's research spans mathematical methods, composite materials, and artificial intelligence. He specializes in the Higher Order Haar Wavelet Method for solving differential equations, structural analysis and design optimization, and applying evolutionary optimization and neural networks to engineering problems. His work bridges theoretical mathematics with practical engineering applications, particularly in structural health monitoring, composite materials analysis, and autonomous systems. His recent publications demonstrate a clear trend toward integrating advanced mathematical methods with AI techniques for engineering applications. The research focuses on structural health monitoring using wavelet transforms and neural networks, optimization of production logistics with autonomous mobile robots, and risk analysis for autonomous vehicle systems. There's a strong emphasis on practical applications of mathematical methods to solve complex engineering problems in materials science, robotics, and industrial processes. Professor Majak actively supervises students and leads research initiatives: Supervises Bachelor theses including reinforcement learning for vehicle control and object detection for quality control Supervised postdoc Mustafa Arda on numerical methods for composite and nanostructures analysis (2021-2022) Leads the research group "Advanced structures and products" since 2019 Directs the Doctoral Program in Engineering Sciences since 2024 Participates in the PARROT Project on Structural Damage Detection (2023-2024) Professor Majak is actively involved in research administration and scholarly activities. He serves on the editorial boards of several prestigious journals including Composites Part C (Elsevier, Q1), Mechanics of Composite Materials (Springer, Q2), and the International Journal for Simulation and Multidisciplinary Design Optimization. He also leads the "Advanced structures and products" research group at Tallinn University of Technology and serves on the Department of Mechanical and Industrial Engineering Board.

Thabit Thabitمشاهده پروفایل

مدرس

• Accounting
• Financial Accounting
• Auditing
• +۶ مورد دیگر

Thabit Thabit is an academic faculty member specializing in Accounting at Cihan University in Erbil, Iraq. He also holds a position at Ninevah University in the Computer and Information Engineering Department. With an M.Sc. in Accounting and currently pursuing a Ph.D. in Financial Accounting, his academic career spans multiple disciplines including accounting, finance, management, and IT applications. His primary research interests include Financial Accounting, Auditing, IFRS, Oil and Gas Accounting, and the application of fuzzy logic in accounting decision-making. His research portfolio demonstrates expertise in both theoretical accounting frameworks and practical business applications, with numerous publications addressing contemporary challenges in financial reporting, auditing practices, and educational technology. His recent publications (2021-2023) show a strong focus on pandemic-related financial challenges, knowledge sharing in educational institutions, and the intersection of information technology with traditional accounting practices. His work often employs advanced statistical methods including fuzzy logic and structural equation modeling. Thabit has demonstrated interdisciplinary research capabilities, publishing in both accounting/finance journals and engineering/technology publications, reflecting his dual expertise in accounting and information technology.

Matthew Yenمشاهده پروفایل

مدرس

• Visual Programming
• Object Models in Business Applications
• Human Machine Interfaces
• +۸ مورد دیگر

Matthew Yen serves as a Lecturer in the Department of Industrial Technology at California State University, Fresno's Jordan College of Agricultural Sciences and Technology. Courses Taught: Technology and Society (IT 20) Technical Writing (IT 198W) Research Methodology Senior Seminar Applied Spatial Technology Applied Imaging Technology Programming Fundamentals Electricity & Electronics CAD Research Profile: Current Focus: Visual programming frameworks, object-oriented business modeling, human-machine interface design, socio-technical implications of technology, and agricultural/commercial applications of GIS/Remote Sensing systems. Historical Research: Neural network architectures, fuzzy logic control systems, AI-driven manufacturing processes, computer-integrated manufacturing (CIM), and microwave vacuum dehydration techniques for food preservation.

• Sustainable Orchestration in Edge-Cloud Environments
• Multi-Cloud Workload Distribution
• Large Language Models (LLMs) Deployment
• +۳ مورد دیگر

Dr. Hadi Tabatabaee Malazi is an Assistant Professor at the University of College Dublin (UCD), leading the Sustainable Orchestration in Computing Continuum (SOC² Lab). He holds an Orcid identifier (0000-0002-2960-6896) and has extensive academic experience across institutions like Maynooth University, Shahid Beheshti University, and Trinity College Dublin. His research focuses on sustainable computing, edge-cloud continuum orchestration, AI/ML deployment (e.g., LLMs), and energy efficiency. He is a Senior Member of IEEE, serves as an Associate Editor for IEEE Access, and chairs the COST Action CA22151 (CYPHER) on decarbonizing energy-intensive industries. Education: PhD (2012): University of Isfahan (Computer Engineering) MSc (prior to 2012): University of Isfahan Research Visit (2010-2011): Delft University of Technology Research Interests: Sustainable edge-cloud systems, AI-driven workload optimization, carbon-aware resource management, distributed LLMs, and IoT interoperability. Key contributions include over 20 journal articles in IEEE, Elsevier, and Springer venues, with topics ranging from vehicular network security to smart city event processing. Professional Activities: Committee member of COST Action CA22151, IEEE Access Associate Editor, and Technical Program Committee member for IEEE conferences. Authored certifications on research leadership and research integrity from Epigeum. Labs/Teams: SOC² Lab (UCD), leading projects on edge-cloud sustainability and AI application deployment.

• Electrical Engineering
• Signal Processing
• Instrumentation
• +۵ مورد دیگر

Pedro Miguel Pinto Ramos is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Lisbon (Técnico Lisboa), affiliated with the Higher Technical Institute. His research focuses on signal processing, instrumentation, power quality analysis, and non-destructive testing. He teaches courses such as 'Instrumentation and Measurements' and '2nd Cycle Integrative Project in Electronic Engineering.' His work spans embedded systems design, magnetic material characterization, and applications in particle accelerator magnets. Recent contributions include deep learning techniques for power quality monitoring, eddy current testing probes using magneto-resistive sensors, and impedance spectroscopy for sensor modeling. He collaborates on projects like smart composting monitoring and robotic tactile sensors. Ramos has published extensively on topics including harmonic estimation algorithms, genetic algorithms for circuit identification, and low-cost measurement systems. His technical contributions include DSP-based data acquisition systems and real-time processing for eddy currents testing. He also works on low-frequency impedance measurement techniques and uncertainty analysis in electrical measurements. His research lab focuses on advancing non-destructive testing (NDT) through eddy current methods, with applications in friction stir welding inspection and material characterization for high-field superconducting magnets. Collaborations include work with CERN on magnetic material properties for Large Hadron Collider (LHC) upgrades.

• Mobile Communications
• 5G/6G Systems
• Machine-to-Machine (M2M) Communications
• +۷ مورد دیگر

Dr. Omar Alani is a Senior Lecturer and Head of the Networking and Mathematics Group at the School of Science, Engineering & Environment, University of Salford, UK. He holds a PhD in Telecommunication Engineering from De Montfort University and has held academic and research roles at Swansea University, the University of Leeds, and De Montfort University. His expertise spans Mobile Communications, 5G/6G systems, IoT, and Green ICT. Education: PhD (Telecommunication Engineering, De Montfort University, 2005), MSc (Advanced Control Systems), BEng (Electrical Engineering) Affiliations: Informatics Research Centre, University of Salford Research Interests: Alani focuses on advancing communication systems through projects in next-generation networks, including 6G/5G innovations, cognitive radio, and energy-efficient telecommunication solutions. His work intersects with renewable energy monitoring via ICT and smart grid technologies. He has authored over 90 publications and supervised multiple theses in these areas. Teaching: He teaches courses on Mobile Communication Networks, IoT, and Control Systems Engineering, emphasizing practical applications in postgraduate project management. Labs/Teams: Leads the Networking and Mathematics Group, collaborating on projects related to routing protocols, antenna design, and network security.

Devinder Kaurمشاهده پروفایل

استاد

• Intelligent Engineering Applications
• Bio-inspired Computational Algorithms
• Fuzzy Logic Systems
• +۴ مورد دیگر

Dr. Devinder Kaur is a Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo's College of Engineering. She holds a PhD in Computer Engineering from Wayne State University (1989), alongside degrees from the University of Aberdeen and Panjab University. Her research focuses on bio-inspired computational algorithms for engineering applications, including fuzzy logic, neural networks, and swarm intelligence. She has published over 100 articles and secured grants from NSF, Daimler Chrysler, and others. Education: PhD and MS in Computer Engineering, Wayne State University (1989, 1985) M.Sc. in Medical Physics, University of Aberdeen (1976) M.Sc. (Hons.) in Physics (Electronics), Panjab University (1970) Research Interests: Integrating intelligence into engineering systems using bio-inspired methods, nature-inspired machine learning, and parallel computing architectures. Her work spans applications in energy systems, medical imaging, and autonomous systems. Key Achievements: Developed courses like 'Biologically Inspired Computing' and 'Fuzzy Systems and Applications.' Summer fellowships at NASA Glenn, AFRL Dayton, and Daimler Chrysler. Fulbright Senior Specialist Award (lectured at Nippon Institute of Technology and Tokyo Denki University). Recipient of Thomas Rumble Fellowship, Commonwealth Fellowship, and Panjab University Medal. Grants & Contributions: Over $2M in research grants, including NSF support and industry partnerships. Active in professional societies like IEEE, WSEAS, and INFORMS. Labs/Teams: Leads research in bio-inspired computing and smart energy systems. Collaborates on interdisciplinary projects involving AI, medical diagnostics, and autonomous UAV systems.