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Iliev AtanasView profile

Associate Professor

• Electric Power Systems
• Optimization Algorithms
• Renewable Energy Systems
• +3 more

Assoc. Prof. Iliev Atanas is affiliated with the Faculty of Electrical Engineering and Information Technologies (FEIT) at the Ss. Cyril and Methodius University of Skopje. He holds the position of Associate Professor at the Institute for Power Plants and Switchgear. His academic journey includes a PhD (2003), MSc (1993), and BSc (1987) in Electrical Engineering from FEIT. His work experience spans over three decades, starting as a Junior Assistant (1987–1994), progressing to Assistant Professor (1994–2008), and attaining his current rank in 2008. His research focuses on optimizing power systems through advanced algorithms, particularly genetic algorithms applied to unit commitment, hydrothermal scheduling, and microgrid management. Key areas include renewable energy integration, grid reliability, and security-constrained optimization. He has contributed to over 50 publications addressing topics like dynamic programming for hybrid power systems, fuzzy logic for hydroelectric project evaluation, and reliability modeling of substations under distributed generation uncertainty. Notable contributions include developing novel self-adaptive genetic algorithms for short-term scheduling and energy management in hybrid systems. His work bridges theoretical optimization with practical grid challenges, emphasizing sustainability and resilience in power infrastructure.

Hojjat AdeliView profile

Professor

• Structural engineering
• Computational neuroscience
• Civil engineering
• +7 more

Hojjat Adeli is an Academy Professor at The Ohio State University (OSU) with courtesy appointments in the Departments of Neurology, Neuroscience, and Biomedical Informatics. He has held the Abba G. Lichtenstein Professorship in Infrastructure Engineering (2003-2013) and served as Editor-in-Chief of Computer-Aided Civil and Infrastructure Engineering for 25 years. Academy Professor, OSU (2018–present) Professor of Neurology, Neuroscience, and Biomedical Informatics (by courtesy, since 2015-2002) His research interests span interdisciplinary domains at the intersection of engineering and neuroscience, focusing on: Computational neuroscience and neurocomputing Biomedical signal processing (particularly EEG-based diagnostics) Machine learning and computational intelligence applications Smart infrastructure systems and structural engineering Optimization algorithms in civil and biomedical contexts His research trends demonstrate a synergy between: Neural network development for medical diagnostics Wavelet and chaos theory in epilepsy detection Computational intelligence for structural engineering Hybrid models integrating fuzzy logic and genetic algorithms Scientific awards and honors include: Multiple IEEE Fellowships and AAAS Fellow Thomson Reuters Highly Cited Researcher in Engineering and Computer Science Hojjat Adeli Awards for Neural Systems and Innovation in Computing Elections to international academies in Poland, Lithuania, and Spain Scott Award for Engineering Education and Distinguished Member ASCE

Hamed BadihiView profile

Assistant Professor

• Condition Monitoring
• Fault-Tolerant Control
• Attack-Resilient Control
• +3 more

Hamed Badihi is an Assistant Professor in Automation Technology and Dependable Systems at Tampere University , part of the Faculty of Engineering and Natural Sciences. He leads the Dependability and Automation Research in Cyber-Physical Systems (DARES) Group within the Dependable Systems Cyber Laboratories . His research focuses on critical aspects of condition monitoring, fault-tolerant control, and attack-resilient control to advance sustainable, dependable cyber-physical systems. Research Interests include: Cybersecurity for industrial control systems Fault-tolerant control mechanisms Resilient control strategies for renewable energy systems Condition monitoring of wind turbines and microgrids Recent Contributions emphasize hybrid approaches combining machine learning and control theory for cyber-attack detection and system resilience in wind farms and microgrids. His work addresses challenges like real-time fault diagnosis and adaptive control under adversarial or environmental perturbations. Awards & Roles : Senior Member of IEEE, editor for International Transactions on Electrical Energy Systems , Advances in Fuzzy Systems , and Processes journals. Active in EU projects like StreamSTEP . Labs & Teams : Directs the DARES Group, collaborating on initiatives like the Dependable Systems Cyber Laboratories to pioneer innovations in cyber-physical system dependability.

Gonzalo NápolesView profile

Assistant Professor

• Artificial Intelligence
• Machine Learning
• Cognitive Science
• +5 more

Gonzalo Nápoles is an Assistant Professor at Tilburg University's School of Humanities and Digital Sciences, Department of Cognitive Science and AI. He holds a Doctoral Degree in Computer Science from Rough Cognitive Networks (2014–2017). His research focuses on AI applications in cognitive modeling, pattern classification, and neural networks with interdisciplinary applications in healthcare, finance, and social sciences. Key research areas include Fuzzy Cognitive Maps, data augmentation techniques for neuroimaging, and interpretable machine learning systems. He actively contributes to UN Sustainable Development Goals related to education and innovation. Recent work explores AI ethics, financial risk assessment using dynamic networks, and sensory processing disorder analysis through neural networks. Education: Doctoral Degree in Computer Science, 2017 (Thesis: Rough Cognitive Networks) Prize-winning research includes Best Paper Awards at CIARP 2021 and IWAIPR 2023. He collaborates internationally, hosting academic visitors and serving on multiple PhD committees. Current projects involve stock prediction using graph neural networks and fMRI data augmentation methodologies. Awards: Best Paper Award - CIARP 2021 Best Paper Award - IWAIPR 2023 Nápoles advises on PhD theses in cognitive science and AI applications. His work bridges theoretical advancements with practical implementations in healthcare, finance, and urban systems.

• Software Technology
• Artificial Intelligence
• Educational Software
• +5 more

Maria Virvou serves as Professor and Chair of the Department of Informatics at the University of Piraeus, where she also directs the Graduate Program in Informatics and leads the Research Laboratory 'Software Technology'. She holds significant institutional leadership roles including membership in the University Senate and has chaired the Department of Informatics for multiple terms. As Editor-in-Chief of Springer book series 'Learning and Analytics in Intelligent Systems' and 'Artificial Intelligence-Enhanced Software and Systems Engineering', she maintains substantial academic influence across international scholarly platforms. Dr. Virvou earned her PhD in Computer Science and Artificial Intelligence from the University of Sussex with a scholarship from the State Scholarships Foundation, a Master of Science in Computer Science from University College London, and her undergraduate degree from the Department of Mathematics at the National and Kapodistrian University of Athens. Her educational background in both mathematics and computer science has provided a strong foundation for her interdisciplinary research approach. Professor Virvou's research spans Software Technology, Artificial Intelligence, Educational Software and Games, User Modeling, and Human-Computer Interaction. She has pioneered work in personalized interactive software systems, applying fuzzy logic and machine learning techniques to create adaptive educational environments. Her recent work demonstrates a strategic expansion into AI applications for healthcare, with significant contributions to medical diagnostics using large language models and multimodal AI systems. She has also made notable advances in smart tourism applications through personalization techniques. With over 400 publications to her name, Professor Virvou's scholarly output shows a clear progression from foundational work in user modeling toward increasingly sophisticated AI applications across multiple domains. Her publication trends reveal a strategic focus on explainable AI, multimodal systems, and practical implementations that bridge theoretical advances with real-world applications, particularly in healthcare and education sectors. Ranked #1 worldwide in 'User Modelling' publications (147,450 total publications) according to Scopus Ranked #1 worldwide in 'Educational Software' publications according to both Scopus and Microsoft Academic Search Recognized among the top 2% of most influential Artificial Intelligence scientists worldwide by Stanford University General Co-Chair at the 14th IISA Conference 2023 Invited Keynote Speaker at the 35th IEEE International Conference on Software Engineering Education and Training (CSEE&T 2023) As Director of the Research Laboratory 'Software Technology', Professor Virvou has built a robust research team focused on AI applications across multiple domains. She co-founded and co-chairs the IEEE Intelligent Information Systems and Applications international conference series, creating a significant platform for scholarly exchange. Her leadership extends to editorial roles with major academic publishers and active participation in international research collaborations that have secured substantial funding for innovative projects in AI and software engineering.

• Computer Science
• Machine Learning
• Health Monitoring Systems
• +7 more

Muhammad Waqas is a researcher affiliated with COMSATS University Islamabad , where he holds a position in the Department of Meteorology under the School of Applied Sciences and Humanities . His academic collaborations span institutions like Bahria University, National University of Technology, and University of Bahrain, indicating a multidisciplinary approach. Research interests include Mechanisms for integrating fuzzy logic and machine learning in health monitoring Application of deep learning to medical imaging and clinical diagnostics Development of smart sensors for wearable technology in biomechanics Analysis of social media data for public health surveillance and sentiment analysis Investigation of digital citizenship and ICT leadership in educational contexts Trends in his 15 most recent publications (2025-2024) reveal a focus on medical diagnostics (e.g., monkeypox, breast cancer), smart infrastructure (e.g., sensor placement, structural health monitoring), and social media analytics for health and behavioral insights. These works leverage machine learning , fuzzy systems , and multi-objective optimization .

• Smart Grids
• Renewable Energy Integration
• Optimization of Power Systems
• +4 more

Cuo Zhang is a Lecturer of Power Engineering and ARC DECRA Fellow at the University of Sydney's School of Electrical & Computer Engineering. He holds a B.E. (Hons.) from the University of Sydney (2014) and a Ph.D. in Electrical Engineering from UNSW (2018). His research focuses on smart grids, renewable energy integration, voltage control, and optimization of power systems. Key interests include distributed generation planning, energy storage systems, and demand response mechanisms. Dr. Zhang leads research on enhancing distribution network resilience through advanced control strategies and participates in the Net Zero Institute. He has secured grants such as the 2024 ARC DECRA project on renewables hosting capacity. Supervised students include Yunqing Zhang, working on robust renewables integration. His recent publications emphasize data-driven approaches, decentralized energy trading, and adaptive control for unbalanced networks. He explores machine learning applications in energy management and stochastic optimization under uncertainty. Awards include the University Medal for academic excellence. Awards: ARC DECRA Fellow Grants: 2024 Robust Renewables Hosting Capacity Enhancement Labs/Teams: Member of the Net Zero Institute

Ayşegül AksoyView profile

Professor

• Environmental systems engineering
• Integrated waste management
• Water quality modeling and management
• +4 more

Prof. Ayşegül Aksoy is a faculty member in the Department of Environmental Engineering at Middle East Technical University (METU) since 2002. She holds a Ph.D. in Civil Engineering from the University of Virginia (2000) and has held visiting roles at Stanford University (2015-2016) and the University of California Davis (2001). Her academic leadership includes Vice Chair roles in METU's Environmental Engineering Department (2012-2015 and 2006-2009), and she co-developed UN courses on Black Sea environmental management. Her research focuses on environmental systems engineering, integrated waste management, water quality modeling, and remote sensing applications. Notable projects include developing autonomous systems for lake turnover monitoring, optimizing landfill leachate management, and evaluating solar sludge drying alternatives. She has directed over 20 graduate theses and contributed to research funded by TÜBİTAK, Newton Fund, and EU programs. Key awards include the AQUA 360 Best Paper Award (2021) and TÜBİTAK Fellowships. Her work spans 120+ peer-reviewed publications, with recent focus areas including anaerobic digestion optimization, GIS-based waste routing, and pollutant fate modeling in heterogeneous aquifers. She advises on national environmental policies and manages projects like the 'Turnover Response System Development' (2020-2023) and 'Chlorophyll-a Modeling in Lake Eymir' (2009-2010).

Charles Raymond SarimuthuView profile

Senior Lecturer

• Power Systems
• Renewable Energy
• Smart Grids
• +3 more

Dr. Charles Raymond Sarimuthu is a Senior Lecturer in the Department of Electrical and Computer Systems Engineering at Monash University Malaysia. He holds a Ph.D. in Electrical Power Engineering from National Energy University, Malaysia. His research focuses on voltage control, power transformers, distribution systems, renewable energy, and smart grids. He actively supervises undergraduate and postgraduate students and has published extensively in high-impact journals such as Electric Power Systems Research and Renewable Energy . Dr. Sarimuthu has collaborated on projects including the Electric Field Imaging (EFI) Sensor for Comprehensive Static Charge Analysis (2024-2025) and the Fundamental study on memristor switching performances (2023-2026). He has also led the Investigation of on-load tap changer transformer operation (2019-2022), demonstrating expertise in grid stability and renewable integration. Teaching commitments include ECE3051 - Electrical Energy Systems , ECE4053 - Electrical Energy-Generation and Supply , and ECE5886/6886 - Smart Grids . He is a member of professional bodies such as the Board of Engineers Malaysia (BEM) and IEEE. His work aligns with UN Sustainable Development Goals related to affordable and clean energy (SDG7) and industry innovation (SDG9). Recent research highlights include game theory approaches for voltage control and adaptive synchronverter technologies for solar power systems.

Leila Moslemi NaeniView profile

Senior Lecturer

• Project Management
• Fuzzy Methods
• Mathematical Modelling
• +5 more

Dr. Leila Moslemi Naeni is a Senior Lecturer at the University of Technology Sydney (UTS), School of Built Environment, with a dual appointment in the Faculty of Design, Architecture and Building. She previously served as a Lecturer at UTS (2016-2018) and Sessional Lecturer at Curtin University (2015-2016). PhD in Computer Science (University of Newcastle, 2017) MSc in Industrial Engineering (Sharif University of Technology, 2007) BSc in Industrial Engineering (Iran University of Science and Technology, 2004) Her research focuses on project management under uncertainty, integrating fuzzy systems and mathematical modeling with applications in construction, ESG reporting, and disruptive technologies. She developed innovative methods for statistical control charts in project monitoring and leads research on leveraging blockchain and digital tools for sustainable infrastructure. Recent publications highlight her work on resource-constrained scheduling algorithms, ESG integration in megaprojects, and gamification in project management education. She serves as Review Editor for Frontiers in Environmental Science and on the Editorial Board of Smart and Sustainable Built Environment . 2016 PMI NSW Research Award 2022 Walt Lipke Award 2013 FEBE Postgraduate Research Prize As an active research mentor, she supervises PhD students in machine learning applications, disaster management technologies, and social infrastructure investments. Her teaching emphasizes simulation-based learning, collaborating with Oulo University (Finland) to quantify educational value.

Sarah Ben AmorView profile

Professor

• Multi-Criteria Decision Making (MCDM/MCDA)
• Operations Research
• Decision Support Systems
• +5 more

Sarah Ben Amor is a Full Professor at the Telfer School of Management , University of Ottawa, with a PhD in Business Administration specializing in Operations and Decision Support. Her academic journey includes a B.A. from the University of Quebec in Outaouais (UQO), and M.Sc. and Ph.D. from Université Laval (uLaval). Fields of Interest : Multi-Criteria Decision Making (MCDM/MCDA), Operations Research, Decision Support Systems, Uncertainty Modeling, Risk Analysis Her research focuses on handling information imperfections in decision-making processes, particularly through multi-criteria analysis and stochastic modeling . Recent works include the development of hierarchical stochastic VIKOR methods, assessment of learning methodologies, and applications in healthcare and pharmaceutical decision-making. Her publication trends reveal a strong emphasis on multi-criteria frameworks for uncertain environments, spanning sustainable manufacturing , clinical decision-making , and portfolio analysis . Collaborative works appear in journals like Applied Soft Computing and Osteoarthritis and Cartilage . She has secured significant funding including: NSERC Grant (2019-2024): $130,000 Telfer School Grants : $6,000 (2014-2018) and $4,000 (2021-2022) Her educational contributions include teaching quantitative methods and developing decision-making models for defense, healthcare, and sustainability sectors, with international collaborations spanning Canada, Brazil, and Europe.

Anna WilbikView profile

Professor

• Data Fusion
• Intelligent Interaction
• Fuzzy Logic
• +4 more

Anna Wilbik is a Professor in Data Fusion and Intelligent Interaction at the Department of Advanced Computing Sciences, Faculty of Science and Engineering, Maastricht University (The Netherlands). Her research bridges data understanding and human-machine synergy in complex systems, focusing on multi-criteria decision making, explainable AI, and data fusion techniques. PhD in Computer Science (with honors), Systems Research Institute, Polish Academy of Science (2010) Postdoctoral Fellow, University of Missouri (2011) Stanford University TOP500 Innovators Program Alumnus Research Pillars: Intelligent human-machine interaction for joint decision making Data fusion methods for heterogeneous data integration Contextualized multi-criteria decision frameworks Fuzzy logic and linguistic summaries for explainability Federated learning systems Article Trends: Recent work focuses on intuitionistic fuzzy sets for knowledge-intensive processes, federated learning with uncertainty handling, and linguistic summarization techniques for interpretable AI. She actively explores explainability , collaborative business models , and driver behavior analysis through attention-based models. Professional Leadership: Vice-chair of IEEE Fuzzy Systems Technical Committee Organizer of IEEE World Congress on Computational Intelligence (2024)

• Control Systems
• Renewable Energy Systems
• Hydrogen Energy Storage
• +3 more

Dr. Fan Zhang serves as Associate Professor in Engineering (Engineering and Design) at the School of Engineering and Informatics, University of Sussex, where he leads research in control systems and sustainable energy technologies. His work bridges theoretical control engineering with practical renewable energy applications, particularly in hydrogen storage and conversion systems. His academic foundation includes: PhD in Control Systems from the University of Sheffield MSc in Control Systems from the University of Sheffield PgCLT (Distinction) from the University of South Wales BEng in Automation from Tianjin University of Technology and Education Research centers on control systems for renewable energy integration, with emphasis on hydrogen storage, wind/solar-hydrogen systems, and automation. His work demonstrates strong interdisciplinary connections between power electronics, energy conversion, and sustainable transportation solutions, particularly through advanced control strategies for complex energy systems. Publication analysis reveals consistent focus on hydrogen energy systems (70% of recent work), with growing emphasis on aviation applications and tidal energy integration. His research trajectory shows evolution from foundational photovoltaic control (2013-2015) toward multi-source renewable systems (2021-2025), reflecting industry shifts toward hydrogen economy solutions. Academic recognition includes: Senior Fellow of the Higher Education Academy He supervises research projects including tidal lagoon power and hydrogen energy storage optimization, with teaching responsibilities spanning Robotics and Electrical Engineering programs delivered in China. His curriculum development for Automation & Mechatronics and Systems Analysis modules demonstrates practical application of his research expertise. Current research activities involve supervisory control systems for renewable hydrogen infrastructure, with emerging work in neurolinguistics-based control interfaces indicating expanding interdisciplinary reach.

Mustapha C.E. YagoubView profile

Professor

• RF/Microwave Circuit Design
• RFID Systems
• Antenna Design
• +5 more

Mustapha C.E. Yagoub is a Full Professor at the School of Electrical Engineering and Computer Science, University of Ottawa, with over 500 publications in RF/microwave CAD, RFID systems, neural networks, and applied electromagnetics. He leads research in the ELEMENT Laboratory and RFM Research Group , focusing on wireless communication systems and nonlinear device modeling. PhD in Electronics (Institut National Polytechnique de Toulouse, 1994) Magister in Telecommunications (École Nationale Polytechnique d'Alger, 1987) Dipl.-Ing. in Electronics (École Nationale Polytechnique d'Alger, 1979) His research bridges Microwave Circuit Design with Artificial Intelligence , including applications in Energy Conservation and Telecommunication Systems . Key trends in his publications include hybrid modeling techniques combining Neural Networks with Computational Electromagnetics for optimizing Antenna Design and RF Components . He is a Senior Member of IEEE and licensed with the Professional Engineers of Ontario and Ordre des Ingénieurs du Québec . His lab teams focus on High-Tc Superconducting Devices and Directional Antenna Optimization for RFID networks.

Miloš RackovićView profile

Professor

• Artificial Intelligence
• Machine Learning
• Databases
• +4 more

Miloš Racković serves as a full Professor in the Department of Mathematics and Informatics at the University of Novi Sad, Serbia. He maintains active academic engagement through the Laboratory for the development of information systems, with his office located in the Information technologies and systems office (DMI&DF) on the second floor, room 49. Contact is available via telephone (485)-2868 or email rackovic@dmi.uns.ac.rs, and his personal website (http://www.is.pmf.uns.ac.rs/rackovicm/) provides additional resources. His research spans foundational and applied computer science, with seminal contributions in fuzzy database systems including PFSQL query language development and prioritized fuzzy logic for relational databases and XML. He has pioneered deep learning methodologies through innovative classification techniques using negative and missing features in convolutional neural networks. Additional expertise includes high-performance computing implementations of Lattice Boltzmann methods using OpenCL, robotics (symbolic modeling and trajectory planning), and blockchain applications for Industry 4.0 production processes. His sports analytics work applies neural networks to basketball player and referee movement analysis. Analysis of his 2012-2025 publications reveals a strategic evolution toward interdisciplinary applications, particularly in industrial transformation (blockchain-enabled traceability) and sports analytics. His work consistently bridges theoretical computer science with practical implementations, demonstrating increasing focus on real-world problem solving while maintaining strong foundations in database theory and computational methods. Professor Racković leads the Laboratory for the development of information systems, which focuses on advancing information system methodologies through formal modeling extensions (including Petri net innovations) and practical implementations for uncertainty management. The laboratory's work spans from foundational research in fuzzy logic systems to applied projects in high-performance computing and blockchain integration, fostering innovation in information technology development.