جستجوی استاد راهنمای دانشگاهی

• Fuzzy Logic
• Multi-criteria Decision Making
• Decision Science
• +۳ مورد دیگر

Başar Öztayşi is a Professor at the Department of Industrial Engineering , Istanbul Technical University , with expertise in fuzzy logic, multi-criteria decision making, and decision science. He has held administrative roles including Associate Professor (2017–present), Deputy Director of the Institute (2016–2017), and Assistant Professor (2013–2017). Fields of Study : Fuzzy Logic, Multi-criteria Decision Making, Decision Science Contact : oztaysib@itu.edu.tr , +90 212 293 1300 Research Interests focus on applying fuzzy set theory to complex decision problems, including financial management, risk assessment, and smart city energy systems. His work extends to industry 4.0 applications and process mining in e-commerce. Recent Publications (2024) analyze fuzzy approaches in financial management, risk assessment, and Industry 4.0, with subfields spanning bibliometric trends, allocation optimization, and sustainable energy planning. Earlier works explore AHP matrix consistency, file distribution models, and customer segmentation. Awards : Best Paper Award, FLINS 2018 Science - Art Awards

• Fuzzy Systems
• Computational Intelligence
• Nonlinear Control
• +۴ مورد دیگر

Michio Sugeno is a distinguished Professor at Tokyo Institute of Technology's Graduate School of Information Science and Engineering, Department of Computational Intelligence. With a career spanning over four decades, he has established himself as a leading figure in fuzzy systems and computational intelligence. His research interests encompass Fuzzy Systems, Computational Intelligence, Nonlinear Control, Choquet Integral theory, Brain-Computer Interfaces, and Linguistic Computing. Sugeno's work has fundamentally shaped modern fuzzy control theory, particularly through his development of the Takagi-Sugeno fuzzy model which has become a standard approach in industrial applications. Analysis of his recent publications reveals a continued focus on piecewise nonlinear modeling, stability analysis of fuzzy systems, and the application of Choquet calculus to various computational problems. His work demonstrates a consistent trajectory from theoretical foundations to practical implementations in control systems and intelligent computing. IEEE Pioneer Award in Fuzzy Systems IFSA Fellow Emanuel R. Piore Award Sugeno has mentored numerous researchers who have become prominent in their own right, including Tadanari Taniguchi, Luka Eciolaza, and Anh-Tu Nguyen. His laboratory has been instrumental in developing novel approaches to nonlinear control systems using piecewise bilinear models and fuzzy logic. Current research directions include brain-computer interfaces using EEG analysis and the development of everyday language computing systems that enable more natural human-computer interaction.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۷ مورد دیگر

Tuğba Dalyan is an Associate Professor in the Department of Computer Engineering at Istanbul Bilgi University, Faculty of Engineering and Natural Sciences. She holds a Ph.D. in Computer Engineering from Yıldız Technical University (2014), an MSc from Kocaeli University (2007), and dual BSc degrees in Mathematics and Computer Science and Business Administration (Minor) from Istanbul Bilgi University (2003). She has been a faculty member since 2016 and previously served as a Teaching Staff member and Research Assistant at the same institution. Her research focuses on Natural Language Processing , Machine Learning , Deep Learning , Text Mining , Data Science , and Big Data Analytics . Her work spans computational linguistics, sentiment analysis, author profiling, machine translation, and smart systems. She has led and contributed to numerous research projects, particularly in AI-driven urban solutions and health technologies. The most recent publications show a strong trend in Turkish NLP, zero-shot classification, multimodal AI (image captioning), emotional robotics, and decision support systems using fuzzy logic. Her work combines theoretical rigor with practical applications in smart cities, education, and healthcare. Best Paper Award , CICLing 2012 TÜBİTAK 2209-A student project awards (2022–2024) Horizon2020 Eşik Üstü Ödülü , MIMOSCSA 2024 TÜBİTAK 2242 competition: 2nd and 3rd place (2016, 2018) She has advised numerous student research projects, many of which have received national recognition. She has directed multiple TÜBİTAK and institutional research grants, including projects on smart homes, blockchain crowdfunding, mental health, and AI for social polarization. Her leadership roles include Head of Department, Vice Dean, and Director of Graduate Programs. Tuğba Dalyan leads research in AI and NLP with a strong emphasis on Turkish language technologies. She is involved in interdisciplinary teams working on emotional robots, smart city platforms, and citizen science ecosystems. Her lab activities focus on neural networks, text analysis, and intelligent systems development.

Hak-Keung Lamمشاهده پروفایل

استاد

• Fuzzy Control Systems
• Neural Networks
• Control Theory
• +۴ مورد دیگر

Dr. Hak-Keung Lam is a Reader in the Department of Engineering at King's College London, part of the Faculty of Natural, Mathematical & Engineering Sciences. He holds an IEEE Fellowship and has been a Clarivate Web of Science Highly Cited Researcher since 2018. His research focuses on fuzzy control systems, neural networks, stability analysis, and their applications in biomedical and engineering domains. Education: Dr. Eng. (2000), B. Eng. (1995), both from Hong Kong Polytechnic University. Research Interests: Fuzzy modeling, neural network-based control, computational intelligence, machine learning, and biomedical applications such as ECG/EEG signal classification. His work bridges theoretical advancements with practical implementations in robotics, autonomous systems, and healthcare technology. Publications: Over 480 publications (as of 2023) in top-tier journals and conferences, with a focus on control systems, fuzzy logic, and intelligent systems. Recent work includes fault-tolerant control, cyber-physical systems, and explainable AI. Awards: IEEE Fellow (2019), 1st Place in PhysioNet Computing in Cardiology Challenge (2022). Grants/Projects: Active projects include fuzzy control system stabilization, autonomous robots in healthcare environments, and networked control of robotic systems. Labs/Teams: Center for Robotics Research, contributing to solutions for societal challenges through robot-centric approaches.

• Signal Processing
• Communication
• Wireless Communications
• +۴ مورد دیگر

Professor Hakan Ali Çırpan is a distinguished faculty member at Istanbul Technical University's Faculty of Electrical and Electronics Engineering, where he serves as Professor in the Department of Electronics and Communication Engineering. He also holds the position of Vice Dean at Istanbul Technical University since 2021. With over three decades of academic experience, Professor Çırpan has established himself as a leading researcher in signal processing and communications. His educational background includes: PhD from Stevens Institute of Technology (1993-1997) Master's degree in Electrical-Electronic Engineering (with thesis) from Istanbul University (1989-1992) Bachelor's degree in Electrical and Electronic Engineering from Uludağ University (1985-1989) Professor Çırpan's research spans multiple domains within signal processing and communications. His primary interests include wireless communications, radar systems, machine learning applications in communications, and electronic warfare. His work on channel estimation, orthogonal frequency division multiplexing, and maximum likelihood methods has been particularly influential. He has pioneered research in areas such as source localization, spectrum sensing, and physical layer security. His recent work focuses on 5G/6G networks, AI-enhanced communications, and integrated sensing and communication systems. Analysis of his recent publications (2023-2025) reveals a strong focus on next-generation wireless technologies, particularly 5G/6G networks, AI integration in communications, and electronic warfare applications. His research demonstrates a consistent pattern of addressing fundamental challenges in signal processing while adapting to emerging technological needs. A significant portion of his recent work involves machine learning applications for spectrum management, optimization techniques for radar systems, and novel approaches to network slicing and resource allocation. His notable scientific achievements include: ASELSAN ACADEMY THESIS COMPETITION WINNER (2020) Professor Çırpan has supervised 59 theses throughout his career, mentoring numerous graduate students in the fields of signal processing and communications. He has secured significant research funding, including the "AI-Enhanced 5G/6G Networks with Integrated Camera and ISAC Systems" project (2023-2024) and the "Railway Vehicle Infrastructure New Generation Secure Communication Systems" TÜBİTAK project with a budget of ₺955,000. His research has practical applications in defense systems, railway communications, and next-generation wireless networks. His laboratory work focuses on wireless communications systems, radar signal processing, and AI-enhanced communication technologies. Professor Çırpan leads research teams working on projects related to 5G/6G networks, electronic warfare countermeasures, and secure communication systems. His group collaborates with industry partners like ASELSAN and conducts research with practical applications in national defense and critical infrastructure.

Saiedeh Razaviمشاهده پروفایل

دانشیار

• Smart Infrastructure
• Intelligent Transportation Systems
• Construction Management Automation
• +۵ مورد دیگر

Dr. Saiedeh Razavi is an Associate Professor and the inaugural Chair in Heavy Construction at McMaster University's Department of Civil Engineering, directing the McMaster Institute for Transportation and Logistics (MITL). She holds a multidisciplinary background with degrees in Computer Engineering (B.Sc., Sharif University), Artificial Intelligence (M.Sc., Iran), and Civil Engineering (Ph.D., Waterloo). Her research focuses on smart infrastructure, connected mobility, and construction safety, funded by NSERC and the Ontario Ministry of Transportation. Key areas include transforming construction management through AI, autonomous vehicles, and smart work zones. Education: B.Sc. (Sharif), M.Sc. (Iran), Ph.D. (Waterloo) Research Interests: Smart cities, connected vehicle systems, data fusion, risk analysis, and sustainable logistics Leadership Roles: Director of MITL, Associate Chair (Research), and lead of national/international multidisciplinary projects Her work bridges academia, government, and industry to enhance mobility and safety. Notable grants include NSERC funding for transformative transportation systems. Awards include teaching excellence and innovation in team-based projects. Grants & Projects: NSERC, Ontario Ministry of Transportation, and industry collaborations Labs/Teams: MITL, CPS-based construction safety initiatives, and autonomous vehicle research groups

Chung-Hsing Yehمشاهده پروفایل

دانشیار

• Multicriteria Decision Analysis
• Applied Artificial Intelligence
• Intelligent Decision Support Systems
• +۶ مورد دیگر

Chung-Hsing Yeh is an Associate Professor at Monash University's Faculty of Information Technology, Department of Data Science & AI. He holds a visiting professorship at National Cheng Kung University, Taiwan, and has extensive experience in academic roles including Chief Examiner and Lecturer for numerous IT and business-related courses. His research focuses on multicriteria decision analysis, applied artificial intelligence, fuzzy logic, neural networks, and sustainable operations management. He has led collaborative projects on e-waste recycling, supply chain optimization, and public health policy, funded by organizations like the Ministry of Science and Technology (Taiwan) and the Australian Research Council. Education: PhD in Operations Research/Information Systems, Monash University (1988) MSc in Management Science, National Cheng Kung University (1982) BSc (Engineering) in Industrial Design, National Cheng Kung University (1977) Research Interests: His work spans decision support systems, optimization modeling, transport research, and recycling operations. Notable contributions include algorithms for production scheduling, AI-driven solutions for healthcare, and sustainable e-waste management strategies. Awards: Listed in Marquis Who's Who in the World Listed in Who's Who in Finance and Industry Listed in Who's Who in Science and Engineering Grants & Projects: Led 6 major projects, including 'Maximizing E-waste Recycling Profitability' (2019–2020) and 'Smoke-Free Policy Effectiveness' (2007–2010). Active in grant review roles for ARC and the Netherlands Organisation for Scientific Research. Teaching: Overseeing courses such as Fundamentals of Artificial Intelligence, Business Intelligence Modelling, and Management Information Systems.

• Power Electronics
• Electrical Engineering
• Energy Conversion
• +۷ مورد دیگر

Kamal Al Haddad is a Lecturer in the Department of Electrical Engineering at École de technologie supérieure (ÉTS). He holds a Doctorate from INTP, Toulouse, and advanced degrees from UQTR. His research focuses on power electronics, renewable energy integration, and smart grid technologies. He leads the GREPCI research group, specializing in Power Electronics and Industrial Control. Education: B.Eng., M.Sc.A. (UQTR), Doctorate (INTP, Toulouse). Research interests span energy conversion, industrial electronics, power quality, and electromagnetic interference. He emphasizes sustainable energy solutions, electric traction systems, and high-efficiency power sources. His work includes developing advanced power electronic converters and grid stability solutions. Recent articles highlight advancements in modular converters for STATCOM, AI-driven fault detection in hydrogenerators, and renewable energy policy frameworks. He has received notable awards, including the 2014 IEEE Eugene Mittelmann Prize and Fellowships from IEEE and other institutions. Supervised over 60 students, including doctoral theses on topics like hydrogenerator diagnostics, EV charging systems, and renewable energy integration. His research also involves real-time simulation of power systems and FPGA-based implementations. Labs/Teams: GREPCI – Power Electronics and Industrial Control Research Group, leading projects on smart grids and energy efficiency.

Wooram Parkمشاهده پروفایل

دانشیار

• Robotics
• Biomedical Robotics
• Computational Structural Biology
• +۳ مورد دیگر

Wooram Park is an Associate Professor in the Department of Mechanical Engineering at the University of Texas at Dallas (UT Dallas), affiliated with the Erik Jonsson School of Engineering and Computer Science. He leads the Robotics and Intelligent Systems Laboratory (ROBINS Lab) and holds a PhD from Johns Hopkins University (2008), along with MS and BS degrees from Seoul National University (2003 and 1999). His research focuses on robotics, biomedical robotics, computational structural biology, and image processing. Key projects include flexible needle steering for medical applications, haptic feedback systems, and advanced algorithms for motion planning and image reconstruction. He has received notable awards such as the Creel Fellowship (2007) and Critics’ Choice Award in ArtBot Design (2004). His work spans theoretical contributions in stochastic systems and practical innovations like vibratory magnetic robots (Vimbot) and wearable haptic devices. The ROBINS Lab emphasizes interdisciplinary research at the intersection of mechanical engineering, computer science, and biomedical applications.

Tingkai Wangمشاهده پروفایل

مدرس ارشد

• Mobile Robots
• Intelligent Systems
• Artificial Intelligence (AI)
• +۵ مورد دیگر

Dr. Tingkai Wang is a Senior Lecturer in the School of Computing and Digital Media at London Metropolitan University. His research focuses on mobile robots, intelligent systems, artificial intelligence, control systems, image/signal processing, and virtual reality. He teaches the Programming for Computer Science module and has led projects like the Virtual Environment and Simulation System (2000-2002) and Navigation and Control of Mobile Robots (1995-1998). His work emphasizes interdisciplinary approaches, combining expert systems, neural networks, and fuzzy logic to address challenges in autonomous systems. Notable contributions include AGV navigation algorithms, hybrid control systems, and predictive modeling. Over 30 publications span robotics, control engineering, and AI applications. He collaborates internationally and has presented at venues like the International Conference on Intelligent Systems Engineering and the IEEE Conference on Engineering in Medicine and Biology. Dr. Wang’s expertise bridges theoretical modeling and practical implementation, with applications in manufacturing automation, environmental monitoring, and industrial management systems. His current research continues exploring adaptive control mechanisms and AI-driven robotics solutions.

İlhan Kocaarslanمشاهده پروفایل

استاد

• Control Systems Engineering
• Load Frequency Control
• Adaptive Control
• +۱۲ مورد دیگر

İlhan Kocaarslan is a Professor in the Department of Control and Automation Engineering at Istanbul Technical University (ITU), Faculty of Electrical and Electronic Engineering. His research focuses on advanced control systems, energy conversion, and sustainable transportation technologies. Research Interests: His work spans Load Frequency Control , Adaptive and Fuzzy Logic Control , PI Controllers , Electric Vehicle energy modeling , Battery and Fuel Cell systems , and Smart Grid integration . He actively contributes to innovations in renewable energy and electromobility. Publication Trends: Recent publications emphasize high-fidelity energy modeling for electric vehicles, optimization of battery systems, control strategies for fuel cells using fuzzy and Lyapunov-based PI controllers, and electromagnetic design for next-generation transportation like Hyperloop. His work bridges theoretical control design with practical energy applications. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: He supervises 25 ongoing theses, indicating active mentorship. He is Principal Investigator (PI) on multiple research projects funded by ITU’s BAP and TTO programs, including initiatives on blockchain-based energy systems, hydrogen technologies, electric mobility, and cybersecurity-integrated sustainability platforms. Labs and Teams: While specific lab names are not mentioned, his role as PI on diverse energy and control projects suggests leadership in a multidisciplinary research group focused on smart energy systems, power electronics, and sustainable transportation at ITU.

Navid Bayatiمشاهده پروفایل

دانشیار

• Renewable/Hybrid Power Systems
• Protection and Transient Analysis of Power Grids
• Microgrids and Active Energy Networks
• +۵ مورد دیگر

Navid Bayati is an Associate Professor at the University of Southern Denmark, affiliated with the Institute of Mechanical and Electrical Engineering and the Centre for Industrial Electronics. He leads the Control and Protection of Smart Grids (CAP-SG) group and focuses on renewable/hybrid power systems, microgrid protection, and grid code compliance. Education: Ph.D. in Power Systems & Microgrid Protection (2020, Aalborg University); M.Sc. in Power Systems (2017, Amirkabir University of Technology) His research spans renewable energy integration , transient analysis , grid interconnection , and digital twin applications . Recent work includes machine learning for carbon emission prediction, fault localization in DC microgrids, and supercapacitor resilience in hybrid systems. Collaborations include projects like IEA Wind Task 50 and RePoSys , addressing grid renovation, life cycle assessment, and digital twin resilience. His teaching portfolio covers power electronics , energy management , and microgrid control .

Miguel Rico-Ramirezمشاهده پروفایل

دانشیار

• Radar Hydrology
• Hydroinformatics
• Flood Forecasting
• +۳ مورد دیگر

Dr. Miguel Rico-Ramirez serves as Associate Professor of Radar Hydrology and Hydroinformatics at the University of Bristol's School of Civil, Aerospace and Design Engineering. His research integrates advanced radar technology with hydrological modeling to address critical water resource challenges including flood forecasting, drought management, and precipitation measurement across diverse global contexts from South Korea to Mexico City. Education: Bachelor of Engineering (Eng.) Master of Engineering (M.Eng.) Ph.D. in Engineering, University of Bristol His research program focuses on radar-based precipitation estimation, hydroinformatics, and flood prediction systems. He pioneers deep learning applications for rainfall nowcasting and develops innovative methods for uncertainty quantification in hydrological modeling. Current work emphasizes cosmic-ray neutron sensor validation, satellite-based flood mapping, and seasonal forecast applications for reservoir operations, with strong emphasis on translating research into operational water management solutions. Recent publications (2023-2025) reveal three dominant research thrusts: (1) deep learning frameworks for spatiotemporal rainfall prediction, (2) global validation of precipitation and soil moisture datasets using novel sensor networks, and (3) operational implementation of seasonal forecasts for drought mitigation in South Korea. His work consistently bridges radar meteorology with practical hydrological applications across urban and data-scarce environments. Scientific Awards: No specific awards documented in source materials Dr. Rico-Ramirez supervises postgraduate researchers in radar hydrology and hydroinformatics, with projects spanning flood early warning systems, precipitation nowcasting, and climate adaptation strategies. His research receives funding for international collaborations focused on water security challenges, particularly in drought-prone regions and data-scarce basins like the Nile Delta. Current grants support development of integrated forecasting systems combining global datasets with machine learning for extreme event management. He leads the Radar Hydrology research group within Bristol's Water and Environmental Engineering division, collaborating closely with Professor Dawei Han on hydroinformatics and Dr. Rafael Rosolem on water-climate interactions. The team maintains active partnerships with meteorological agencies and water authorities globally, particularly in flood forecasting system implementation across South Korea and Mexico.

Pooya Davariمشاهده پروفایل

استاد

• Harmonic and EMI analysis and mitigation in grid-tied converters
• Electromagnetic interference and compatibility
• High power density power electronic systems
• +۲ مورد دیگر

Pooya Davari is a Professor and Head of the Section for Applied Power Electronic Systems at Aalborg University , Denmark. He leads the EMI/EMC in Power Electronics Research Group and serves as Vice Chair of the Energy Efficiency Mission. His research focuses on electromagnetic interference (EMI) and harmonic mitigation in power electronic systems, with over 200 publications and significant contributions to renewable energy integration. Education: B.Sc. and M.Sc. in Electronic Engineering (2004, 2008), Ph.D. in Power Electronics from Queensland University of Technology (2013) Prior Roles: Lecturer at QUT (2013–2014), Postdoc at AAU (2014) Research Interests: Harmonic and EMI analysis in grid-tied converters High power density converter design Signal processing for converter modeling Reliability of power electronic systems Article Trends: Recent work emphasizes EMI/EMC in renewable energy systems, wide bandgap semiconductors (SiC/GaN), and reliability modeling for EVs and hydrogen production via electrolysis. Sub-fields include converter topologies, grid integration challenges, and AI-driven diagnostics. Scientific Awards: Equinor 2022 Prize (Denmark’s oldest engineering award) IEEE EMC Society Young Professional Award (2020) World’s Top 2% Highly Cited Scientist (Stanford, 2021–2025) Multiple best paper awards (IEEE, Applied Sciences, etc.) Grants & Editorial Roles: Recipient of grants from Innovation Fund Denmark (Supra-EMC project), Horizon Europe (SOLARIS), and industry partnerships. Serves as Area Editor for IEEE Transactions on Transportation Electrification , Associate Editor for IEEE Transactions on Power Electronics , and Editor-in-Chief of Circuit World Journal (2020–2025). Labs & Standards: Coordinator of the EMC Laboratory at Aalborg University. Member of IEC standardization Working Groups 6 and 8 (TC77A), focusing on EMC strategies for power grids.

LJILJANA TRAJKOVICمشاهده پروفایل

استاد

• Communication Networks
• Nonlinear Circuits and Systems
• Electronics Engineering
• +۳ مورد دیگر

Ljiljana Trajkovic is a Professor in the Department of Engineering Science at Simon Fraser University's Faculty of Applied Sciences. She holds a Ph.D. from the University of California, Los Angeles (1986), M.Sc. from Syracuse University (1979), and Dipl.Ing. from the University of Pristina (1974). Her research focuses on communication networks, nonlinear circuits, and machine learning applications for network security. She actively contributes to IEEE initiatives, including roles as conference committee chair and editorial board member. Education highlights include a strong foundation in electrical engineering and advanced studies in circuit theory and systems science. Her work bridges theoretical analysis with practical applications, such as anomaly detection in communication networks using machine learning. She teaches courses like ENSC 220 D100 Electric Circuits I, integrating research insights into education. Research interests emphasize network security, traffic analysis, and distributed systems. Recent articles explore BGP anomaly classification, ransomware detection, and virtual network embedding. She collaborates on tools like VNE-Sim and Anonym for network analysis. Awards and recognitions are highlighted through her leadership roles in IEEE and academic contributions. Advising and grants involve mentoring graduate students in cybersecurity and networking projects. She leads research teams exploring complex networks and their applications in autonomous systems. Her lab focuses on interdisciplinary projects merging electronics engineering with AI-driven network solutions.