جست‌وجوی استاد و پژوهشگر

Idriss Dagalمشاهده پروفایل

استادیار

• Renewable Energy Systems
• Photovoltaic Systems
• Power Electronics
• +۶ مورد دیگر

Idriss Dagal serves as an Assistant Professor at Beykent University's Department of Electrical and Electronics Engineering. With a PhD and Master's in Electrical Engineering from Yildiz Technical University (2015 and 2023 respectively), and additional academic credentials from Ethiopian Airlines Aviation University and Mongo Polytechnics University, his career bridges academic research with industry experience as a Sales Engineer. PhD: Yildiz Technical University (2015) Master's: Yildiz Technical University (2023), Ethiopian Airlines Aviation University (2008) Bachelor's: Mongo Polytechnics University (2006) His research focuses on renewable energy systems , particularly photovoltaic power optimization using metaheuristic algorithms (Hybrid PSO-Salp Swarm, Gray Wolf Optimization). He also explores control systems for solar energy and aircraft dynamics, including PID and fuzzy logic controllers. Additional work spans machine learning applications in energy and medical diagnostics, along with power electronics for battery charging. Recent publications highlight 15 2025 articles on topics like hybrid energy systems , AI-driven MPPT , and aircraft control frameworks . His work appears in journals such as Scientific Reports , IEEE Access , and International Journal of Aeronautical and Space Sciences . Teaching experience includes courses in Electrical Machines and Information Technologies . Non-university roles at Elektra Electronic Company and Aktif Group Company involved sales engineering, complementing his academic profile with industry insights.

• Electrical Energy and Power Systems
• Artificial Intelligence
• Electrical Facilities

Dr. Cenk Andiç is a Research Assistant at Istanbul Technical University's Department of Electrical Engineering. His work bridges Electrical Energy and Power Systems with Artificial Intelligence , focusing on optimization techniques for energy management and control systems. PhD in Electrical and Electronics Engineering (Düzce University) Integrated PhD program completion in 2024 Key research areas include: Automatic Voltage Regulation Load Frequency Control Dynamic Economic Load Dispatch Energy Optimization in Transportation Renewable Energy Integration Metaheuristic Optimization Algorithms Recent publications demonstrate a trend toward bio-inspired algorithms like Mountain Gazelle Optimizer , Puma Optimizer , and Sea Horse Optimizer for power system stability and renewable integration challenges. His work spans theoretical control systems to practical implementations in photovoltaic-thermal hybrid systems and data centres. Scientific recognition includes: 2023 Publication Award (Istanbul Technical University) 2024 Best Paper Award 2023 Cenk Andic Prize YÖK 100/2000 Scholarship He actively participates in international collaborations and serves as Principal Investigator for the 2025 project Improving Load Frequency Control in Interconnected Power Systems with Sled Dog Optimization Algorithm . Contact: andic18@itu.edu.tr

• Economics
• Finance
• Banking
• +۵ مورد دیگر

Professor Jerzy Węcławski of Maria Curie-Skłodowska University's Faculty of Economics specializes in banking, family business finance, and financial market dynamics. His work bridges theoretical research with practical applications in economic transformation and corporate governance. Department of Banking and Financial Markets Faculty of Economics, UMCS Research focuses on family business financial strategies , venture capital mechanisms , and banking sector reforms . Current projects examine private equity's role in economic development and relationship banking's evolution in Eastern Europe. Article analysis reveals trends in financial innovation , institutional adaptation , and family business sustainability , with 60% of publications addressing capital structure issues and 40% analyzing banking system transformations. Scientific contributions include Honorary member of Polish Finance and Banking Association Member of Polish Academy of Sciences, Committee on Financial Sciences Editorial roles in leading Polish economic journals Active in EU financial integration studies and regional development projects, with advisory work for the Lublin Regional Operational Programme and Polish Accreditation Commission expertise spanning two decades.

• Information Retrieval
• Data Science
• Text Analytics
• +۵ مورد دیگر

Christina Lioma is a Full Professor at the Department of Computer Science (DIKU), University of Copenhagen . She has held academic positions including Associate Professor (2014-2018) and Freja Fellow/Assistant Professor (2012-2013) at the same institution. M.Hons (University of Glasgow, 2001) M.Sc. (University of Manchester, 2003) Ph.D (University of Glasgow, 2007) Her research focuses on Information Retrieval , Text Analytics , and Recommender Systems within Applied Machine Learning and Natural Language Processing . Recent work examines fairness-relevance tradeoffs in recommendation systems and neural mechanisms for knowledge conflict tracing. Recent publications in Nature Communications and top conference proceedings (WWW, SIGIR) explore hybrid computation architectures, brain-based language generation, and fairness evaluation metrics. She actively participates in academic conferences as organizer and speaker, including the European Conference on Information Retrieval.

Kalyanmoy Debمشاهده پروفایل

استاد

• Multi-Objective Optimization
• Evolutionary Algorithms
• Genetic Algorithms
• +۵ مورد دیگر

Kalyanmoy Deb is a Professor at the Department of Electrical and Computer Engineering, Michigan State University. Previously affiliated with Indian Institute of Technology Kanpur and Indian Institute of Technology Madras, he is a leading researcher in evolutionary algorithms and multi-objective optimization. Research Focus : Multi-Objective Optimization, Genetic Algorithms, Constraint Handling, Machine Learning-assisted Optimization Key Contributions : Development of NSGA (Non-dominated Sorting Genetic Algorithm) series, hybridization of machine learning with evolutionary algorithms, fidelity evaluation techniques Scientific Accomplishments : With over 347 publications and 19,618 citations, his work on NSGA algorithms has become foundational in evolutionary computation. His recent research explores mixed-fidelity evaluations, innovized knowledge extraction, and neural architecture search.

• Accelerator Physics
• Machine Learning
• Reinforcement Learning
• +۴ مورد دیگر

Dr Andrea Santamaria Garcia is a Lecturer in Artificial Intelligence for Particle Accelerators at the University of Liverpool and a member of the Cockcroft Institute. Her work bridges accelerator physics with machine learning, focusing on reinforcement learning and Bayesian optimization for real-time particle accelerator control. Current Research: Reinforcement learning in autonomous accelerators, Bayesian optimization, differentiable simulations Key Projects: RL4AA collaboration, Cheetah simulation code, microbunching instability control Education: PhD in Accelerator Physics (CERN), postdoctoral work on electron light sources Her research explores the synergy between accelerator physics and machine learning, particularly through reinforcement learning and Bayesian optimization . Recent work focuses on zero-shot reinforcement learning, meta-algorithms, and deploying machine learning on hardware for low-latency beam control. She leads collaborations with KIT, DESY, and CERN, including the development of the first differentiable beam physics simulation code. Scientific highlights include the 2024 Physical Review Accelerators and Beams Editors' Choice for her work on online reinforcement learning in accelerators. Her publications demonstrate cross-disciplinary impact in Scientific Reports and Physical Review Accelerators and Beams . PhD Supervision: Chenran Xu (KIT/DESY), Luca Scomparin (real-time RL platform) Teaching Philosophy: Emphasizes precision, ethics, and interdisciplinary collaboration She collaborates with international institutions and co-founded the Reinforcement Learning for Autonomous Accelerators (RL4AA) initiative, which organizes annual workshops on cutting-edge control techniques.

Shahram Payandehمشاهده پروفایل

استاد

• Robotics
• Geometrical Robotics
• Networked Dynamical Systems
• +۴ مورد دیگر

Shahram Payandeh is a Professor of Engineering Science at Simon Fraser University (SFU), affiliated with the School of Engineering Science within the Faculty of Applied Sciences. He holds a Ph.D. from the University of Toronto (1990), M.A.Sc. (1986), and B.Sc. (1981). His research focuses on robotics, geometrical robotics, networked dynamical systems, and medical robotics, with emphasis on haptic devices, multi-view tracking, and multi-modal interaction in serious games. Education: Ph.D., University of Toronto, Canada, 1990 M.A.Sc., University of Toronto, Canada, 1986 B.Sc., University of Akron, United States, 1981 Research Interests: Robotics and medical robotics applications Geometrical robotics and sensor networks Multi-view tracking and haptic rendering Networked dynamical systems and decision support His work spans visual tracking algorithms, sensor calibration, and teleoperation systems, with practical applications in healthcare and elderly care technology. Teaching: ENSC 482: Introduction to Decision Making in Engineering ENSC 890: Advanced Robotics: Mechanics and Control Labs & Facilities: Associated with the Engineering Science Research Lab (erl.ensc.sfu.ca) Office: ASB 10829

Mircea Nicolescuمشاهده پروفایل

استاد

• Computer Vision
• Surveillance Systems
• Robotic Vision
• +۳ مورد دیگر

Mircea Nicolescu is a Professor in the Department of Computer Science and Engineering at the University of Nevada, Reno. He holds a Ph.D. (2003) and M.S. (1999) from the University of Southern California, and a B.S. (1995) from Polytechnic University Bucharest. He co-directs the Computer Vision Laboratory . His research focuses on computer vision , particularly in video content understanding , surveillance systems , robotic vision , and human-computer interaction . Key areas include robust tracking in dynamic scenes, autonomous navigation, and gesture/face recognition. Recent work addresses maritime safety, cryptocurrency forecasting, and robotic task parameter estimation via multimodal data fusion. He has published over 100 peer-reviewed articles and holds a U.S. patent for 'Fast Digital Pan-Tilt-Zoom Video'. His work has earned a Best Paper Award Finalist distinction (2021). Teaching responsibilities include Programming Languages and Advanced Computer Vision courses. Collaborative projects involve multi-agent systems, intent recognition, and spiking neural networks for pattern analysis.

Federica Sarroمشاهده پروفایل

استاد

• Predictive Analytics for Software Engineering
• Search-Based Software Engineering
• Empirical Software Engineering
• +۴ مورد دیگر

Federica Sarro is a Professor of Software Engineering at the Department of Computer Science, University College London (UCL). She leads the SOLAR group, focusing on Predictive Analytics, Search-Based Software Engineering, and Empirical Software Engineering. Her research emphasizes software testing, effort estimation, and app store analysis, with over 70 peer-reviewed publications and collaborations with 20+ institutions worldwide. Her research has been supported by grants including the €2.1M ERC EPIC grant and a £6.8M EPSRC Programme Grant (DAASE). She has supervised numerous PhD students and postdoctoral researchers, including graduated scholars like Afnan Al-Subaihin and William Martin. She is actively involved in program committees and editorial roles, including Associate Editor for ACM TOSEM and IEEE Transactions on Evolutionary Computation. Key achievements include the ACM Distinguished Paper Award (2019), the GECCO-HUMIES Medal (2016), and leadership roles in conferences like ICSE, FSE, and SSBSE. Her work bridges software engineering with machine learning and data analytics, addressing challenges in testing, defect prediction, and agile practices.

• Environmental Engineering
• Sustainable Product Design
• Decision Analysis
• +۵ مورد دیگر

Deborah L. Thurston is a Professor in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign, affiliated with the College of Engineering. She holds a Ph.D. (1987) and S.M. (1984) in Civil Engineering from the Massachusetts Institute of Technology, and a B.S. (1978) in Civil Engineering from the University of Minnesota. Her research focuses on sustainable design, lifecycle product strategies, decision analysis for engineering systems, and environmentally conscious manufacturing processes. She has served as Area Editor for The Engineering Economist (1993–2001) and Associate Technical Editor for ASME's Journal of Mechanical Design (1993–1998). Her research emphasizes integrating environmental considerations into product design and supply chain decisions, with contributions to remanufacturing systems, disassembly planning under uncertainty, and lifecycle profit optimization. Recent work leverages immersive computing technologies to enhance decision-making in complex engineering systems. Key publications include studies on sustainable lifecycle design (2010), disassembly sequence evaluation using VR (2015), and optimization frameworks for engineering systems (2017). Dr. Thurston has received numerous awards, including the 2014 Kos Ishii-Toshiba Award, ASME Fellow distinction (2010), and the 2011 American Academy of Environmental Engineering Honors Award. She has advised over 30 students in environmental engineering and mechanical design, with notable contributions to senior design projects such as the 'Zero Wastewater Discharge Operation' (2001) and 'Analysis and Design of Baby Changing Table' (2003). Her work bridges academic research and industry applications, addressing global challenges in sustainable manufacturing and policy integration.

Giulia Michielettoمشاهده پروفایل

استادیار

• Multi-agent Systems
• Aerial Robotics
• Control Theory
• +۴ مورد دیگر

Giulia Michieletto serves as an Assistant Professor (RTD-A) at the Department of Management and Engineering, University of Padova, where she leads research in networked control systems and multi-agent robotics. She is a core member of the SPARCS research team and holds the position of publicity and dissemination lead for the IEEE Robotics and Automation Society's Technical Committee on Multi-Robot Systems. Her academic foundation includes a Laurea Degree in Automation Engineering (2014) and a Ph.D. in Information Engineering (2018), both from the University of Padova, supplemented by a Visiting Researcher appointment at LAAS-CNRS (2016-2017) funded by the Eiffel Scholarship Program. Michieletto's research centers on multi-agent system modeling with specialized focus on aerial vehicle formations and nanosatellite coordination . She pioneers thrust-vectoring aerial platform design for enhanced environmental interaction, while advancing theoretical frameworks in bearing rigidity theory. Her work spans wireless sensor networks for environmental monitoring, multi-camera systems for cooperative tracking, and ground robotics for autonomous manipulation, addressing critical challenges in robustness, security, and distributed control. Analysis of her publication trajectory reveals deep integration of bearing rigidity theory with practical aerial robotics applications, evolving toward cybersecurity-enhanced navigation and distributed estimation for sensor networks. Recent work demonstrates increasing sophistication in handling GNSS spoofing attacks, multi-robot formation control under disturbances, and real-time surveillance systems. Her scientific recognition includes: Eiffel Scholarship Program of Excellence (2016) Finalist for IEEE RAS Italian Chapter Fabrizio Flacco Young Author Best Paper Award (2019) As an active educator, Michieletto supervises master's theses on contact-aware aerial robotics and mobile manipulation while securing research leadership as Principal Investigator for the Contact-Aware Robotics (CAR) project and co-PI for formation control research. Her grant portfolio spans national initiatives including TSTARK and INTERACT, plus EU H2020's AEROARMS, frequently as fellowship recipient. She drives innovation within the SPARCS research ecosystem, focusing on networked control solutions for complex robotic systems operating in constrained environments.

Lutz Ecksteinمشاهده پروفایل

استاد

• Automotive Engineering
• Automated Driving Systems
• Vehicle Dynamics
• +۴ مورد دیگر

Univ.-Prof. Dr.-Ing. Lutz Eckstein is the Head of the Institute of Automotive Engineering (ika) at RWTH Aachen University and a leading expert in automotive engineering. He concurrently serves as President of the VDI Association of German Engineers, President of the VDI Scientific Advisory Board for the Federal Ministry of Digital and Transport (BMDV), and Scientific Director of the NRW Competence Network for Automated and Connected Mobility. His professional background includes senior roles at BMW and DaimlerChrysler, focusing on vehicle safety, driver assistance systems, and ergonomics. Eckstein holds a Doctorate from the University of Stuttgart (2000) and received the Artur Fischer Prize (1995) for academic excellence. His research interests span automated driving systems, human-machine interfaces, scenario-based testing, and mobility infrastructure. He leads high-profile projects like UNICARagil and coordinates the Mobility and Transport profile at RWTH Aachen. Over 80 patents and publications reflect his contributions to automotive innovation, including advancements in sensor fusion, digital twins, and cooperative intelligent transport systems (C-ITS). His recent work emphasizes safety assurance for automated vehicles, scenario databases, and scalable simulation frameworks. Eckstein's interdisciplinary approach bridges academia and industry, driving transformative solutions for future mobility challenges.

Yair Zickمشاهده پروفایل

استادیار

• Theoretical Computer Science
• Artificial Intelligence
• Algorithmic Game Theory
• +۳ مورد دیگر

Yair Zick is an Assistant Professor at the Manning College of Information Systems and Computer Sciences (CICS), University of Massachusetts Amherst. Previously, he held positions at the National University of Singapore (NUS School of Computing) and Carnegie Mellon University as a postdoc. His research focuses on algorithmic fairness, game theory, fair division, and explainable AI. He earned his PhD in Mathematics from Nanyang Technological University (2014) and a BSc (Amirim Honors Program) from the Hebrew University of Jerusalem. Educations: PhD in Mathematics, Nanyang Technological University, Singapore (2014) BSc in Mathematics (Amirim Honors Program), Hebrew University of Jerusalem, Israel (2009) His research interests include computational aspects of game theory, fair division, algorithmic transparency, and applying machine learning to economic problems. He teaches courses such as Algorithms, Game Theory, and Fairness, Artificial Intelligence, and Algorithmic Fairness. Key Awards: 2021 IJCAI Early Career Spotlight Award 2020 AAAI Outstanding Senior Program Committee Member Award 2017 Singapore NRF Fellowship 2016 ACM EC Best Paper Award 2014 Victor Lesser IFAAMAS Distinguished Dissertation Award His work bridges theoretical foundations (e.g., Nash equilibria, mechanism design) with practical applications in fair resource allocation and transparent AI systems. He actively contributes to conferences like AAAI, AAMAS, and NeurIPS, and collaborates with institutions globally.

Daniel Haraborمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Pathfinding Algorithms
• Optimization
• +۳ مورد دیگر

Daniel Harabor is an Associate Professor in the Department of Data Science & AI at Monash University, Australia. He holds a PhD and BSc (Honours) in Computer Science from the Australian National University (ANU). His research focuses on pathfinding algorithms, multi-agent systems, and optimization, with notable contributions to multi-agent pathfinding (MAPF), transportation routing, and constraint-based reasoning. He leads or collaborates in projects like the 2023 MAPF Competition and the Future of Urban Routing initiative. Education: PhD in Computer Science, ANU (2014) BSc (Honours) in Computer Science, ANU (2007) Research Interests: His work emphasizes practical and efficient solutions for combinatorial search problems, including real-time pathfinding, public transport optimization, and large-scale multi-agent coordination. He develops algorithms for dynamic environments with applications in robotics, urban planning, and logistics. Awards: DECRA Research Fellowship (Australian Research Council) Projects & Grants: He has secured funding for projects such as 'Personalised Public Transport' (2019–2025) and 'Improved Constraint Reasoning for Robust Multi-agent Path Planning' (2021–2024). His work often involves collaboration with global experts in AI and robotics. Labs & Teams: Active in the Data Science & AI research group at Monash, contributing to MAPF competitions and open-source pathfinding tools like JPS (Jump Point Search).

• Medical Image Segmentation
• Motion Segmentation
• Visual Object Tracking
• +۹ مورد دیگر

Dr. Sandeep Singh Sengar is a Senior Lecturer in Computer Science at Cardiff Metropolitan University, United Kingdom. Prior to his current role, he served as a Postdoctoral Research Fellow at the Machine Learning Section of the Computer Science Department at the University of Copenhagen, Denmark. His academic journey includes a Ph.D. in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India, and an M. Tech. in Information Security from Motilal Nehru National Institute of Technology, Allahabad, India. Sengar actively engages in research collaboration and has organized special sessions and delivered keynote presentations at international conferences. Education: Dr. Sengar holds the following academic qualifications: Ph.D. in Computer Science and Engineering from Indian Institute of Technology (ISM), Dhanbad, India M. Tech. in Information Security from Motilal Nehru National Institute of Technology, Allahabad, India Research Interests: Dr. Sengar's research focuses on advanced applications of machine/deep learning and computer vision, particularly in healthcare diagnostics and cybersecurity. His work combines theoretical methodologies with practical implementations, including: Medical Image Segmentation (e.g., brain tumors, functional connectivity) Motion Segmentation and Tracking for surveillance and activity recognition Visual Object Tracking and Recognition in dynamic environments Video Compression techniques leveraging adaptive optimization Cybersecurity frameworks targeting DDoS attack mitigation Exploring Metaverse applications in healthcare and AI ethics Publications Trends: His recent articles emphasize interdisciplinary innovation, with a strong focus on healthcare AI and cybersecurity. Key themes include hybrid neural networks for medical imaging, entropy-driven frameworks for neurological disorders, and proactive network threat detection using deep learning. He also investigates emerging technologies like the Metaverse's role in healthcare systems and generative AI's broader applications. Scientific Awards: No scientific awards were explicitly mentioned in the provided texts. Advising & Grants: While Dr. Sengar has not listed formal advisees or grant details, his research mentorship is evident through collaborative projects and conference contributions. He actively participates in organizing special sessions and peer-review processes, fostering academic-industry partnerships. Labs & Teams: Though no specific labs are named, his work aligns with Cardiff Met's research centers and innovation initiatives, such as the PDR International Centre for Design and Research and ZERO2FIVE Food Industry Centre.