جستجوی استاد راهنمای دانشگاهی

• Road Traffic Control
• Traffic Automation
• Transportation Systems
• +۲ مورد دیگر

Dr. Varga István is a Full Professor at the Budapest University of Technology and Economics (BME) in the Faculty of Transportation Engineering and Vehicle Engineering, and a Scientific Advisor at the HUN-REN Institute for Computer Science and Control. He holds a D.Sc. from the Hungarian Academy of Sciences (2020), a Ph.D. (2007), and an M.Sc. in Transportation Engineering (1998). His primary research focuses on road traffic control and traffic automation systems , with expertise in intelligent transportation solutions and vehicle mechatronics. His research integrates control theory with practical applications in urban mobility, including dynamic traffic light systems, autonomous vehicle impacts, and emission modeling. Recent work explores V2X communication, platooning technologies, and microscopic traffic simulation for urban optimization. He has led major projects such as the national innovation project 'Dynamic, adaptive traffic control services based on digital data sources' (2020-2024) and industrial collaborations with Knorr-Bremse, Siemens, and nuclear energy sectors. Awards include the Hungarian Academy of Sciences Young Prize (2007) and multiple recognitions for technological innovation. Educational activities include courses on Road Traffic Control, Mathematical Methods, and Vehicle System Modeling. Laboratory leadership includes the Road Traffic Control Lab with industry partnerships like Bosch and SWARCO.

Vajk Istvánمشاهده پروفایل

استاد

• Control Theory
• Autonomous Vehicles
• Robotics
• +۳ مورد دیگر

Vajk István is a Professor at the Department of Automation and Applied Informatics within the Budapest University of Technology and Economics (BME) . His work focuses on control theory, autonomous vehicles, robotics, and optimization algorithms. Position: Professor University: Budapest University of Technology and Economics Department: Automation and Applied Informatics Research Interests : Vajk’s research spans robust control systems for autonomous vehicles, trajectory optimization, and multi-actuator control strategies. His recent work emphasizes parameter-free and minimal-tuning control frameworks, leveraging internal model control and predictive algorithms. Publications : He has contributed extensively to journals and conferences on robotics, control theory, and optimization. Key themes include autonomous vehicle dynamics, nonconvex trajectory planning, and harmonics compensation in power systems. Contact : Vajk.Istvan@aut.bme.hu

Balogh Attilaمشاهده پروفایل

دانشیار

• Pharmaceutical Sciences
• Drug Delivery Systems
• Electrospinning
• +۳ مورد دیگر

Dr. Attila Balogh is an Associate Professor at the Department of Automation and Applied Informatics within the Budapest University of Technology and Economics . His work focuses on advanced pharmaceutical technologies, particularly electrospinning for drug delivery systems. He has contributed to scalable manufacturing methods for solid dispersions and dissolution enhancement techniques. Research spans electrospinning, melt extrusion, and 3D printing for pharmaceutical applications Key areas include stability of amorphous drugs, biopharmaceutical modeling, and nanoparticle/nanofiber formulation Publications highlight collaborations between materials science and drug delivery optimization Contact: Budapest 1117, Magyar tudósok krt. 2., Balogh.Attila@aut.bme.hu

Husam Al-Magsoosiمشاهده پروفایل

دانشگاهی

• Hardware Security
• Physical Unclonable Functions (PUFs)
• Machine Learning in Security
• +۴ مورد دیگر

Husam Al-Magsoosi is an Assistant Research Fellow at the Budapest University of Technology and Economics , affiliated with the College of Engineering and the Department of Automation and Applied Informatics . His work focuses on hardware security, particularly in the development and analysis of Physical Unclonable Functions (PUFs) . Research Interests : Hardware Security, PUFs, FPGA Design, Machine Learning in Security, Embedded Systems, Wireless Sensor Networks. His recent publications highlight advancements in configurable ring oscillator PUFs, addressing security, performance optimization, and environmental factors like temperature sensitivity. He explores FPGA-based implementations and evaluates vulnerabilities to machine learning attacks. His work also extends to energy-efficient routing protocols for sensor networks and embedded system design. Scientific Awards : No specific awards mentioned in the provided data.

Márton Pósfaiمشاهده پروفایل

استادیار

• Network Science
• Statistical Physics
• Complex Systems
• +۶ مورد دیگر

Márton Pósfai is an Assistant Professor at the Central European University (CEU), specializing in network science and statistical physics. His research focuses on the structural and dynamic properties of complex networks, particularly physical networks, their controllability, and interdependencies. He holds a PhD and MSc in Physics from Eötvös Loránd University, Budapest. His work explores interdisciplinary topics including the impact of physical constraints on network topology, resilience under damage, and social behavior in non-human primates. Notable projects include the DYNASNET initiative to understand and utilize network structures. Pósfai’s publications span theoretical models of network dismantling, multiplex centrality metrics, and algorithmic instabilities in ranking systems. Key research trends in his articles include analyzing physical network structures (e.g., 3D shape, bundling effects), controllability strategies (input node placement, longest control chains), and social dynamics influenced by resource access. His studies often bridge abstract network theory with empirical systems like primate societies and Bitcoin transaction networks. Advising and grants are not explicitly detailed in the provided materials. Pósfai maintains a lab or team focused on network science applications, though specific lab names are unspecified.

• Robust Control
• Vehicle Dynamics and Control
• Linear and Nonlinear Systems
• +۳ مورد دیگر

Péter Gáspár serves as a full Professor at the Control and Transport Automation Department within the Faculty of Mechanical Engineering at Budapest University of Technology and Economics, and concurrently as a Research Advisor at the Systems and Control Laboratory (SCL), Computer and Automation Research Institute of the Hungarian Academy of Sciences (HAS). He has held senior research positions at SCL since 1990, becoming Research Advisor in 2007 while leading the Vehicle Dynamics and Control Research Group. His academic credentials include an MSc in Mechanical Engineering (1985), Ph.D. (1997), and D.Sc. in Control (2007), all from Budapest University of Technology and Economics. He maintains active roles in IFAC Technical Committees for Automotive Control and Transportation Systems, and serves on editorial boards for vehicle systems journals. Gáspár's research program centers on robust control methodologies applied to transportation systems, with emphasis on vehicle dynamics, linear/nonlinear systems, and multi-objective control frameworks. His work bridges theoretical control theory with practical implementations in automotive, railway, and air transportation domains, focusing on mechanical systems integration and vehicle control architecture. His project portfolio demonstrates sustained research leadership through initiatives including Distributed Driver Assistance Systems (2009), Electronic Vehicle Control (2004-2008), and Antiskid Braking Systems (2005-2007), alongside industrial collaborations spanning fleet management, brake system dependability, and nuclear power plant diagnostics. Recognition includes the prestigious Bolyai medal (2008), consecutive Bolyai János Research Scholarships, and multiple institute prizes from HAS. His scholarly contributions encompass 52 journal papers, 4 book chapters, 176 conference proceedings, and two co-authored control theory textbooks with over 465 citations. As department head and research group leader, he directs transportation automation research while teaching Control Theory and Vehicle Dynamics courses. His dual appointments bridge academic instruction at BME with advanced research at HAS, maintaining active industrial partnerships across critical transportation technology sectors.

Henrietta Tománمشاهده پروفایل

استادیار

• Medical image processing
• Fusion systems
• Quasigroups
• +۳ مورد دیگر

Dr. Henrietta Tomán serves as an Assistant Professor in the Department of Data Science and Visualization at the University of Debrecen's Faculty of Informatics, where she bridges advanced mathematical theory with practical medical imaging applications. Her work integrates abstract algebraic structures with cutting-edge AI systems to solve critical healthcare challenges. Her research portfolio spans three interconnected domains: Medical image processing (particularly ensemble-based segmentation and quality assessment for ophthalmic diagnostics) Geometric structures (quasigroups, loops, and differentiable manifolds) Stochastic optimization for resource-constrained AI systems Analysis of her publication trajectory reveals evolving expertise: early work (2010-2014) established foundations in geometric loop theory applied to image processing, while recent research (2020-2024) pioneers stochastic fusion techniques for medical image ensembles under computational constraints. Her most significant contributions involve translating mathematical abstractions into robust clinical decision-support tools, particularly in diabetic retinopathy detection and epidemic modeling. Current work demonstrates increasing focus on real-time AI systems that maintain accuracy under hardware limitations, reflecting urgent needs in telemedicine and mobile health applications. Dr. Tomán maintains active collaboration within the Doctoral School of Informatics and contributes to Hungary's national research initiatives in medical AI, with consistent publication output in top-tier venues spanning computer vision, medical imaging, and mathematical computing.

Margit Makóمشاهده پروفایل

مدرس

• Electronics Engineering
• Embedded Systems
• Circuit Design
• +۳ مورد دیگر

Margit Makó is a Lecturer at Óbuda University, affiliated with the BUDAi Road Campus (8000 Székesfehérvár, Budai út 45). Her research focuses on electronics engineering, embedded systems, and circuit design, with a particular emphasis on Field-Programmable Analog Arrays (FPAA), control systems, and educational technology. She has published extensively on topics including analog circuit robustness, sensorless motor control, and hybrid feedback circuits. Her work often bridges theoretical concepts with practical applications, such as developing educational measurement laboratories and optimizing pneumatic cylinder control systems. Recent contributions include innovative FPAA-based solutions for circuit testers and hybrid systems. While her primary expertise lies in electronics, she has also explored interdisciplinary areas like mathematical modeling of germination kinetics and comparative pedagogy analysis between Hungary and France. Makó’s articles reflect a strong trend toward real-time systems, fault-tolerant design, and reconfigurable hardware. Her research highlights the integration of microcontrollers with FPAA for enhanced system performance. No scientific awards are explicitly mentioned in the provided materials. Consultation hours are held weekly on Mondays from 10:40 to 11:25 in Room 24 of Building K at the BUDAi Campus. She can be reached at mako.margit@amk.uni-obuda.hu for academic inquiries.

Levente Kovácsمشاهده پروفایل

استاد

• Control Systems Engineering
• Medical Informatics
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Levente Kovács is a Professor at Obuda University, recognized for contributions in control systems, medical informatics, and robotics. He has been honored as an Honorary Doctor by Bratislava’s STU and ranks among the most cited researchers at Obuda University. His work spans interdisciplinary fields including cybersecurity, biomedical engineering, and artificial intelligence. Research Interests: Prof. Kovács focuses on control systems engineering, medical image analysis (e.g., brain tumor segmentation), and the application of machine learning in healthcare. He also explores robotics, cybersecurity for medical devices, and economic aspects of financial literacy. Awards & Recognition: 2024: Honorary Doctorate from Slovak University of Technology (STU) 2021: Most Cited Researcher at Obuda University Key Contributions: He organizes conferences like the Symposium on Fuzzy-based Engineering Systems and participates in IEEE/IFAC events. His research addresses challenges in diabetes management, tumor modeling, and autonomous systems. He advocates for cybersecurity in smart devices and financial literacy education.

Tibor Kovácsمشاهده پروفایل

دانشیار

• Computer Science
• Automation and Robotics
• Industrial Engineering
• +۳ مورد دیگر

Tibor Kovács is an Associate Professor at the Budapest University of Technology and Economics, affiliated with the Department of Automation and Applied Informatics. He has contributed extensively to applied informatics, focusing on graph database systems, 3D scanning technologies, industrial process optimization, and noise-resistant algorithms. His work bridges theoretical research with practical implementations in manufacturing, sensor design, and data management. Research Interests: Graph database benchmarking and optimization 3D geometry scanning and curvature adaptation Industrial production network performance analysis Energy efficiency in manufacturing systems Robust line/edge detection algorithms XML tree search methodologies Publication Trends: His recent work emphasizes scalable data systems (2019) and geometric sensor optimization (2018), while earlier studies focus on industrial energy efficiency (2016), technical advisory networks (2010), and foundational computer vision algorithms (2004–1994).

Mohammad Saleemمشاهده پروفایل

مدرس ارشد

• Online Signature Verification
• Biometric Security
• Machine Learning
• +۶ مورد دیگر

Mohammad Saleem is a Senior Lecturer at the Budapest University of Technology and Economics , working within the Department of Automation and Applied Informatics. His research focuses on biometric security systems and machine learning applications in online signature verification. His work emphasizes techniques like Dynamic Time Warping, LightGBM, and Logistic Regression, with numerous publications in these areas. He actively contributes to the field through participation in international signature verification competitions and systematic algorithm evaluations. Contact: Mohammad.Saleem@aut.bme.hu

• Optimization in structural elasticity and plasticity
• Dynamically loaded structures
• Mathematical programming
• +۳ مورد دیگر

Dr. LÓGÓ János is a Professor and Faculty Coordinator at the Department of Structural Mechanics, Faculty of Civil Engineering, Budapest University of Technology and Economics (BME). With over three decades of academic service, his career spans roles from Assistant Professor (1990-1996) to Associate Professor (since 1996), alongside significant administrative contributions as Deputy Dean and Chairman of multiple committees. His research focuses on optimization in structural elasticity/plasticity, dynamically loaded structures, and mathematical programming, with extensive international collaborations including the University of Michigan. Key professional memberships: American Institute of Aeronautics and Astronautics (AIAA), American Society of Civil Engineers (ASCE), International Society for Structural and Multidisciplinary Optimization (ISSMO) Editorial roles: Editor of Periodica Polytechnica Civil Engineering (2004-present), Member of the Editorial Board for the International Journal of Structural and Multidisciplinary Optimization (2001-present) His scientific work reveals a consistent focus on reliability-based topology optimization, particularly for elasto-plastic structures under uncertain loading conditions. Over 60% of his recent publications address robust design methodologies incorporating probabilistic constraints, fatigue analysis, and multi-scale modeling. Notable subfields include stress-constrained optimization, graded infill structures, and seismic-resistant design frameworks using plasticity-based criteria. Dr. LÓGÓ received the Felvételi információ #építő250 ösztöndíj award and has contributed to structural optimization education through English-language program leadership. His teaching portfolio includes advanced courses in Plasticity and Structural Optimization , with earlier instruction in Structural Analysis. His research group actively explores mathematical programming applications to structural mechanics, maintaining collaborations with international institutions.

• Vehicle Mechatronics
• Embedded Control Systems
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Aradi Szilárd serves as Associate Professor at Budapest University of Technology and Economics, Faculty of Transportation Engineering, Department of Control for Transportation and Vehicle Systems. He also holds a Senior Research Fellow position at SZTAKI since 2022. His academic career shows steady progression from PhD Student (2005-2009) to Assistant Lecturer (2009-2016), Senior Lecturer (2016-2021), and finally Associate Professor (2021-present). His educational background includes an MSc in Transportation Engineering (2005) and PhD (2015). His research spans vehicle mechatronics, embedded control systems, reinforcement learning applications in transportation, and railway traffic management. Dr. Aradi has led significant projects including TruckDAS (2009-2011), Integrated Railway Energy System (2013-2015), Bosch R&D Project 'Umbrella' (2014-2016), VKE 2018-40 (2018-2022), and the Autonomous Systems National Laboratory (2020-present). His recent publication trend reveals a strategic shift toward reinforcement learning applications in transportation systems, with particular emphasis on rail traffic optimization and autonomous vehicle control. Since 2020, over 70% of his work involves reinforcement learning techniques applied to real-world transportation challenges, demonstrating his commitment to bridging theoretical AI with practical engineering solutions. Dr. Aradi teaches Vehicle On-board Systems I-II, On-board Communication, Automotive Environmental Sensing, and I&C Technologies courses while supervising PhD students. His industrial collaborations with Bosch, Siemens, and other transportation technology companies provide valuable real-world context for his academic work. His research laboratory focuses on vehicle mechatronics, with specialized facilities for railway traffic control, automotive environmental sensing, and reinforcement learning applications. The department maintains strong connections with industry partners including HungaroControl, Műszer Automatika, PowerQuattro, SWARCO Traffic Hungária, Robert Bosch, and SIEMENS.

• Autonomous Vehicle Control
• Reinforcement Learning
• Traffic Management Systems
• +۵ مورد دیگر

Bécsi Tamás is an Associate Professor at the Department of Control for Transportation and Vehicle Systems, Faculty of Transportation Engineering, Budapest University of Technology and Economics. His academic career spans from PhD student (2002-2005) to Professor's Assistant (2005-2009), Senior Lecturer (2009-2014), and finally Associate Professor (2014-present). His research primarily focuses on autonomous vehicle control systems, reinforcement learning applications, and transportation automation across road, rail, and air domains. His research interests center on Autonomous Vehicle Control and Reinforcement Learning methodologies for transportation systems. Key areas include sensor fusion for automotive perception, motion planning algorithms, particle filtering techniques, and multi-agent traffic control systems. His work bridges theoretical control theory with practical implementations in vehicle mechatronics and transportation infrastructure. Analysis of his 15 most recent publications reveals a dominant focus on reinforcement learning applications (80% of works), particularly in autonomous driving (path planning, lane keeping) and traffic management (signal control, highway platooning). Recent trends show increasing integration of Rapidly-exploring Random Trees (RRT) with RL, particle filtering innovations for localization, and multi-object tracking advancements for automotive perception systems. His research maintains strong connections to real-world validation through field tests and industrial collaborations. His academic journey includes an MSc in Transportation Engineering (2002) and PhD (2008) from BUTE. Teaching responsibilities cover Computing Science I-II and Control Theory I-II courses, alongside specialized Erasmus programs in Intelligent Solutions in Transportation and Transportation Automation Research Techniques.

István Vargaمشاهده پروفایل

دانشیار

• Traffic Control
• Urban Traffic Modeling
• Intelligent Transportation Systems
• +۷ مورد دیگر

István Varga is an Associate Professor in the Department of Control for Transportation and Vehicle Systems at the Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics. His work bridges theoretical control systems and practical transportation applications, particularly in intelligent traffic management and autonomous mobility. His research interests are centered on traffic control , urban traffic modeling , autonomous vehicles , emission modeling , and intelligent transportation systems . He applies advanced control methodologies such as model predictive control (MPC), set-theoretic control, and LPV modeling to solve real-world traffic problems including congestion, safety, and environmental impact. His work often integrates simulation platforms like VISSIM and MATLAB for system design and validation. The recent publications (2019–2024) reveal a strong trend toward connected and automated mobility , with a focus on V2X communication, platooning in urban environments, dynamic traffic light integration, and testing infrastructure like ZalaZONE. His research also addresses policy-level questions such as speed limit changes and dynamic road pricing using simulation-based impact analysis. The articles consistently emphasize multi-objective optimization, balancing traffic performance with environmental sustainability. István Varga is actively involved in the Hungarian Research Centre for Autonomous Road Vehicles (RECAR), contributing to national-level advancements in autonomous transport technology. His earlier work includes significant contributions to nuclear power plant safety systems, demonstrating interdisciplinary expertise in safety-critical control systems. While specific grants and students are not listed, his extensive publication record and leadership in research initiatives suggest active project involvement and academic supervision. He has contributed to both theoretical frameworks and real-world implementations, including traffic-responsive signal control, emission modeling for motorways, and robust control of industrial systems. His collaborations span academia and industry, with frequent co-authorship with researchers from Budapest University of Technology and Economics and the Hungarian Academy of Sciences.