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Dr. habil. Simon János PhD is an Associate Professor at the University of Szeged's Faculty of Engineering, Institute of Technology. Born on July 27, 1980, he maintains his office at 6724 Szeged, Moszkvai krt. 9. Room F9, with contact number +36-62-546-575. His educational background includes IT engineering and electrical engineering from Technical College of Subotica (1999-2005), Certified Computer Engineering from University of Novi Sad (2005-2008), PhD in Engineering from University of Osijek (2008-2014), and habilitation from Óbuda University Doctoral School of Security Sciences (2020). English (intermediate, complex) Serbian (advanced, complex) Dr. Simon's research focuses on design and programming of Internet of Things environments, hardware and software development of mobile robots and wireless sensor networks, and analysis of Industry 4.0 case studies. His teaching portfolio includes Computer Modeling, Simulation courses, Microcontrollers, Graphical Programming at BSc level, and Real-time systems, Autonomous and intelligent robots at MSc level. He serves as Associate Editor for Analecta Technica Szegedinensia and is a member of the Higher Education Management Education Methodology Association (FIOM). His international experience includes CEEPUS mobility to Timisoara, Erasmus mobility to multiple Romanian cities, and participation in IoTTech Expo Global in London.

• Internet of Things
• Mobile Robotics
• Wireless Sensor Networks
• +5 more

László Lengyel is a Professor at the Budapest University of Technology and Economics (BME), affiliated with the Department of Automation and Applied Informatics . His work bridges theoretical and applied computer science, focusing on industrial automation, IoT systems, and model-driven engineering. Research interests include Model transformations and domain-specific languages IoT device management and multi-domain integration Software obfuscation and cybersecurity Graph algorithms and distributed computing (MapReduce) Real-time data analysis in manufacturing Automotive sensor networks His recent publications reflect expertise in model-driven IoT architectures , granule manufacturing automation , and MapReduce-based graph analysis , with a focus on industrial and automotive applications. He contributes to open-source frameworks like SensorHUB and explores gamification in driver behavior systems.

• Model-Driven Engineering
• Internet of Things (IoT)
• Software Obfuscation
• +7 more

Tamás Tettamanti is a Professor at Budapest University of Technology and Economics, serving as Deputy Head of the Department of Control for Transportation and Vehicle Systems. He holds a PhD (2013), Habilitation (2023), and DSc (2023) in Transportation Engineering, with expertise in road traffic modeling and control. 2007–2010: PhD Student 2010–2013: Assistant Lecturer 2014–2018: Senior Lecturer 2019–2024: Associate Professor 2025–present: Full Professor Education: High School Graduation (2001), DEUG (2004), MSc in Transportation Engineering (2007), Jazz Trumpet Graduate (2008) PhD (2013), Habilitation (2023), DSc (2023) Research focuses on road traffic modeling, intelligent transportation systems (ITS), autonomous vehicle integration, and emission-aware traffic control. His work bridges theoretical developments with real-world applications, including wireless traffic light systems and deep learning for urban mobility peaks. Scientific Awards: BME PhD Research Prize (2012) Literary Awards from Hungarian Scientific Association for Transport (2013, 2017, 2021, 2023) Bolyai János Research Scholarship (2017–2020) Michelberger Master Prize (2022) BME Jubilee Medal (2023) He has led major projects such as Dynamic Adaptive Traffic Control Services (2020–2024) and Deep Learning Anticipated Urban Mobility Peaks (DARUMA) (2021–2024), with industry collaborations including Google-BME Traffic Lab.

• Road Traffic Control
• Intelligent Transportation Systems
• Traffic Simulation
• +3 more

Dr. Balázs Varga is a Research Fellow at the Department of Control for Transportation and Vehicle Systems, Budapest University of Technology and Economics (BME). He holds a PhD in Transportation and Vehicle Sciences (2021) and an MSc in Vehicle Engineering (2015) from BME. His industry experience includes roles at AVL Hungary as a Software and Function Developer (2016–2018) and academic positions at Chalmers University of Technology (2015) and SZTAKI (2012–2014). Current Role: Research Fellow (2021–present) Teaching: Programming, Control Theory, Traffic Modeling (English language course) Research Interests: Varga specializes in road traffic modeling and control, focusing on AI-based traffic estimation and dynamic traffic management. His work integrates machine learning with mesoscopic and microscopic traffic simulation tools like SUMO to optimize urban mobility and reduce emissions. Projects: He leads the 2020–2024 national development project 'Dynamic, adaptive traffic control services and evaluation tools based on digitally connected data sources' (2019-1.1.1-PIACI KFI). This initiative leverages connected data sources for real-time traffic control and policy evaluation. Key Publications Trends: His recent articles explore topics such as graph neural networks for sensor placement, multiobjective control of emissions, and mixed-reality V2X testing. These works emphasize data-driven approaches, emission reduction, and simulation frameworks for autonomous vehicles.

• Road Traffic Modeling and Control
• AI-based Traffic Flow Prediction
• Urban Traffic Simulation
• +3 more

Dr. Gergely Vakulya is an Associate Professor and Research Fellow at Óbuda University. He specializes in interdisciplinary research spanning cybersecurity, agricultural technology, sensor networks, and image processing. His work integrates hardware design, algorithm development, and real-world applications. Dr. Vakulya’s recent focus includes developing rumen bolus sensors for dairy cattle health monitoring, gamification of cybersecurity training, and innovative methods in camera exposure time measurement. He is affiliated with Óbuda University’s Budai Road and Pirosalma Street campuses, with an office at building F room 316. His research frequently addresses challenges in data collection, sensor fusion, and embedded systems. Research Interests: Dr. Vakulya’s expertise includes cybersecurity frameworks (e.g., CTF challenges), agricultural IoT systems (e.g., rumen bolus sensors for livestock monitoring), and image processing techniques (e.g., genetic algorithms for shape approximation). His work on visible light communication (VLC) and wireless sensor networks highlights his contributions to communication protocols and energy-efficient systems. Recent trends in his publications emphasize cross-disciplinary approaches, such as applying AI methods to agricultural sensor data and optimizing sensor networks for real-time applications. Advising & Grants: No specific advising relationships or grants are listed in available materials. His research infrastructure is likely supported through institutional and collaborative projects. Labs/Teams: While not explicitly stated, his research likely involves collaborations within Óbuda University’s engineering and computer science departments. His work on rumen sensors and VLC systems suggests potential affiliations with robotics, biomedical engineering, or smart agriculture research groups.

• Cybersecurity
• Agricultural Technology
• Sensor Networks
• +3 more

Charaf Hassan is a Professor and Head of Department at the Budapest University of Technology and Economics, specifically in the Department of Automation and Applied Informatics. His work spans interdisciplinary domains, focusing on distributed systems, network coding, and IoT technologies. His research interests include Distributed Systems and Domain-Specific Modeling Network Coding and Mobile Peer-to-Peer Systems Model-Driven Development for Multiplatform Applications Machine Learning in Fluid Dynamics and Pharmaceutical Analysis Recent publications highlight trends in applying convolutional neural networks to viscosity estimation, model-driven methodologies for IoT, and network coding in cloud storage. He teaches advanced courses in distributed systems and software architectures at the university level.

• Distributed Systems
• Network Coding
• Internet of Things (IoT)
• +12 more

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.

• Hardware Security
• Physical Unclonable Functions (PUFs)
• Machine Learning in Security
• +4 more

Prof. Gyula Simon is a faculty member at Óbuda University's Alba Regia Faculty, where he holds the rank of Professor. His research focuses on sensor networks, localization systems, and signal processing. He has contributed extensively to advancements in technologies like TDOA-based positioning, VLC communication, and acoustic source tracking. With over two decades of academic work, his publications span applications ranging from agricultural sensors to fault-tolerant indoor positioning systems. Key research interests include developing robust localization algorithms for both outdoor and indoor environments, optimizing wireless sensor networks for energy efficiency and reliability, and integrating emerging technologies like visible light communication (VLC) for beaconing and tracking. His work bridges theoretical signal processing with practical implementations in fields like smart agriculture and security systems. Recent articles highlight innovation in hyperbolic localization methods, sparse sampling techniques for camera systems, and semi-automatic plant growth monitoring. Despite prolific publication output, no scientific awards are explicitly listed. Consultation hours are arranged via email at simon.gyula@amk.uni-obuda.hu, with his office located at Building F Room 316 in Székesfehérvár.

• Sensor Networks
• Localization Systems
• Signal Processing
• +3 more

Dr. Péter Udvardy is an Associate Professor at Óbuda University. He is affiliated with the university's engineering and environmental science programs, located at the Budai Út Campus in Székesfehérvár. His research focuses on advanced technologies such as UAV applications, agricultural sensors, robotics, and environmental monitoring. He actively contributes to interdisciplinary fields like precision agriculture, remote sensing, and GIS-driven urban planning. His work combines theoretical and practical innovations, addressing challenges in renewable energy infrastructure inspection, livestock health monitoring via ingestible sensors, and educational robotics. Notable projects include UAV-based wind turbine assessment and bolus sensor development for dairy cattle. Udvardy emphasizes real-world problem-solving in industrial maintenance, data collection methodologies, and sustainable energy solutions. He maintains a consultation schedule on Mondays and can be reached via udvardy.peter@amk.uni-obuda.hu. His research outputs are publicly accessible via Google Scholar and institutional repositories.

• Remote Sensing
• Agricultural Technology
• Robotics
• +3 more

Gábor Kiss is an Associate Professor in the Department of Atomic Physics at Budapest University of Technology and Economics (BME). His research focuses on applied physics, surface physics, gas sensors, electrolytic capacitors, and hydrogen storage in metals. He has contributed to studies on metal hydride alloys, titanium-based medical implants, and gas detection technologies. His work involves advanced analytical methods like XPS, SIMS, and AES. Notable collaborations include investigations into hydrogen absorption/desorption processes and the effects of surface contaminations on hydrogen storage materials. Recent work extends to speech-based medical diagnostics, leveraging machine learning for depression and Parkinson’s disease detection. Education details are not explicitly listed, but his research expertise spans materials science and interdisciplinary applications. His publications emphasize surface analysis techniques and their biomedical and energy storage applications. He has co-authored influential papers in journals like Analytical and Bioanalytical Chemistry and Sensors and Actuators B. Research trends in his recent articles focus on computational linguistics (e.g., Hungarian speech data analysis), clinical diagnostics via speech processing, and optimization in wireless sensor networks. These reflect a shift towards AI-driven healthcare solutions while maintaining core strengths in materials physics. No awards or grants are explicitly mentioned, but his extensive publication record and cross-disciplinary collaborations indicate significant contributions to both fundamental and applied research.

• Applied Physics
• Surface Physics
• Gas Sensors
• +3 more

Péter Ekler is an Associate Professor at the Department of Automation and Applied Informatics , Budapest University of Technology and Economics (BME) , Hungary. He is affiliated with the Applied Mobile Research Group (AMORG) and the Applied Computer Science Group , focusing on cutting-edge research in AI, IoT, and mobile systems. Research Interests: Artificial Intelligence and Machine Learning Internet of Things (IoT) and Smart Cities Wireless Sensor Networks and Energy-Efficient Routing Network Coding and Mobile Peer-to-Peer Systems Blockchain and Distributed Systems Computer Vision and Sensor Data Analysis His recent work includes the development of AI-based thermal imaging systems, energy-aware IoT routing, and secure authentication mechanisms using JWT. He has published extensively on optimizing IoT performance, enhancing mobile streaming with network coding, and applying machine learning to real-world sensor data. Scientific Contributions: Published over 50 peer-reviewed articles from 2013 to 2023 Active on platforms like Google Scholar, Scopus, ResearchGate, and ResearcherID Research spans both technical systems and historical studies in science Contact & Affiliations: Email: Ekler.Peter@aut.bme.hu Location: Q.B226, Magyar tudósok krt. 2., Budapest 1117, Hungary Phone: +36 (1) 463-3702 LinkedIn: http://hu.linkedin.com/in/peterekler

• Artificial Intelligence
• Machine Learning
• Internet of Things
• +7 more

Professor Zoltán Gál serves as Professor and Head of the Department of IT Systems and Networks at the Faculty of Informatics, University of Debrecen, with contact details including email gal.zoltan@inf.unideb.hu and office location at 4028 Debrecen, Kassai út 26. (Faculty of Informatics building, ground floor, IF12). His research expertise spans critical domains in computer networking and systems engineering: Real-Time Communication Wireless Broadband Networks Multimedia Communication High-Speed Packet Switching Sensor Networks Internet of Things Distributed Computer Systems Parallel Computer Architectures Parallel Computing Professor Gál maintains active scientific profiles across MTMT, ODT, iDEa, Tudóstér, Google Scholar, ResearchGate, ORCID, Scopus, and Web of Science, with curriculum vitae and teaching information accessible via his organizational webpage.

• Real-Time Communication
• Wireless Broadband Networks
• Multimedia Communication
• +6 more

János Hamar is an Associate Professor at the Department of Automation and Applied Informatics , Budapest University of Technology and Economics. His work bridges power electronics and control systems with a focus on energy efficiency and renewable energy integration. Specializes in resonant DC-DC converter topologies Developed multi-agent control systems for parallel converters Contributed to E-learning tools in power electronics Explores electromagnetic interference (EMI) mitigation Investigates microgrid power distribution His research spans symmetrical and asymmetrical converter operations, virtual laboratories, and smart energy systems like "Energymon." Publications highlight innovations in multilevel converters, common-mode noise suppression, and discrete-time modeling tools. Awards and student supervision details remain unspecified in available sources.

• Power Electronics
• Control Systems
• Renewable Energy Integration
• +3 more

László Blázovics is a Senior Lecturer at the Department of Automation and Applied Informatics, Budapest University of Technology and Economics. He leads the Applied Mobile Research Group (AMORG) focusing on mobile computing and distributed systems. His office is located at Q.B222, Magyar tudósok krt. 2., Budapest 1117, Hungary, with contact available via phone (+36 1 463-1648) and email. His primary research explores: Swarm robotics including drone coordination, uniform dispersal algorithms, and obstacle avoidance Distributed systems featuring sensor networks, multi-robot frameworks, and decentralized algorithms Mobile technologies spanning 5G networks, VR teleoperation, and cognitive communication AI applications such as human activity recognition and sensor fusion techniques Publication analysis reveals consistent focus on autonomous systems since 2011, with recent expansion into 5G-enabled applications and AI-driven solutions. Earlier work established foundations in swarm robotics and distributed algorithms, while recent publications demonstrate applied research in VR streaming, drone networks, and neural networks. He maintains active involvement in the Applied Mobile Research Group (AMORG), developing simulation frameworks for multi-robot systems and investigating cognitive drone applications.

• Robotics
• Distributed Systems
• Mobile Networks
• +2 more