Luminița POPA is a Lecturer at the Automation and Information Technology department within the Faculty of Electrical Engineering and Computer Science at Transilvania University of Brașov, Romania. Her work integrates computer-aided design, simulation, and sustainability principles into industrial applications. Research Focus: Computer-aided graphics/design/modeling/simulation, Product Lifecycle Management (PLM), Industrial circular economy, and User interface design Contact: Email: luminitapopa@unitbv.ro | Address: Mihai Viteazu 5, Brașov, Romania, Building V Her recent publications highlight eco-sustainability analysis in manufacturing, circular economy applications in business processes, and robotics modeling. She utilizes tools like CAD SolidWorks and contributes to sustainable design frameworks. No scientific awards or student advisement details were explicitly mentioned in the provided text.
Natalia Anatolyvna Kulikovska serves as a Senior Lecturer at the Department of Computer Systems and Networks within the Faculty of Computer Science and Technology at Zaporizhia National Technical University. She has maintained a continuous academic affiliation with the university since 2010, contributing significantly to both teaching and research initiatives in computer science and technology. Dr. Kulikovska completed her higher education at Zaporizhia National Technical University, graduating in 2010 with a Master's degree in "Specialized Computer Systems" and further specializing in "Organizational Management" in 2011. Her academic credentials are complemented by multiple scholarly identifiers including Scopus (ID: 57208667683), ResearcherID (AAE-4642-2019), Google Scholar, and ORCID (0000-0003-4691-5102). Her research expertise spans semantic technologies, modeling, multi-service systems, ontology, web services, and Service-Oriented Architecture (SOA). Dr. Kulikovska's scholarly work demonstrates a progressive evolution from theoretical foundations in distributed knowledge-based systems toward practical implementations in Internet of Things applications. Her early publications focused on semantic service structures and distributed knowledge systems, while her recent work (2022-2024) shows a pronounced shift toward practical IoT applications addressing real-world challenges in environmental monitoring, temperature control, and security protocols. Analysis of her recent publications reveals a consistent research trajectory focusing on the intersection of semantic technologies with IoT implementations. Her work addresses critical challenges in data transmission integrity, system resilience, security measures for IoT devices in fog computing environments, and the integration of Big Data analytics with distributed sensor networks. Notably, her research on chatbot applications for environmental control represents an innovative fusion of natural language processing with practical IoT solutions. As an educator, Dr. Kulikovska teaches courses in modern internet technologies, information protection, software engineering, and modern programming methods. Her teaching methodology likely integrates her research findings, providing students with current knowledge in rapidly evolving technological domains. While specific details about her advising responsibilities are not available in the provided text, her extensive publication record suggests active mentorship of students in research projects related to distributed systems and IoT technologies. Her laboratory and team affiliations are not explicitly detailed in the available information, though her research focus suggests potential involvement with university centers specializing in computer modeling, intelligent systems, and IoT development. Her work on green computing in Ukraine indicates engagement with sustainability initiatives within the technological sector.
Florica Moldoveanu is a Professor at the Faculty of Automatic Control and Computers, University Politehnica of Bucharest. Their research focuses on Virtual Reality (VR), Medical Informatics, and Human-Computer Interaction with a strong emphasis on healthcare applications, assistive technologies, and educational technology. Developed VR systems for phobia treatment and neuromotor rehabilitation (TRAVEE) Pioneered sensory substitution interfaces for visually impaired individuals Advanced GPU-accelerated medical imaging and 3D reconstruction techniques Contributed to SDN networking and healthcare interoperability standards Research spans VR therapy systems, machine learning for emotion/fear detection, and inclusive gaming for accessibility. Collaborations include projects on real-time medical image processing and augmented reality applications in education and healthcare. Publications emphasize interdisciplinary work combining computer science with medicine/education, with over 100+ peer-reviewed articles across journals like Sensors, IEEE Access, and Symmetry. Active in conferences such as IEEE VR, HCII, and CHI.
Csaba Zoltán KERTÉSZ is a Lecturer at the Department of Electronic and Computers, Faculty of Electrical Engineering and Computer Science, Technical University of Brașov. His research focuses on embedded systems, microcontroller applications, graphical user interfaces, digital signal processing, and real-time operating systems. He has contributed to IoT/M2M communication, wireless sensor networks, and SDR platforms. He has also explored the use of GitHub in collaborative learning and automotive industry-supported curriculum design. Key research interests include: Embedded GUI development frameworks IoT gateway systems using SDR Real-time monitoring and control systems HbbTV architecture performance analysis His recent work (2021-2024) emphasizes: AI-driven programming assessment tools SIMD extension optimization Wireless sensor networks for water distribution Reconfigurable IoT infrastructure Publications span over 15 years, showing sustained contributions in embedded systems, telecommunications, and educational technology. No specific awards mentioned. Labs/Teams: Actively involved in the University's embedded systems and IoT research groups.
