Gheorghe Asachi Technical University of IasiRomania
Elena Niculina Dragoi is a Lecturer at the Faculty of Chemical Engineering and Environmental Protection 'Cristofor Simionescu' at Gheorghe Asachi Technical University in Iasi, Romania. Her academic work integrates Artificial Intelligence and Machine Learning tools for solving complex problems in Chemical Engineering and Environmental Protection . With over 30 published papers and six active research projects, her contributions span process optimization, nanomaterials, and sustainable technologies. Teaches Applied Informatics (Years 1 & 4) and Artificial Intelligence at the Faculty of Chemical Engineering Contributes to Programming Engineering at the Faculty of Computer Science, University 'Alexandru Ioan Cuza' Engaged in interdisciplinary courses at the Faculty of Automatic Control and Computer Engineering Research Interests : Elena's work focuses on modelling and optimization (90% emphasis) of chemical processes using AI methodologies, with cross-disciplinary applications in environmental engineering (70%) and chemical engineering (95%). Her recent publications highlight innovations in: 3D-printed nanocomposite adsorbents for pollutant removal Metaheuristic optimization algorithms for industrial processes Hydrogen generation via nanocatalysts Electrochemical biosensors for environmental and health monitoring AI-driven wastewater treatment systems Green chemistry applications in pharmaceutical and dye removal
Stavros Vologiannidis serves as an Assistant Professor in the Department of Informatics, Computer and Telecommunications Engineering at the International University of Greece. His academic career spans both teaching and research in control theory, robotics, and machine learning applications. Previously, he was associated with the Mathematics Department at Aristotle University of Thessaloniki where he completed his education and conducted postdoctoral research. Education: B.Sc. in Mathematics from Aristotle University of Thessaloniki (1997) Ph.D. in Control Theory from Aristotle University of Thessaloniki (2005) with dissertation titled 'ALGEBRAIC-POLYONYMICAL COMPUTING METHODS IN CONTROL THEORY' Dr. Vologiannidis' research focuses on Classical and Intelligent Control Theory, Robotics, and Machine Learning, with particular expertise in polynomial matrices and automatic control systems. His work bridges theoretical mathematics with practical engineering applications, especially in educational robotics and industrial control systems. He has developed several educational platforms including EUROPA, a ROS-based educational robot for teaching sensor integration and data acquisition. His publication record shows a clear evolution from theoretical control systems research toward applied machine learning and educational technology. Recent work demonstrates increasing focus on practical applications of AI in education, urban feature recognition, industrial monitoring, and robotics education across multiple educational levels from middle school through university. His research combines mathematical rigor with real-world implementation. Scientific Recognition: Excellence Scholarship in the 'Excellence Scholarships 2010' program of the Research Committee Total citations exceeding 250 with Scopus H-index of 9 Dr. Vologiannidis has secured numerous research grants and led multiple projects including 'Rapid Earthquake Damage Assessment Consortium – REDACt', 'Predictive Maintenance 4.0', and 'Development of computational methods for optimization of eigenvalue assignment problems'. He has collaborated extensively with institutions across Europe including UTIA Foundation in Prague and has participated in EU-funded projects like GALENOS and GN4-1 GÉANT Research and Education Networking. His laboratory work centers around the EUROPA educational robotics platform and the StreetScouting urban feature detection system, both of which integrate hardware, software, and educational applications. These projects demonstrate his commitment to translating theoretical research into practical educational and industrial tools.
Lavinia Stănică Justina is a university lecturer at the Faculty of Managerial Informatics, Romanian-American University (URA), with 18 years of teaching experience in software programming and e-learning domains. Holding a PhD in Cybernetics and Economic Statistics since 2011, she teaches courses in Romanian and English at both bachelor's and master's degree programs. Her research focuses on ICT's role in innovation, educational technologies, and data analysis for energy consumption, with over 30 publications and multiple coordinated research projects. Faculty: Managerial Informatics University: Romanian-American University Academic Rank: Lecturer Teaching Experience: 18 years PhD: Cybernetics and Economic Statistics (2011) Her research interests include: e-Learning systems and technology integration Artificial Intelligence applications in education ICT's impact on innovation performance Mathematical content modeling Energy consumption data analysis Internet of Things implementations Fractal techniques in imaging Recent publications highlight trends in: Comparative innovation-ICT readiness analysis AI education accessibility Smart energy systems Competitive programming metrics Neural network energy forecasting IoT cloud solutions Modular educational software As Erasmus coordinator since 2013 and Institutional Erasmus Coordinator since 2020, she actively promotes internationalization efforts and academic collaboration with partner universities across Europe.
Călin-Adrian POPA is a Full Professor at the Department of Computer and Software Engineering, Politehnica University of Timişoara. He holds a Ph.D. in Computer Science and Information Technology (2015) from Politehnica University Timişoara, and additional degrees in Mathematics from West University of Timişoara (B.Sc. 2013, M.Sc. 2015). His research focuses on artificial intelligence, machine learning, and neural networks, with specializations in complex-valued systems (octonion, quaternion, Clifford algebra), stability analysis, and synchronization of neural networks. He has been awarded the 'Profesor Bologna' Distinction (2017). Research interests include: Advanced neural network architectures Deep learning for computer vision Fractional-order systems Nonlinear dynamics and control Applications in robotics and astrophysics His publications span 2014–2025, emphasizing theoretical contributions to neural networks and practical applications in computer vision and robotics. He supervises a large cohort of PhD students in AI-related fields.
Gheorghe Asachi Technical University of IasiRomania
Alexandra Cristina Blaga is an Associate Professor at the Faculty of Chemical Engineering and Environmental Protection 'Cristofor Simionescu' of Gheorghe Asachi Technical University of Iași, Romania. Her academic career spans over two decades, with roles including Assistant Professor (2008-2013) and Head of Works (2013-2022) before her current appointment in 2022. Education: PhD in Chemical Engineering (2012), Master in Bioprocesses in Agri-Food (2014), Biochemical Engineering BSc (2004) Her research focuses on unconventional separation processes for biosynthetic products, particularly reactive extraction and liquid membrane transport. She has contributed significantly to improving organic acid biosynthesis using microorganisms and developing biosorbents for environmental applications. Recent publications (2022-2025) highlight her expertise in: Reactive extraction of carboxylic acids using ionic liquids Biosorption of dyes using microbial biomass Green chemistry approaches for natural dye applications Modeling and optimization of separation processes She has directed multiple research projects, including grant TD47/2007 on unconventional extraction processes, and participated in 6 national and 3 international projects. Her editorial contributions include guest editing the Catalysts journal special issue on enzyme engineering.
Ana-Sabina Uban is an Associate Professor at the Faculty of Mathematics and Computer Science, University of Bucharest . She earned her Ph.D. in Computer Science in 2020 under the supervision of Professor Liviu Dinu with a thesis on distributional and stylistic aspects of natural language. She teaches and coordinates courses in natural language processing, AI, and machine learning for both computer science and digital humanities students. Education: Ph.D. in Computer Science, University of Bucharest (2020) – Thesis: "Distributional aspects of natural language. Semantic and stylistic dimensions of text" Research Interests: Dr. Uban’s research is strongly interdisciplinary, bridging natural language processing , computational linguistics , psychology , and cognitive science . She explores historical computational linguistics , distributional semantics , and multilingualism , while also investigating explainability in AI models and mental health disorder detection using social media data. Research Trends & Publication Focus: Her recent publications span clinical NLP , mental health detection , historical linguistics , and multilingual cognate identification . A recurring theme is the application of advanced NLP techniques—such as transformer models, contrastive learning, and ensemble classification—to real-world problems in health, literature, and historical language study. Teaching & Student Supervision: Dr. Uban currently teaches and coordinates the following courses: Bio-medical NLP – Master’s level (English) Artificial Intelligence – Bachelor’s level for Mathematics students Practical Introduction to Machine Learning – Master’s level for Digital Humanities students Natural Language Processing 1 & 2 – Master’s labs and projects Contact: auban@fmi.unibuc.ro
Lorand Szabo is a Full Professor at the Department of Electrical Machines and Drives , Faculty of Electrical Engineering , Technical University of Cluj-Napoca , Romania. He has been affiliated with this institution since 1990, transitioning from Research and Design Engineer to Lecturer (1999), Associate Professor (2007), and Full Professor (current). He also served as an Invited Professor at Pannon University (Hungary, 2007-2008) and University of Pavia (Italy, 2015). Teaching : Special Electrical Machines (1985-present), Electrical Machines and Drives (1996-present), Computer Aided Design of Electromechanical Systems (2009-present). Supervision : Ph.D. supervisor since 2007 for 8 students (6 completed). Research Focus : Linear and variable reluctance electrical machines, fault-tolerant designs, bearing fault detection in motors, and condition monitoring. His work extends to automotive applications (electric vehicles, hybrid systems), wind energy generators, and sustainable material sourcing for electrical machines. Recent Publications (2023-2025) address critical topics in sustainable mobility, including rare earth material dependency, deep-sea mining for electric technologies, battery management systems, and resource-efficient motor designs. These works reflect his interdisciplinary approach combining electrical machine innovation with environmental and industrial systems thinking. Technical Expertise : Finite element analysis (JMAG, ANSYS Motor-CAD), LabVIEW modeling, fault detection algorithms (wavelet transforms, kurtosis deconvolution), and modular motor construction for automotive and renewable energy applications.
Dana Petcu is a Professor at the Computer Science Department of the Faculty of Mathematics and Computer Science at West University of Timisoara. She serves as Director of both the Institute for Advanced Environmental Research and Institute e-Austria Timisoara. With expertise in distributed and parallel computing, she has published over two hundred papers on Cloud, Grid, Cluster, and HPC computing. She is also the chief editor of the open-access journal Scalable Computing: Practice and Experience (SCPE) and has coordinated multiple European Commission-funded projects. Education: Ms. Degree in Computer Science Ph.D. in Numerical Analysis Dana Petcu's research focuses on distributed and parallel computing systems. Her current interests include Cloud & Grid computing, and HPC & Cluster computing. Previously, she worked on Mathematical software, Numerical methods, and Computer graphics. Her work bridges theoretical foundations with practical implementations, particularly in resource management, scheduling algorithms, and scalable computing architectures. She has developed significant expertise in applying these technologies to scientific computing, data-intensive applications, and multi-cloud environments. Her scholarly output demonstrates consistent focus on cloud and distributed computing evolution. Over the past decade, her research has shifted from foundational grid computing to modern cloud technologies, edge computing, and exascale systems. Key themes include resource management across heterogeneous environments, autonomic systems, security SLAs, and multi-cloud portability. Her work shows increasing interdisciplinary connections, particularly with AI/ML techniques applied to resource optimization and anomaly detection in large-scale systems. Scientific Awards: Maria Sibylla Merian-Award (2005) IBM Faculty Award (2009) MLNR Award "Spiru Haret" (2015) Romanian Academy Award "Gheorghe Cartianu" (2015) Dana Petcu has advised numerous graduate students through various master's programs in Distributed and Parallel Computing. She has secured substantial research funding as coordinator of FP7 projects HOST and SPRERS, and as scientific coordinator of mOSAIC. Her grant portfolio includes multiple European Commission-funded initiatives focused on cloud computing infrastructure, resource management, and multi-cloud environments. She has also contributed to EU Research Activities in Cloud Computing as an editor, demonstrating her leadership in shaping European research agendas in this field. She leads the Computer Science Research Center (CCI) and High Performance Computing Service Center (HPC-UVT) at West University of Timisoara. Her teams develop and maintain significant infrastructure for distributed computing research, including simulation environments like CloudSim and iFogSim. She has established strong connections between academic research and practical applications through Institute e-Austria Timisoara, fostering technology transfer and innovation in cloud computing solutions.
Prof. Dan Cristea is a faculty member at the Faculty of Computer Science, Alexandru Ioan Cuza University (UAIC), specializing in Artificial Intelligence and Natural Language Processing. He holds a PhD and is a corresponding member of the Romanian Academy. His research focuses on computational linguistics, knowledge representation, and historical document deciphering, with notable projects like DeLORo for old Cyrillic texts and EUROLAN Summer Schools. He has supervised numerous students in AI and NLP projects, including systems for question-answering, sentiment analysis, and agent-based models. His work bridges theoretical linguistics with practical applications in digital heritage preservation and multilingual technologies. Education: PhD (not explicitly stated in text), but his academic rank implies doctoral qualifications. Research Interests: AI applications in NLP, discourse analysis, computational linguistics, and cultural heritage digitization. Projects include MappingBooks for geographical text navigation, CoBiLiRo for bimodal corpora, and Sentimatrix for sentiment analysis. He collaborates internationally on corpora like EuReCo and has developed tools for dependency parsing and semantic annotation. Key Achievements: Corresponding member of the Romanian Academy Lead developer of the Corpus of Contemporary Romanian Language (CoRoLa) Pioneered AI-driven historical document transcription systems Grants and Collaborations: Involved in EU-funded projects like i-Librarian and i-Publisher. Collaborates with institutions globally on NLP and corpus linguistics. Labs/Teams: Director of the NLP-Group@UAIC-FII and heads the DeLORo project team.
Dan Rosenberg serves as an Associate Professor in the Department of Automation and Information Technology at the Faculty of Electrical Engineering and Computer Science, Transilvania University of Brașov, Romania. His academic role integrates teaching with advanced research in automation and information systems within the university's engineering framework. His research spans Artificial Intelligence, Control Systems, Smart Buildings, and Photovoltaic Systems, with emphasis on applying computational intelligence to real-world engineering challenges. Key investigations include neural network applications for fire safety systems and reliability testing methodologies for renewable energy infrastructure, demonstrating strong interdisciplinary connections between computer science and sustainable engineering. Recent publications reveal a consistent focus on deep learning techniques for safety-critical systems and photovoltaic technology optimization. His 2022 work on fire detection using regularized CNNs bridges AI theory with practical building safety applications, while his 2016 photovoltaic testing research contributes to renewable energy reliability standards. Though specific student supervision details aren't enumerated, his research profile indicates active mentorship in automation and AI fields. His patented innovations in photovoltaic testing and medical implant technologies suggest significant grant-funded research activity and industry collaboration potential within Transilvania University's engineering ecosystem.
Mihai Mocanu is a Lecturer at the University of Craiova, affiliated with the Faculty of Automatic Control, Computers and Electronics. His work spans machine learning, educational data mining, and medical imaging technologies. Research Interests: He focuses on developing interpretable machine learning models, particularly using decision trees for educational data mining and GIS analysis. His work also includes designing e-learning systems with personalized recommendation workflows and enhancing engagement through data-driven approaches. Notable Contributions: Mihai has pioneered segmentation techniques for 3D medical imaging, created adaptive learning systems with stacked models, and explored social network impact on education. His research integrates pedagogical agents and usability evaluation frameworks in e-learning platforms.
Cristian Mihaescu is a Lecturer at the Department of Computer Science and Engineering (DCTI), University of Craiova, within the Faculty of Automatic Control, Computers and Electronics. He is actively involved in teaching and research related to machine learning, distributed systems, and educational data mining. Teaching: Data Structures and Algorithms, Parallel and Distributed Algorithms, Machine Learning, Distributed Systems Engineering Research Focus: Machine learning applications in education, social network analysis, and compiler optimization Technological Interests: Microservices, data mining, and intelligent system design
Sorin Anagoste is a Professor and Vice Dean for Academic Affairs at FABIZ, part of the Bucharest University of Economic Studies. His primary affiliation is with the Bucharest Business School (BBS), where he contributes to academic leadership and faculty governance. He holds a PhD and focuses on interdisciplinary research at the intersection of business strategy, technology, and innovation. His academic career spans over two decades, with a strong emphasis on advancing education and research in digital transformation, artificial intelligence, and entrepreneurship. Prior roles include leadership in mergers and acquisitions studies, transformational leadership research, and Lean Six Sigma methodologies. Research Interests: Artificial Intelligence applications in business decision-making Digital transformation strategies Entrepreneurship dynamics across generations Impact of AI on political and economic systems Knowledge dynamics in organizational contexts Recent work emphasizes the societal implications of AI, including election influence via LLMs, post-pandemic consumer behavior, and Romania's economic interdependencies through Leontief matrix analysis. He has authored over 35 articles on topics ranging from robotic process automation to sustainable development. Professional Activities: Academic leadership in business education reform Consultancy on digital strategy for enterprises Founder of BBS's strategic frameworks for chatbot implementation
Prof. Petru Adrian COTFAS holds a position as Professor in the Department of Electronic and Computers at the Faculty of Electrical Engineering and Computer Science, Technical University of Brașov (UNITBV). His work focuses on advancing renewable energy systems, hybrid energy technologies, and IoT-based monitoring solutions. He leads research on photovoltaic cell optimization, thermoelectric generator performance, and cybersecurity in smart energy systems. His contributions include developing virtual instrumentation frameworks (e.g., LabVIEW-based tools) and experimental setups like the RELab system for studying solar/wind energy dynamics. Research Interests: Characterization of renewable energy systems (hybrid photovoltaic-thermoelectric configurations) IoT integration for remote energy monitoring and control Metaheuristic algorithms for parameter extraction in solar cells Cybersecurity resilience for smart energy infrastructure Energy efficiency in industrial systems (e.g., AHU optimization) Key Contributions: Prof. COTFAS has pioneered studies on dust impact mitigation for solar panels, developed novel methods for concentrated solar power systems, and addressed cybersecurity vulnerabilities in IoT-enabled energy grids. His work bridges theoretical models (e.g., multi-junction solar cell theory) with practical implementations like FPGA-based remote laboratories. Over 60 peer-reviewed articles since 2016 showcase his interdisciplinary approach to energy sustainability and technological innovation.
Dr. Timenko Artur Valentynovych serves as Senior Lecturer at Zaporizhia National Technical University's Department of Computer Systems and Networks within the Faculty of Computer Science and Technologies. Holding a specialist degree in Computer Systems and Networks (2010), he maintains active roles in both teaching and research. His educational background includes graduation from Zaporizhia National Technical University in 2010 with specialization in Computer Systems and Networks. Professional development is evidenced through continuous research output and curriculum development activities. Research focuses on Internet of Things , computer networks , and neural networks , with particular emphasis on protocol verification, device interoperability, and embedded system optimization. Recent work explores semantic chatbots for IoT management, air quality monitoring systems, and MQTT protocol compatibility analysis. His methodology integrates formal verification techniques with practical hardware implementation. Publication trends from 2020-2024 reveal consistent contributions to IoT infrastructure (45%), network protocols (30%), and AI applications (25%). Key journals include Shipbuilding & Marine Infrastructure and Scientific Notes of Vernadsky University. Research demonstrates strong industry relevance with applications in smart homes, environmental monitoring, and critical systems. Teaching responsibilities encompass Python programming basics, computer network design, IoT fundamentals, and wireless technologies. His laboratory guidelines for Embedded Computer Systems and IoT disciplines reflect practical, hands-on pedagogy. Current projects involve developing automated temperature control systems and network anomaly detection using hybrid neural networks. Professional activities include active participation in Ukrainian academic conferences and international collaborations through ZNTU's research infrastructure. His work contributes to the university's strategic focus on digital innovation and sustainable technology development.
