Zlatkova Aleksandra is affiliated with the Faculty of Electrical Engineering and Information Technologies at Ss. Cyril and Methodius University in Skopje. Her research spans interdisciplinary domains including Machine Learning , Signal Processing , and Energy Systems . Key contributions in Power Quality analysis using Convolutional Neural Networks Expertise in Federated Learning for Short-Term Energy Forecasting Developed the UbiLAB Framework for remote laboratory environments Explored Wavelet Transforms in Medical Image Processing Her work also addresses Smart Grid Security through Temporal Convolutional Networks and investigates Honeybee Swarming with Acoustic Signal Processing . Recent publications emphasize Multi-Horizon Forecasting and Deep Learning applications in energy and medical domains.
Dr. Sergej Cvetkovski is an Associate Professor at the Institute for Security, Defence and Peace Studies, Faculty of Philosophy, Ss. Cyril and Methodius University. He serves as Chief of the Protection and Rescue Staff and leads the second cycle of Strategic and Defense Studies. His career spans roles such as Crisis Management expert (2001–2004), ARM of Macedonia (2002–2004), and academic positions since 2004. Education: Bachelor's in Defense (2001), Faculty of Philosophy Master's in Defense (2008), Faculty of Philosophy PhD in Crisis Management (2013), Institute for Security, Defence and Peace Research Interests: Dr. Cvetkovski focuses on civil defense, crisis management, civil-military cooperation, protection/rescue systems, nuclear safety, and comparative security frameworks. His work often addresses Balkan and European security challenges, including NATO strategies and humanitarian intervention ethics. Professional Engagement: He teaches courses such as Civil Crisis Management, Civil Protection, Regional Security, and Comparative Security Systems. Active in conferences and workshops in Macedonia and internationally, he contributes to defense policy reform and crisis management best practices. Advising & Grants: No listed advisees, but oversees institutional projects like the Protection and Rescue Staff and defense sector budgeting initiatives. Labs/Teams: Leads the Protection and Rescue Staff unit at the Faculty of Philosophy, focusing on urban security models and crisis response systems.
Katerina Angelevska - Najdeska is an academic researcher at St. Clement of Ohrid University - Bitola, specializing in tourism economics and marketing. With a doctoral thesis completed in 2009 on tourist resource management for sustainable tourism development in Macedonia, she has established herself as a prominent researcher in Balkan tourism studies. Her research spans sustainable tourism development, tourist resource valorization, marketing management in tourism, intercultural competence of tourism professionals, and insurance market analysis. She has extensively studied Macedonian tourism potential, particularly focusing on the Southwest Planning Region, spa tourism, and Ohrid's tourism offerings. Her work demonstrates how market mechanisms can be leveraged for effective tourism resource management and sustainable development. Analysis of her recent publications reveals a consistent focus on practical applications of tourism theory to Macedonian contexts, with increasing attention to wellness tourism, intercultural communication in tourism services, and the economic impacts of tourism development. Her research often employs interdisciplinary approaches, combining economics, marketing, and cultural studies perspectives. She has been actively involved in regional development projects, including the Study on the Tourism Potentials in the Southwest Planning Region (2013) and the Programme for the Development of the Southwest Planning Region (2010-2015), demonstrating her commitment to practical applications of academic research for regional economic development. Her collaborative work with colleagues across multiple institutions indicates strong networking within the Balkan academic community, particularly in tourism and economics research. While specific grant information isn't provided in the available materials, her sustained publication record and involvement in regional development projects suggest successful research funding acquisition.
Agron Çaushi is an Associate Professor at the Faculty of Business and Economics, South East European University, Tetovo, North Macedonia. With a PhD in Economic Sciences (2017) and an MSc in Information Systems (2007), his work bridges economic theory, information systems, and digital transformation. His career has focused on e-Government, business analytics, and AI applications in education and organizational efficiency. Education: PhD in Economic Sciences (2017), Master of Science in Information Systems (2007), Bachelor of Arts in Business Administration (2005) Research interests include the socio-economic impact of digital technologies, ERP systems, AI ethics in education, and sustainable development through digitalization. Recent publications analyze AI's role in higher education, robotics in renewable energy, and e-Government maturity models. His work combines empirical studies with comprehensive reviews, often collaborating with regional institutions. Publications span topics like ERP evolution , AI in education , cloud healthcare , and robotics , reflecting his interdisciplinary approach. Co-authored works frequently address policy implications and technological integration in public and private sectors.
Ordan Chukaliev is a Full Professor at the Department of Water and Erosion Protection within the Faculty of Agricultural Sciences and Food at Ss. Cyril and Methodius University in Skopje (UKIM). His research focuses on irrigation systems, climate change adaptation, and crop yield optimization in Mediterranean agroecosystems. Institute for the Environment Department of Water and Erosion Protection Expertise: Specializes in irrigation optimization, fertilization techniques, and water resource management. His work bridges agricultural engineering with climate science to improve crop productivity in arid regions. Research Trends: Recent publications emphasize machine learning applications for yield forecasting, climate change mitigation in sunflower cultivation, and irrigation efficiency in pepper and tomato crops. His studies span both field and greenhouse experiments. Professional Contact: Email: Ordan.Cukaliev@fznh.ukim.edu.mk | Institute: Faculty of Agricultural Sciences and Food, 3 16th Macedonian Brigade Street, Skopje, Macedonia
Prof. Dr. Pande Trajkov is a Full Professor at the Faculty of Forestry, Ss. Cyril and Methodius University in North Macedonia. With over three decades of experience since his 1988 graduation, he specializes in forest management, dendrometry, and multifunctional forest systems. He teaches courses including Forest Management , Dendometry , and Forest Inventory at both undergraduate and graduate levels. Education: PhD in Forestry (1997), MSc in Forestry (1992), BSc in Forestry (1988) from the Faculty of Forestry, Skopje His research focuses on forest productivity , silvicultural practices , and nature conservation in protected areas. Recent work explores machine learning applications in forest biomass estimation, elevation impacts on Macedonian pine stands, and coppice forest management challenges in Europe. Key trends in his publications include: Integration of remote sensing and AI for forest inventory Ecological dynamics of native species like Macedonian pine and sessile oak Policy analysis for nature conservation vs. forestry activities Sustainable management of coppice forests Forest road infrastructure optimization Administratively, he has served as Vice-Dean of the Faculty of Forestry (2001-2004, 2017-present) and contributed to EU agricultural policy adaptation frameworks.
Suzana Loshkovska, PhD , is a Full Professor at the Faculty of Computer Science and Engineering of Ss. Cyril and Methodius University in Skopje , Macedonia. Since 1992 she has held continuous academic appointments, interrupted only by a visiting-researcher stay at the Academy of Sciences of Lower Austria (1993–1994) where she designed a medical information system for Krems Hospital. Education : BSc (1989) and MSc (1992) in Computer Science and Automation, Faculty of Electrical Engineering, Skopje PhD (1995) in Technical Sciences, Technical University of Wien, Austria Research Interests span programming, visualization, human–computer interaction, virtual reality, medical imaging, and modelling/visualization of medical processes. Her work integrates advanced algorithmic techniques—such as hierarchical multi-label classification, support-vector machines, predictive clustering trees, and Bayesian networks—into practical medical and multimedia applications. Across more than one hundred peer-reviewed publications, her recent articles concentrate on content-based medical image retrieval , annotation of medical images , visual concept detection , and interactive medical systems . These contributions collectively advance computer-aided diagnosis, clinical decision support, and efficient management of large-scale medical data sets. Scientific Awards & Recognition : Member, Editorial Board, INFORMATICA (international journal, Slovenia) Projects & Funding : Principal investigator or participant in bilateral and EU-funded projects including SEE-ERA.NET Plus, TEMPUS DL@WEB, TEMPUS M.Sc. E-Learning, and multiple Macedonian Ministry of Science grants covering medical imaging, environmental modelling, distance learning, and electromagnetic-effects visualisation. While no specific research group or laboratory name is provided, her sustained involvement in national and international projects indicates active leadership within the university’s medical-informatics and multimedia-research community.
Prof. Dr. Andreja Naumoski is a full professor at the Faculty of Computer Science and Engineering (FCSE) at Ss. Cyril and Methodius University in Skopje. Since 2009, he has contributed to teaching and research, leading courses in intelligent information systems and serving as head of the master’s program in Eco-Informatics and the Laboratory for Eco-Informatics since 2024. Focus areas: machine learning, GIS applications, environmental data modeling Specialties: Smart IoT systems, ecological modeling, data visualization His research emphasizes intelligent decision support systems applied to environmental domains, integrating GIS with machine learning for dynamic process prediction. He participated in international projects (Interreg IPA, Tempus, FP6) and authored over 100 papers in prestigious venues.
Xhemal Zenuni is a Full Professor and current Dean at the Faculty of Contemporary Sciences and Technologies, South East European University (Tetovo, North Macedonia). His academic career spans multiple roles from IT Administration Assistant (2003-2004) to progressively senior positions including Young Assistant (2004-2006), Assistant (2006-2008), Assistant Professor (2013-2018), Associate Professor (2018-2023), and now Full Professor since 2023. Education: PhD in Computer Sciences (2006-2012, Technical University of Sofia), specialization in Computer Systems, Complexes and Networks Master of Sciences in Informatics (2004-2005, New Bulgarian University), specialization in Internet Software Technologies Bachelor of Sciences in Computer Sciences (2001-2003, SEEU) With expertise in Machine Learning , IoT , Cloud Computing , and Database Systems , his research focuses on applying AI/ML techniques across multiple domains. Recent work includes predictive modeling in education, hate speech detection for Albanian social media, smart agriculture systems, and microservices architecture migration. His publications demonstrate consistent engagement with modern computational challenges, particularly around low-resource language processing , smart city infrastructure , and educational technology . While serving as Dean and Vice-Dean, he has maintained active research output through collaborations with colleagues like Mentor Hamiti, Jaumin Ajdari, and Florije Ismaili.
Sadri Alija is a Full Professor in the Department of Mathematics and Statistics at the Faculty of Business and Economics, South East European University (SEEU), Tetovo, Macedonia. With over 15 years of academic experience, his work bridges applied mathematics, economics, and education technology. PhD in Applied Mathematics Sciences in Economics (SEEU, 2013) MSc in Mathematics (University of Tirana, 2006) BSc in Mathematics (University of Tirana, 2000) His research focuses on socio-economic analysis, educational performance modeling, and financial development in emerging markets. Recent publications explore: Machine learning applications for student performance prediction Impact of blended learning on satisfaction metrics Statistical analysis of demographic influences on academic staff productivity Financial risk modeling in transition economies As Vice-Dean for Undergraduate Studies (2010-2012), he contributed to academic administration in SEEU's Faculty of Business and Economics.
Агрон Чауши is an Associate Professor at the Faculty of Business and Economics of South East European University in Tetovo, North Macedonia. He holds a PhD in Economic Sciences with a specialization in Information Systems, a Master of Science in Information Systems from Indiana University, and a Bachelor of Arts in Business Administration from the same university. PhD: Economic Sciences (Information Systems), SEEU (2012-2017) MS: Information Systems, Indiana University (2006-2007) BA: Business Administration, SEEU (2001-2005) His research focuses on the intersection of information systems and economics, particularly e-Government maturity models, ERP system implementations, and machine learning applications in education and healthcare. Recent work explores AI ethics, digital organizational transformation, and renewable energy automation. Publications between 2016-2025 demonstrate consistent engagement with information systems, e-Government, and business analytics. Key article keywords include artificial intelligence, ERP systems, digitalization, and renewable energy technologies. Sub-fields span machine learning applications, data mining, and educational analytics. He teaches business and technology courses at SEEU, having held progressively senior roles from Junior Assistant (2005-2009) to current Associate Professor (2023-present). His professional experience includes systems analysis at Indiana University's Kelley School of Business and consulting at SEEU's Business Development Center.
Leyla Abazi-Bexheti is a Full Professor of Computer Sciences at the Faculty of Modern Sciences and Technologies, South East European University (SEEU) in Tetovo, Macedonia. She holds a Doctorate in Computer Science (2009) from SEEU, a Master's in Electrical Engineering (2006) from Ss. Cyril and Methodius University, and a Computer Science Engineering degree (2000) from the same institution. Her research focuses on e-learning systems, cybersecurity, open data governance, VR/AR integration in education, and gender disparities in computing. She has held leadership roles including Director of the PhD School (2019–present), Pro Rector for Academic Issues (2016–2018), Dean of Faculty (2014–2015), and Director of the eLearning Center (2010–2014). Her work spans 20+ peer-reviewed publications since 2016, emphasizing machine learning applications in safety analytics, VR/AR pedagogy, and policy-driven open data initiatives. She has co-authored studies on road accident prediction using web data and cyber efficacy in public platforms. Her research often intersects technology adoption challenges in Balkan educational systems. Abazi-Bexheti has led institutional reforms in academic governance, curriculum development, and digital transformation initiatives. She contributes to international conferences (MECO, MIPRO, ENTRENOVA) and collaborates with institutions across Europe on ICT education frameworks and gender equity in STEM fields.
Zamir Dika is a Full Professor at the Faculty of Modern Sciences and Technologies of the South East European University (SEEU), employed on a part-time basis. His research focuses on information systems, ERP implementation challenges in higher education, e-learning technologies, service quality management, and conceptual modeling frameworks. He has contributed to studies on educational leadership in North Macedonia, text-mining algorithms for financial prediction, and cloud computing architectures. His work frequently engages with institutional quality assurance frameworks and Bologna Process compliance. Key publications include analyses of ERP implementation factors (2018), comparative studies of COVID-19 datasets (2020), and frameworks for conceptual modeling (2016-2018). His research also extends to cloud reliability models (2017), banking e-service quality (2012), and web services for SMEs (2011). Award recognition details are not explicitly mentioned in the provided texts. His advising record is not listed here, though his publications suggest collaborative research with colleagues across disciplines. He has contributed to institutional projects such as the development of learning management systems (LMS) and academic planning modules at SEEU. His work bridges theoretical frameworks with practical applications in higher education technology, business process optimization, and digital transformation strategies. Current research trends emphasize sustainability in service quality paradigms and leveraging AI in financial predictive analytics.
Marija Kalendar is an Associate Professor at the Faculty of Electrical Engineering and Information Technologies (FEIT) of the Ss. Cyril and Methodius University of Skopje. She is affiliated with the Department of Computer Engineering and Informatics, where she contributes to research and teaching in computer science, AI, and network technologies. Her work spans machine learning applications, healthcare ethics in AI, IoT frameworks, FPGA implementations, and remote laboratory systems. Education: No explicit educational details provided in the text. Research Interests: Dr. Kalendar's research focuses on ethical AI (e.g., bias detection in medical datasets), federated learning for healthcare and IoT security, FPGA-based hardware designs for networking, and virtual laboratory frameworks. She also explores cryptocurrency price prediction using ML and LoRaWAN IoT limitations. Key Article Trends: Her recent work emphasizes AI ethics (racial bias in clinical AI), cybersecurity in IoT (federated learning for intrusion detection), and remote education infrastructure (UbiLAB framework). She also studies vital signs' role in bias and 5G network frameworks for mission-critical data. Grants/Advising: No specific grants or advising details provided. However, her involvement in collaborative projects (e.g., UbiLAB, federated learning frameworks) suggests interdisciplinary teamwork. Labs/Teams: Her affiliation with the Department of Computer Engineering and Informatics implies collaboration with FEIT's research institutes, though specific lab names are not mentioned.
Mile Stankovski is a full Professor at the Department of Automation and Systems Engineering within the Faculty of Electrical Engineering and Information Technologies (FEIT) at Ss. Cyril and Methodius University of Skopje. His research focuses on control systems engineering, industrial automation, robotics, and the integration of AI techniques into industrial processes. He has contributed extensively to the development of fuzzy logic and neural network-based control systems for complex thermal processes, industrial furnaces, and robotic systems. Dr. Stankovski's academic career spans over three decades, with notable work in networked control systems, cybersecurity for industrial automation, and model predictive control strategies. He has spearheaded projects on energy-efficient industrial furnace control, path planning for multi-agent robotic systems, and secure communication protocols for cyber-physical systems. His pedagogical efforts include advancing microelectronics curricula and integrating open educational resources in cloud-based learning environments. Research Interests: Cyber-physical systems, industrial automation, robotics, fuzzy logic, neural networks, and control system security. Key Contributions: Pioneered hybrid model predictive control for industrial furnaces, developed algorithms for noise-robust secure communication, and designed educational tools for microelectronics and PLC training. Awards: No explicitly stated scientific awards, though his extensive publication record reflects recognition in the field. His work bridges theoretical control systems research with practical industrial applications, emphasizing sustainability and safety in automation technologies. Current projects include AI-driven model management for industrial AI systems and optimization of heliostat field control in renewable energy systems.
