Giuseppe Di Gironimo | Remote Handling | Excellence in Research Award

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Prof. Giuseppe Di Gironimo | Remote Handling | Excellence in Research Award

Professor | University of Naples Federico II | Italy

Prof. Giuseppe Di Gironimo is a multidisciplinary researcher specializing in advanced mechanical design, digital engineering, and remote-handling technologies for large-scale scientific and industrial systems, with a strong focus on fusion energy devices such as DTT, ITER, and RFX-Mod2. With over 201 publications, 3,031 citations, and an h-index of 28, he has established a significant international presence in the fields of CAD/CAE modeling, electromechanical system analysis, ICRH/ICRF antenna design, and virtual alignment methodologies. His work integrates cloud-based engineering, digital twins, immersive VR training, and under-actuated robotic systems to improve maintainability, safety, and operational efficiency in high-complexity environments. Collaborating with nearly 1,000 co-authors across global research laboratories, universities, and industry partners, he contributes to multidisciplinary advancements in fusion energy development, aerospace manufacturing, and human–machine interaction. His research demonstrates both academic depth and industrial relevance, supporting innovation in automated assembly, virtual design reviews, and remote operations for next-generation scientific infrastructures.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Grazioso, S., Di Gironimo, G., & Siciliano, B. (2019). A geometrically exact model for soft continuum robots: The finite element deformation space formulation. Soft Robotics, 6(6), 790–811.
Cited by: 253

2. Del Nevo, A., Arena, P., Caruso, G., Chiovaro, P., Di Maio, P. A., Eboli, M., … (2019). Recent progress in developing a feasible and integrated conceptual design of the WCLL BB in EUROfusion project. Fusion Engineering and Design, 146, 1805–1809.
Cited by: 186

3. Singh, G., Akrigg, S., Di Maio, M., Fontana, V., Alitappeh, R. J., Khan, S., Saha, S., … (2022). ROAD: The road event awareness dataset for autonomous driving. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(1), 1036–1054.
Cited by: 159

4. Del Nevo, A., Martelli, E., Agostini, P., Arena, P., Bongiovì, G., Caruso, G., … (2017). WCLL breeding blanket design and integration for DEMO 2015: Status and perspectives. Fusion Engineering and Design, 124, 682–686.
Cited by: 155

5. You, J. H., Mazzone, G., Visca, E., Greuner, H., Fursdon, M., Addab, Y., … (2022). Divertor of the European DEMO: Engineering and technologies for power exhaust. Fusion Engineering and Design, 175, 113010.
Cited by: 151

Prof. Giuseppe Di Gironimo work accelerates progress toward reliable fusion energy systems and next-generation digital engineering, strengthening the technological foundations for future clean-energy infrastructures. Through innovations in virtual design, remote handling, and electromechanical systems, he contributes directly to safer, more efficient, and globally scalable industrial and scientific solutions.

Róbert Bata | Scientific Computing | Best Researcher Award

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Mr. Róbert Bata | Scientific Computing | Best Researcher Award

Assistant Lecturer | University of Debrecen | Hungary

Mr. Róbert Bata is an emerging public health researcher whose work focuses on social epidemiology, gender-related health disparities, and the behavioral and structural determinants of population health. With 5 peer-reviewed publications, 6 citations, and an h-index of 2, he has contributed evidence-based insights into how social perceptions, intimate partner violence, and sexual and reproductive behaviors shape health outcomes, particularly among women in low- and middle-income settings. His research integrates quantitative methods with socio-behavioral analysis to examine sensitive but globally significant issues such as sexually transmitted infections and violence-related health vulnerabilities. Collaborating with 16 co-authors across multidisciplinary fields—including public health, sociology, and international development—he works to illuminate the mechanisms through which social inequality influences individual and community health. Bata’s scholarship, exemplified by his recent open-access study on sexual perceptions, behavior, and intimate partner violence among Filipino women, seeks to inform health policy, strengthen gender-responsive interventions, and support equitable, culturally grounded public health strategies. His growing body of work demonstrates a commitment to advancing global understanding of the social determinants of health and contributing to more inclusive, evidence-driven approaches to improving health outcomes in vulnerable populations worldwide.

Profiles: Scopus | ORCID

Featured Publication

1. Bata, R. (2025). Association of sexual perceptions, behavior, and intimate partner violence with sexually transmitted infection (STI) among Filipino women. BMC Public Health, 25, Article .

Mr. Róbert Bata’s research advances global public health by generating evidence that strengthens women’s health, safety, and autonomy, particularly in marginalized communities. His work contributes to policy-relevant knowledge that supports equitable health systems and promotes social resilience through informed, data-driven interventions.

Zongran Dong | Computer Aided Design | Best Researcher Award

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Assoc. Prof. Dr. Zongran Dong | Computer Aided Design | Best Researcher Award

Teacher | Dalian University of Foreign Languages | China

Assoc. Prof. Dr. Zongran Dong, affiliated with Dalian Neusoft University of Information, China, is an expert in computational optimization and heuristic algorithms, with a focus on practical applications in logistics and industrial engineering. His research emphasizes the development and refinement of metaheuristic methods, including tabu search, to address complex operational challenges such as container-loading optimization, demonstrating both algorithmic innovation and real-world applicability. Despite a concise publication record of 3 peer-reviewed works, his research has garnered 58 citations and of 2 h-index, reflecting recognition and engagement within the scholarly community. Collaborating with six co-authors, Dong has contributed to interdisciplinary knowledge exchange that bridges computer science, applied mathematics, and engineering, enhancing the robustness and impact of his work. His contributions hold relevance for industrial practice, supporting efficiency, resource optimization, and sustainability in logistics and supply-chain systems. Overall, Dong’s research embodies a targeted, application-driven approach that advances intelligent optimization methods and demonstrates measurable influence on both academic research and operational industries worldwide.

Profiles: Scopus | ORCID

Featured Publication

1. A tabu search algorithm for container loading based on homogeneous blocks. (2011). Gaojishu Tongxin
Cited by: 1

Assoc. Prof. Dr. Zongran Dong’s research advances intelligent optimization techniques that enhance efficiency in global logistics and industrial operations. By improving algorithmic performance in container-loading and related systems, his work supports more sustainable, cost-effective, and data-driven decision-making across industries.

Saeid Barshandeh | Optimization | Best Researcher Award

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Dr. Saeid Barshandeh | Optimization | Best Researcher Award

Instructor-Researcher | Afagh Higher Education Institute | Iran

Dr. Saeid Barshandeh is a computational intelligence researcher specializing in metaheuristic optimization, machine learning, and advanced algorithm design, with a research portfolio comprising 14 scientific publications, 12 h-index and over 885 citations. His work focuses on developing innovative, nature-inspired optimization techniques capable of addressing complex, nonlinear problems prevalent in engineering, data science, and industrial systems. A key achievement is the development of the Puma Optimizer (PO), a novel metaheuristic algorithm that has rapidly gained global academic attention and demonstrates his expertise in algorithmic modeling, performance tuning, and machine-learning integration. His research activities are enriched by collaborations with more than 30 co-authors, reflecting active engagement in interdisciplinary networks spanning intelligent systems, evolutionary computation, and data-driven decision-making. Collectively, his contributions enhance the efficiency, scalability, and applicability of optimization methodologies across diverse domains such as energy management, automation, predictive analytics, and industrial process optimization. Through impactful publications and growing scholarly influence, Dr. Barshandeh advances the theoretical and practical foundations of intelligent optimization, contributing to technological innovation and the broader scientific community.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Abdollahzadeh, B., Khodadadi, N., Barshandeh, S., Trojovský, P., & … (2024). Puma optimizer (PO): A novel metaheuristic optimization algorithm and its application in machine learning. Cluster Computing, 27(4), 5235–5283.
Cited by: 661

2. Barshandeh, S., & Haghzadeh, M. (2021). A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems. Engineering with Computers, 37(4), 3079–3122.
Cited by: 129

3. Gharehchopogh, F. S., Abdollahzadeh, B., Barshandeh, S., & Arasteh, B. (2023). A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT. Internet of Things, 24, 100952.
Cited by: 128

4. Gharehchopogh, F. S., Nadimi-Shahraki, M. H., Barshandeh, S., & … (2023). Cqffa: A chaotic quasi-oppositional farmland fertility algorithm for solving engineering optimization problems. Journal of Bionic Engineering, 20(1), 158–183.
Cited by: 89

5. Barshandeh, S., Piri, F., & Sangani, S. R. (2022). HMPA: An innovative hybrid multi-population algorithm based on artificial ecosystem-based and Harris Hawks optimization algorithms for engineering problems. Engineering with Computers, 38(2), 1581–1625.
Cited by: 78

Dr. Barshandeh’s research advances the science of optimization by providing robust, efficient algorithms that strengthen machine-learning performance and industrial decision systems. His work contributes to global technological innovation, enabling smarter, more adaptive solutions for complex societal and engineering challenges.

Davoud Shahgholian-Ghahfarokhi | Neural Network | Best Researcher Award

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Dr. Davoud Shahgholian-Ghahfarokhi | Neural Network | Best Researcher Award

Senior Researcher | Tarbiat Modares University | Iran

Dr. Davoud Shahgholian-Ghahfarokhi is a researcher affiliated with Tarbiat Modares University whose work spans advanced structural engineering, materials mechanics, and computational modeling, with a focus on improving the performance, durability, and safety of modern engineering systems. With 20 peer-reviewed publications, 15 h-index and over 792 citations, his research demonstrates sustained scholarly influence and recognition within the global engineering community. His expertise encompasses mechanics-based structural design, vibration analysis, composite and sandwich structures, offshore pipeline integrity, auxetic and graded materials, and artificial-intelligence-assisted engineering assessment. Across his body of work, he has contributed analytical, numerical, and hybrid computational frameworks for understanding complex structural behaviors under dynamic and environmental loads. Notable contributions include the formulation of vibration models for sandwich folded plates with auxetic honeycomb cores and FG-GPLRC coatings, advancing next-generation lightweight, high-performance structures. Additionally, his research on corrosion-induced degradation of offshore pipelines—combining code-based methods, finite-element simulations, and neural-network prediction—provides industry-relevant tools for failure assessment and risk mitigation. Dr. Shahgholian-Ghahfarokhi has collaborated with at least 25 co-authors, reflecting a strong record of interdisciplinary and international engagement. His work supports structural reliability, materials innovation, and infrastructure resilience, offering direct societal benefits in safety-critical sectors such as offshore energy, transportation, and advanced manufacturing. Collectively, his research contributes to a more robust scientific understanding of complex structural systems while fostering emerging engineering solutions that balance performance, sustainability, and safety.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Shahgholian-Ghahfarokhi, D., Safarpour, M., & Rahimi, A. (2021). Torsional buckling analyses of functionally graded porous nanocomposite cylindrical shells reinforced with graphene platelets (GPLs). Mechanics Based Design of Structures and Machines, 49(1), 81–102.
Cited by: 119

2. Shahgholian, D., Safarpour, M., Rahimi, A. R., & Alibeigloo, A. (2020). Buckling analyses of functionally graded graphene-reinforced porous cylindrical shell using the Rayleigh–Ritz method. Acta Mechanica, 231(5), 1887–1902.
Cited by: 102

3. Shahgholian-Ghahfarokhi, D., & Rahimi, G. (2018). Buckling load prediction of grid-stiffened composite cylindrical shells using the vibration correlation technique. Composites Science and Technology, 167, 470–481.
Cited by: 81

4. Khodadadi, A., Liaghat, G., Taherzadeh-Fard, A., … (2021). Impact characteristics of soft composites using shear thickening fluid and natural rubber – A review of current status. Composite Structures, 271, Article 114092.
Cited by: 80

5. Ghahfarokhi, D. S., & Rahimi, G. (2018). An analytical approach for global buckling of composite sandwich cylindrical shells with lattice cores. International Journal of Solids and Structures, 146, 69–79.
Cited by: 77

Dr. Shahgholian-Ghahfarokhi’s research advances the scientific foundations and practical tools needed to design safer, lighter, and more resilient engineering structures. By integrating novel materials, computational intelligence, and rigorous mechanics, his work contributes to global innovation in sustainable infrastructure, industrial reliability, and engineering risk reduction.

Vasuk Gautam | Bioinformatics | Best Researcher Award

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Dr. Vasuk Gautam | Bioinformatics | Best Researcher Award

Sr.Scientist | Norton Research Institute | United States

Dr. Vasuk Gautam is an emerging researcher whose work spans metabolomics, biomarker discovery, and computational methods for enhancing analytical confidence in high-throughput biological studies. With a record of 24 peer-reviewed publications, 13 h-index and over 3,102 citations, Gautam has established a strong early-career footprint marked by methodological innovation and extensive interdisciplinary collaboration. His contributions focus particularly on developing frameworks for improving metabolite identification accuracy—an essential challenge in metabolomics that directly influences the reliability of biomedical and environmental research. Notably, his recent work introducing the concept of “Identification Probability” provides a transferable, automated metric for evaluating identification confidence, positioning it as a potentially transformative tool for large-scale metabolomic pipelines. In parallel, Gautam has contributed significantly to the development of MarkerDB 2.0, a comprehensive biomarker database that integrates molecular, clinical, and contextual information to support precision medicine, translational research, and global health initiatives. His scholarship reflects a blend of computational rigor, domain expertise, and a commitment to open-access scientific resources. Gautam’s collaborations include partnerships with over 180 co-authors, underscoring his active engagement with diverse research groups and his ability to contribute meaningfully to multi-institutional projects. This collaborative network spans biochemistry, bioinformatics, systems biology, and clinical sciences, highlighting the broad applicability and relevance of his expertise. Through both his methodological contributions and his involvement in global data-resource efforts, Gautam’s work supports reproducibility, accessibility, and evidence-based discovery in molecular life sciences. His growing citation impact and participation in influential open-access initiatives demonstrate both scientific merit and societal relevance, particularly in areas related to disease diagnostics, personalized healthcare, and data-driven research infrastructures.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Wishart, D. S., Guo, A. C., Oler, E., Wang, F., Anjum, A., Peters, H., Dizon, R., … (2022). HMDB 5.0: The human metabolome database for 2022. Nucleic Acids Research, 50(D1), D622–D631.

Cited by: 2116

2. Knox, C., Wilson, M., Klinger, C. M., Franklin, M., Oler, E., Wilson, A., Pon, A., Cox, J., … (2024). DrugBank 6.0: The DrugBank knowledgebase for 2024. Nucleic Acids Research, 52(D1), D1265–D1275.

Cited by: 1112

3. Wishart, D. S., Han, S., Saha, S., Oler, E., Peters, H., Grant, J. R., Stothard, P., … (2023). PHASTEST: Faster than PHASTER, better than PHAST. Nucleic Acids Research, 51(W1), W443–W450.

Cited by: 394

4. Wishart, D. S., Tian, S., Allen, D., Oler, E., Peters, H., Lui, V. W., Gautam, V., … (2022). BioTransformer 3.0: A web server for accurately predicting metabolic transformation products. Nucleic Acids Research, 50(W1), W115–W123.

Cited by: 160

5. Wang, F., Allen, D., Tian, S., Oler, E., Gautam, V., Greiner, R., Metz, T. O., … (2022). CFM-ID 4.0: A web server for accurate MS-based metabolite identification. Nucleic Acids Research, 50(W1), W165–W174.

Cited by: 115

Dr. Vasuk Gautam’s work advances the reliability and scalability of metabolomic and biomarker research, enabling more accurate diagnostics and deeper biological insight. By developing robust identification metrics and contributing to global data resources, he helps accelerate scientific discovery, support precision medicine, and enhance evidence-based decision-making across research, healthcare, and industry.

Xingxing You | Intelligent control | Editorial Board Member

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Assist. Prof. Dr. Xingxing You | Intelligent control | Editorial Board Member

Assistant Professor | Sichuan University | China

Assist. Prof. Dr. Xingxing You is a developing researcher affiliated with Sichuan University, China, whose work spans advanced signal processing, intelligent control, and underwater imaging technologies. With 26 scientific publications, h-index 7and over 408 citations, the author demonstrates an emerging yet steadily growing influence in these fields. His research contributions include multi-level feature fusion strategies for perception-driven underwater image enhancement, advancing the reliability of visual sensing in complex aquatic environments, as well as novel critic-only self-learning optimal control methods for continuum robots operating under unknown disturbances, integrating extended state observer frameworks to elevate robustness and adaptability. These works reflect a broader expertise in machine learning–guided optimization, sensor fusion, and nonlinear dynamical systems, addressing real-world problems where conventional modeling is insufficient. Collaboration is a key dimension of his academic trajectory, with 55 co-authors across disciplines, indicating strong engagement within interdisciplinary research networks and an ability to participate effectively in multi-institutional scientific efforts. His research outcomes demonstrate relevance not only to academic communities working on robotics, automation, and digital signal processing, but also to domains such as marine engineering, environmental monitoring, and intelligent manufacturing. By focusing on interpretable enhancements, computational efficiency, and real-time control, his contributions help bridge theoretical advances and applied technological innovation. Overall, Xingxing You’s scholarly record showcases growing expertise, collaborative capacity, and a commitment to addressing technically challenging problems with practical societal implications.

Profiles: Scopus | ORCID

Featured Publications

1. Perception-driven underwater image enhancement via multi-level feature fusion. (2026). Digital Signal Processing: A Review Journal.

2. Critic-only based self learning optimal control for continuum robots with unknown disturbances via extended state observer. (2025). Nonlinear Dynamics.

Assist. Prof. Dr. Xingxing You’s work advances intelligent sensing and robust control systems, enabling more reliable robotic and imaging technologies in uncertain environments. His research contributes to global innovation by strengthening the scientific foundation for autonomous systems and enhancing their applications in marine exploration, environmental protection, and advanced robotics.

Béchir Béjaoui | Bioinformatics | Editorial Board Member

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Prof. Béchir Béjaoui | Bioinformatics | Editorial Board Member

Researcher | National Institute of Marine Sciences and Technologies | Tunisia

Prof. Béchir Béjaoui is a distinguished marine and environmental scientist affiliated with the National Institute of Marine Sciences and Technologies (INSTM) in Carthage, Tunisia. His research primarily focuses on coastal and marine ecosystem dynamics, climate change impacts, and the application of advanced modeling and machine learning techniques to assess and manage aquatic environments. Over his career, Dr. Béjaoui has authored 34 scientific publications, collectively cited more than 1,130 times across 954 documents, reflecting his strong academic influence and the global relevance of his research. His work integrates remote sensing, numerical modeling, and ecological indicators to evaluate trophic states, water quality, and biodiversity in sensitive environments, such as the Ichkeul Lake Ramsar sanctuary—a UNESCO biosphere reserve and a critical wetland ecosystem in North Africa. Dr. Béjaoui’s studies, including the development of innovative models such as the TRIX-XGBoost Trophic Model and data-driven approaches for forecasting environmental change, provide valuable insights into sustainable wetland management under anthropogenic and climatic pressures. With over 180 international collaborators, his research reflects a strong commitment to multidisciplinary and cross-institutional cooperation, enhancing the global understanding of marine system resilience. His contributions extend beyond academia to inform environmental policy, conservation planning, and adaptive management strategies, bridging the gap between scientific research and socio-environmental decision-making. Through his sustained scholarly output and leadership in marine ecosystem modeling, Dr. Béjaoui continues to play a pivotal role in advancing data-driven sustainability solutions in the Mediterranean and beyond.

Profile: Scopus

Featured Publications

1. Béjaoui, B., … (2025). TRIX-XGBoost Trophic Model for assessing the trophic status of Ichkeul Lake, a Ramsar sanctuary in Northern Tunisia. Marine Pollution Bulletin.

2. Béjaoui, B., … (2025). Remote sensing and numerical modeling to assess the drought in Ichkeul Lake, a RAMSAR wetland and UNESCO biosphere reserve, under climate change. Regional Studies in Marine Science.

3. Béjaoui, B., … (2025, Conference Paper). Machine learning techniques for forecasting the effect of climate change and anthropogenic pressures on coastal wetlands (Ichkeul Lake, Ramsar site).

Prof. Béjaoui’s work drives innovation in environmental modeling, offering scientifically grounded tools to safeguard fragile aquatic ecosystems against climate and human-induced stressors. His research vision promotes sustainable management of marine and wetland resources, contributing to global efforts toward ecological resilience, climate adaptation, and sustainable development.

Mohammad Abuamsha | FinTech | Best Researcher Award

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Assoc. Prof. Dr. Mohammad Abuamsha | FinTech | Best Researcher Award

Associate Professor | Palestine Technical University | Palestine

Assoc. Prof. Dr. Mohammad Kamal Abuamsha, affiliated with Palestine Technical University – Kadoorie, is an emerging scholar whose research lies at the intersection of economics, financial sustainability, and the informal or shadow economy, with a particular focus on the socioeconomic dynamics of developing regions such as Palestine. With 8 peer-reviewed publications and 28 citations, his academic contributions demonstrate growing recognition in the international research community. His work explores critical themes including financial resilience, macroeconomic stability, fiscal policy, and the interaction between economic informality and sustainable development. Through rigorous quantitative and econometric analyses, Dr. Abuamsha’s studies provide empirical insights into how informal economic activities influence public finance, growth trajectories, and policy formulation in constrained or transitional economies. His recent publication, “Shadow Economy–Financial Sustainability Nexus: The Case of Palestine” (Journal of Economic Studies, 2024), represents a key contribution to understanding financial sustainability in the context of structural economic challenges. Collaborating with multidisciplinary teams across regional and international institutions, Dr. Abuamsha integrates economic theory with applied policy research, enhancing the evidence base for sustainable economic governance. His modest yet impactful publication record, coupled with a developing citation profile (h-index: 4), underscores his growing influence in the fields of development economics and financial policy. Beyond academia, his research supports informed decision-making for governments, development agencies, and financial institutions working to enhance fiscal transparency and resilience in emerging markets. Collectively, Dr. Abuamsha’s scholarly endeavors reflect a commitment to advancing data-driven, inclusive, and sustainable economic systems within and beyond the Palestinian context.

Profiles: Scopus | ORCID

Featured Publication

1. Abuamsha, M. K., & Hattab, L. M. (2023). Shadow economy–financial sustainability nexus: the case of Palestine. Journal of Economic Studies, 51(2), 375–393.
Cited by: 8

Assoc. Prof. Dr. Abuamsha’s work advances global understanding of the interplay between shadow economies and financial sustainability, offering evidence-based pathways to strengthen economic resilience in developing regions. His vision centers on empowering societies through sustainable fiscal policies that bridge the gap between informal activity and formal economic growth.

Leonidas Anthopoulos | Smart City | Best Researcher Award

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Prof. Leonidas Anthopoulos | Smart City | Best Researcher Award

Professor | University of Thessaly | Greece

Prof. Leonidas G. Anthopoulos of the University of Thessaly, Greece, is an internationally recognized scholar in the domains of Smart Cities, Digital Transformation, and Emerging Technologies such as Artificial Intelligence, the Internet of Things (IoT), and the Metaverse. With a prolific academic record of 129 publications, 27 h-index and over 2,992 citations, he demonstrates sustained research excellence and global influence in the interdisciplinary field of urban innovation, digital governance, and technology standardization. His research bridges the gap between information systems, urban management, and policy-making, providing actionable frameworks for sustainable and citizen-centric digital ecosystems. Professor Anthopoulos has played a leading role in developing standardization strategies for smart cities at national and international levels, including contributions to the ITU Metaverse Focus Group, where he co-authored the seminal work “Toward a Standardized Metaverse Definition.” His extensive collaborations with 62 co-authors reflect strong interdisciplinary engagement across academia, government, and industry, enhancing the global dialogue on responsible, ethical, and inclusive digital transformation. His scholarship encompasses critical analyses of AI governance, smart city interoperability, and data-driven urban resilience, addressing contemporary challenges such as sustainability, digital equity, and crisis management. In addition to his academic achievements, Professor Anthopoulos’ leadership in conferences such as WebAndTheCity and contributions to open-access research reinforce his commitment to democratizing knowledge and fostering innovation for public good. His work has not only shaped academic discourse but has also informed policy frameworks and strategic planning for smart and resilient cities worldwide, emphasizing technology’s social and economic impact in urban contexts.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Anthopoulos, L., Reddick, C. G., Giannakidou, I., & Mavridis, N. (2016). Why e-government projects fail? An analysis of the Healthcare.gov website. Government Information Quarterly, 33(1), 161–173.
Cited by: 606

2. Anthopoulos, L. (2017). Smart utopia VS smart reality: Learning by experience from 10 smart city cases. Cities, 63, 128–148.
Cited by: 514

3. Anthopoulos, L. G. (2015). Understanding the smart city domain: A literature review. In Transforming city governments for successful smart cities (pp. 9–21).
Cited by :497

4. Anthopoulos, L. G. (2017). Understanding smart cities: A tool for smart government or an industrial trick? Springer International Publishing, 22, 293.
Cited by: 477

5. Anthopoulos, L., Janssen, M., & Weerakkody, V. (2018). A Unified Smart City Model (USCM) for smart city conceptualization and benchmarking. In E-Planning and collaboration: Concepts, methodologies, tools.
Cited by: 381

Professor Anthopoulos’ pioneering work advances the global transition toward intelligent, ethical, and sustainable digital societies, where technology serves humanity and governance aligns with social responsibility. His vision promotes the creation of standardized, inclusive, and human-centered smart ecosystems that drive innovation, improve quality of life, and contribute to the digital future of cities worldwide.