Kyeong Kang | Computer Science and Artificial Intelligence | Innovative Research Award

Innovative Research Award

Kyeong Kang
University of Technology Sydney, Australia

Kyeong Kang
Affiliation University of Technology Sydney
Country Australia
Google Scholar ID 5-h0TvcAAAAJ
Documents 116
Citations 1770
h-index 24
Subject Area Computer Science and Artificial Intelligence
Event International Research Awards
ORCID 0000-0003-4252-9802

The Innovative Research Award recognizes sustained scholarly achievement and research innovation demonstrated through scientific publications, academic influence, and contributions to the advancement of knowledge. Kyeong Kang of the University of Technology Sydney has established a research profile in Computer Science and Artificial Intelligence through peer-reviewed publications, scholarly collaboration, and measurable citation impact.[1] The recognition aligns with the objectives of the International Research Awards, which acknowledge researchers whose work supports innovation, academic excellence, and interdisciplinary development.[4]

Abstract

Kyeong Kang has developed an academic record characterized by peer-reviewed research, interdisciplinary collaboration, and contributions to Computer Science and Artificial Intelligence. Publication output, citation performance, and scholarly visibility indicate sustained engagement with contemporary research topics and international academic communication.[1][2]

Keywords

Artificial Intelligence, Computer Science, Machine Learning, Intelligent Systems, Data Analytics, Academic Research

Introduction

Research in Artificial Intelligence and Computer Science continues to influence scientific discovery, industrial innovation, and digital transformation. Academic contributions within these disciplines are evaluated using publication quality, citation impact, collaboration networks, and research relevance. Kyeong Kang’s scholarly record reflects active participation in these areas through internationally disseminated research outputs.[1]

Research Profile

The research profile includes 116 indexed scholarly documents, approximately 1,770 citations, and an h-index of 24. These bibliometric indicators demonstrate consistent publication activity and measurable academic influence across Computer Science and Artificial Intelligence research domains.[1]

Research Contributions

The research portfolio encompasses investigations in intelligent computing, artificial intelligence methodologies, computational modelling, and advanced software systems. Contributions have supported the development of scalable computational approaches, improved analytical methodologies, and interdisciplinary applications that connect theoretical computer science with practical technological solutions.[2][3]

Publications

Published work has appeared through peer-reviewed scholarly venues and has contributed to ongoing developments within Artificial Intelligence and Computer Science. Research dissemination through indexed journals and conference proceedings has increased scholarly visibility while supporting knowledge exchange across the international research community.[1][2]

Research Impact

Bibliometric indicators provide evidence of scholarly influence through citation activity, publication productivity, and sustained engagement with the research community. Such metrics are commonly used alongside qualitative assessment when evaluating academic achievement and research excellence.[1]

Award Suitability

Based on documented scholarly productivity, citation performance, institutional affiliation, and continued contributions to Computer Science and Artificial Intelligence, Kyeong Kang demonstrates characteristics consistent with the objectives of the Innovative Research Award. Recognition acknowledges measurable academic achievement, research dissemination, and sustained commitment to scientific advancement.[4]

Conclusion

Kyeong Kang’s academic profile illustrates sustained research productivity, recognized scholarly impact, and continued participation in the advancement of Computer Science and Artificial Intelligence. The available bibliometric indicators and institutional research activities support consideration for academic recognition within the International Research Awards framework.[1][4]

References

  1. Google Scholar. (2026). Scholar profile: Kyeong Kang.
    https://scholar.google.com/citations?hl=en&user=5-h0TvcAAAAJ
  2. ORCID. (2026). Kyeong Kang ORCID Record.
    https://orcid.org/0000-0003-4252-9802
  3. Kyeong Kang (2026). Research Output.
    https://profiles.uts.edu.au/Kyeong.Kang/publications
  4. International Research Awards. (2026). International Research Awards Official Website.
    https://researchawards.net/

Luciano Alessandro Ipsaro Palesi | Computer Science | Research Excellence Award

Research Excellence Award

Luciano Alessandro Ipsaro Palesi
University of Florence, Italy

Luciano Alessandro Ipsaro Palesi
Affiliation University of Florence
Country Italy
Scopus ID 57226812823
Documents 24
Citations 282
h-index 9
Subject Area Computer Science
Event International Research Awards
ORCID 0000-0001-8992-2084

Luciano Alessandro Ipsaro Palesi is a researcher affiliated with the University of Florence whose scholarly activities focus on computer science, artificial intelligence, smart cities, digital twins, intelligent transportation systems, and Internet of Things applications. His publication record demonstrates consistent contributions to data-driven urban intelligence and decision-support technologies. His research profile reflects interdisciplinary collaboration and sustained engagement with emerging computational methodologies.[1]

Abstract

This article summarizes the academic profile and research accomplishments of Luciano Alessandro Ipsaro Palesi. His work emphasizes intelligent mobility, explainable artificial intelligence, digital twin infrastructures, and smart city technologies. Through peer-reviewed publications and collaborative projects, he has contributed to practical solutions addressing urban planning, transportation optimization, and data-centric decision support systems.[2]

Keywords

Artificial Intelligence, Explainable AI, Smart Cities, Digital Twins, Intelligent Transportation Systems, Internet of Things, Deep Learning, Urban Mobility Analytics, Decision Support Systems, Data-Driven Computing.

Introduction

Modern computer science increasingly intersects with urban intelligence and connected infrastructures. Luciano Alessandro Ipsaro Palesi has participated in research addressing these evolving challenges through innovative computational models and scalable architectures. His publications highlight the integration of artificial intelligence with real-world mobility and smart city environments, creating measurable benefits for public services and urban sustainability.[3]

Research Profile

Affiliated with the University of Florence, Palesi has developed a research portfolio spanning digital twins, machine learning, mobility analytics, and Internet of Things ecosystems. His publication metrics include 24 indexed documents, 282 citations, and an h-index of 9. These indicators demonstrate active scholarly engagement and growing influence within applied computer science research communities.[1]

Research Contributions

His contributions include AI-driven traffic optimization, privacy-preserving mobility analysis, digital twin frameworks, and explainable artificial intelligence applications. Research outputs have explored predictive transportation models, public mobility demand matching, smart parking solutions, and urban environmental analytics. These studies support evidence-based decision making for municipalities and intelligent service platforms.[4]

Publications

Recent publications include studies on human-centered artificial intelligence, dynamic mobility demand matching, traffic signal optimization, digital twin architectures, and explainable AI methodologies. His work appears in recognized venues such as IEEE Access, Expert Systems with Applications, Computer Networks, Applied Soft Computing, and Big Data and Cognitive Computing. These publications collectively illustrate a consistent focus on intelligent systems and urban innovation.[5]

Research Impact

The practical orientation of his research has contributed to advancements in mobility management, smart infrastructure monitoring, and AI-enabled public services. Citation activity and collaborations across interdisciplinary teams indicate the relevance of his work within academic and applied settings. His studies support scalable solutions for contemporary urban and technological challenges.[2]

Award Suitability

The International Research Awards recognize individuals demonstrating sustained scholarly achievement and meaningful scientific contributions. Palesi’s publication record, citation performance, and involvement in advanced computational research align with these objectives. His interdisciplinary approach and engagement with emerging technologies support his suitability for recognition within international academic award programs.

Conclusion

Luciano Alessandro Ipsaro Palesi has established a notable academic profile through research focused on intelligent systems, smart cities, and artificial intelligence. His contributions demonstrate technical rigor, practical relevance, and collaborative scholarship. Continued research activity within these domains is expected to further strengthen his academic impact and professional recognition.

References

  1. Elsevier. (n.d.). Scopus author details: Luciano Alessandro Ipsaro Palesi, Author ID 57226812823. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57226812823
  2. Fanfani, M., Ipsaro Palesi, L. A., & Nesi, P. (2026). Human-Centered AI for Decision Support Systems: A Systematic Review of Application Domains, Architecture Designs, Current Trends and Future Directions. Big Data and Cognitive Computing.
    https://doi.org/10.3390/bdcc10060186
  3. Bellini, P., Ipsaro Palesi, L. A., Giovannoni, A., & Nesi, P. (2023). Managing Complexity of Data Models and Performance in Broker-Based Internet/Web of Things Architectures. Internet of Things.
    https://doi.org/10.1016/j.iot.2023.100834
  4. Fereidooni, Z., Ipsaro Palesi, L. A., & Nesi, P. (2025). Multi-Agent Optimizing Traffic Light Signals Using Deep Reinforcement Learning. IEEE Access.
    https://doi.org/10.1109/ACCESS.2025.3578518
  5. Bilotta, S., Ipsaro Palesi, L. A., & Nesi, P. (2025). Exploiting Open Data for CO2 Estimation via Artificial Intelligence and Explainable AI. Expert Systems with Applications.
    https://doi.org/10.1016/j.eswa.2025.128598

Lamia Fourati | Computer Science | Best Researcher Award

Prof Dr. Lamia fourati | Computer Science | Best Researcher Award

Computer science and multimedia higher institute of Sfax | Tunisia

Prof. Lamia Chaari Fourati is a distinguished Professor of Telecommunications at the Higher Institute of Computer Science and Multimedia (ISIMS), Sfax University, Tunisia, and a senior researcher at the Digital Research Center of Sfax (CRNS) within the SM@RTS Laboratory. With over two decades of academic and research excellence, she has established herself as one of North Africa’s leading figures in wireless communications, intelligent network systems, and AI-driven communication technologies. Her research is centered on the design, optimization, and security of wireless networks—including Wireless Body Area Networks (WBANs), Internet of Things (IoT), UAV-based networks (FANETs), and Internet of Vehicles (IoV). She has significantly contributed to developing MAC and routing protocols, trust management frameworks, and privacy-preserving communication systems for next-generation wireless infrastructures. Her innovative work also spans AI, machine learning, reinforcement learning, blockchain, and federated learning, applied to 6G, edge, and cloud computing ecosystems, with a focus on security, reliability, and energy efficiency. Prof. Fourati’s international collaborations are extensive. She serves as a Working Group Member in European COST Actions such as INTERACT (CA20120) and CA22168 on Physical Layer Security for Trustworthy and Resilient 6G Systems. She has led and participated in multiple sponsored projects on AI-based secure frameworks for UAVs, trust management in IoV, and smart water systems, in partnership with institutions like University of Troyes (France) and University of Aveiro (Portugal). Her research has also been pivotal in developing autonomous and energy-efficient communication systems for smart cities, vehicular networks, and healthcare applications. A dedicated educator and mentor, Prof. Fourati has supervised numerous Master’s and Ph.D. theses and has served on national and international doctoral juries. Her global academic engagements include visiting professorships in India, delivering advanced courses on LLMs, generative AI, network security, IoT, and mobile networks, as well as invited tutorials and talks at major IEEE and international events such as NoF, CRiSIS, IEEE ICBC, and ICHI. Her distinguished contributions have earned her prestigious recognitions, including the African Union Kwame Nkrumah Regional Scientific Award (2016), Miss.Africa Seed Fund Award (2018), Burj Kallel Award for Best Researcher (2019), and Outstanding Woman in Tech – North Africa (2021). In 2024, she was named among the Top Tunisian Women in Tech. An IEEE Senior Member and active participant in organizations such as OWSD, N2Women, ISOC, and ITU, Prof. Fourati continues to inspire the next generation of researchers and women in STEM. Her work integrates sustainable development, green computing, and ethical AI, aiming to build a future where intelligent, secure, and inclusive communication systems empower societies globally.

Profiles: Scopus | Orcid

Featured Publications

Fourati, L. C. (2024). Investigation of security threat datasets for intra- and inter-vehicular environments. Sensors, 24(11), 3431. https://doi.org/10.3390/s24113431

Fourati, L. C. (2022). Analysis of LoRaWAN 1.0 and 1.1 protocols security mechanisms. Sensors, 22(10), 3717. https://doi.org/10.3390/s22103717

Fourati, L. C. (2022). A genetic algorithm-based intelligent solution for water pipeline monitoring system in a transient state. Concurrency and Computation: Practice and Experience, 34(21), e5959. https://doi.org/10.1002/cpe.5959

Fourati, L. C. (2022). Cyber-physical systems for structural health monitoring: Sensing technologies and intelligent computing. Journal of Supercomputing, 78, 15126–15153. https://doi.org/10.1007/s11227-021-03875-5

Fourati, L. C. (2022). Investigation on vulnerabilities, threats and attacks prohibiting UAVs charging and depleting UAVs batteries: Assessments and countermeasures. Ad Hoc Networks, 131, 102805. https://doi.org/10.1016/j.adhoc.2022.102805

Fourati, L. C. (2021). 5G network slicing: Fundamental concepts, architectures, algorithmics, projects practices, and open issues. Concurrency and Computation: Practice and Experience, 33(24), e6352. https://doi.org/10.1002/cpe.6352

Fourati, L. C. (2021). A convoy of ground mobile vehicles protection using cooperative UAVs-based system. In 2021 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1–6). IEEE. https://doi.org/10.1109/ISNCC52172.2021.9615724

Fourati, L. C. (2021). A survey of 5G network systems: Challenges and machine learning approaches. International Journal of Machine Learning and Cybernetics, 12, 1–27. https://doi.org/10.1007/s13042-020-01178-4

Fourati, L. C. (2021). Blockchain-based trust management approach for IoV. In Lecture Notes in Networks and Systems (Vol. 206, pp. 455–467). Springer. https://doi.org/10.1007/978-3-030-75100-5_42