Emmanouil Zoulias | Cybersecurity | Best Researcher Award

Published on by Global CSE Awards

Best Researcher Award

Emmanouil Zoulias – National and Kapodistrian University of Athens

Emmanouil Zoulias
Affiliation National and Kapodistrian University of Athens
Country Greece
Scopus ID 55944921900
Documents 76
Citations 389
h-index 10
Subject Area Cybersecurity
Event Global CSE Awards
ORCID 0000-0002-1953-3267

Emmanouil Zoulias is affiliated with the National and Kapodistrian University of Athens, Greece. His research profile encompasses cybersecurity and technology-oriented academic contributions. His publications also address healthcare information systems, digital applications, and telemedicine, demonstrating interdisciplinary engagement with technological solutions and healthcare workflows. His academic profile provides a foundation for examining research productivity, publication activity, and scholarly impact within contemporary scientific research. [1] [3]

Abstract

Emmanouil Zoulias, affiliated with the National and Kapodistrian University of Athens in Greece, maintains a scholarly profile associated with cybersecurity and interdisciplinary technological research. His Scopus profile reports 76 documents, 389 citations, and an h-index of 10, providing bibliometric indicators of publication activity and scholarly visibility. His selected publications address data management for molecular blood donor screening, mobile health applications for operating-room nurses, and telemedicine integration within the Greek national healthcare system.  [1]

Keywords

  • Cybersecurity
  • Research Productivity
  • Digital Healthcare
  • Telemedicine
  • Healthcare Information Systems
  • Academic Research

Introduction

Cybersecurity and digital technologies increasingly influence healthcare, information management, and scientific research. Emmanouil Zoulias’s academic profile connects technology-oriented scholarship with healthcare applications, including digital workflows and telemedicine. His publications provide context for understanding interdisciplinary research addressing contemporary technological and organizational challenges. [3]

Research Profile

Emmanouil Zoulias is affiliated with the National and Kapodistrian University of Athens, Greece. His Scopus profile records 76 documents, 389 citations, and an h-index of 10. These bibliometric indicators provide an overview of indexed scholarly productivity and citation visibility. [1] [2]

Research Contributions

His selected publications examine data-management tools for molecular blood donor screening, mobile applications supporting operating-room nursing workflows, and telemedicine integration in Greece. These contributions address information processing, healthcare coordination, digital workflow optimization, and technology-enabled service delivery.[2] [3]

Publications

The following selected publications illustrate research addressing healthcare information systems, digital applications, and telemedicine. Their DOI identifiers provide persistent links to publication records and support verification of the cited scholarly works. [1]

Research Impact

The researcher profile reports 389 citations and an h-index of 10, indicating measurable scholarly visibility. Publications addressing healthcare information systems and digital applications contribute to discussions concerning clinical workflows, information management, and technology-enabled healthcare delivery.[2]

Award Suitability

The documented publication record, citation indicators, and interdisciplinary research activities provide relevant academic context for the Best Researcher Award category. Recognition associated with the Global CSE Awards acknowledges the supplied researcher profile and award designation. [1]

Conclusion

Emmanouil Zoulias’s academic profile demonstrates research engagement across cybersecurity, digital technologies, and healthcare information systems. His publications and bibliometric indicators provide an overview of scholarly productivity, interdisciplinary research interests, and academic contributions within technology-oriented research.[3]

References

  1. A Data-Management Tool for Reactive Sample Handling in Molecular Blood Donor Screening
    https://doi.org/10.3233/SHTI260919
  2. A Mobile Health Application for Operating Room Nurses: Optimizing Workflows with Surgical Checklists and Preference Cards. (n.d.). Studies in Health Technology and Informatics. IOS Press.
    https://doi.org/10.3233/SHTI260792
  3. Telemedicine Integration into the Greek National Health Care System: Challenges, Suggestions and Future Perspectives. (n.d.). Studies in Health Technology and Informatics. IOS Press.
    https://doi.org/10.3233/SHTI250709

Ahmed Elkhalil | Cybersecurity | Excellence in Cybersecurity Leadership Award

Published on by Global CSE Awards

Excellence in Cybersecurity Leadership Award

Ahmed Elkhalil
Affiliation Qilu Institute of Technology
Country China
Subject Area Cybersecurity
Scopus Profile 57218991786
Documents 19
Citations 176
h-index 7
Event Global CSE Awards
ORCID ORCID Profile

Ahmed Elkhalil is a researcher affiliated with Qilu Institute of Technology, China, whose stated academic subject area is Cybersecurity. Cybersecurity focuses on protecting digital systems, networks, applications, and information against unauthorized access, malicious activities, and cyber threats. The supplied publications associated with his research profile address secure blockchain frameworks for vehicular ad hoc networks, exfiltration-resistant edge computing for intelligent transportation systems, and adversarial attack detection in industrial control systems.[1] [2] [3]

Abstract

This article presents the academic research profile of Ahmed Elkhalil, affiliated with Qilu Institute of Technology, China, in the subject area of Cybersecurity. The supplied research publications address secure blockchain frameworks for vehicular ad hoc networks, exfiltration-resistant edge computing architectures for intelligent transportation systems, and adversarial attack detection in industrial control systems using LSTM-based intrusion detection and black-box defense strategies. [1]

Keywords

Cybersecurity; Blockchain Security; Vehicular Ad Hoc Networks; VANETs; Secure Blockchain Framework; Firewall Protection; Edge Computing; Intelligent Transportation Systems; Data Exfiltration; Intrusion Detection Systems; Industrial Control Systems; Adversarial Attack Detection; LSTM; Black-Box Defense; Network Security; Cyber Defense.

Introduction

Cybersecurity is an important field of research concerned with protecting information systems, communication networks, digital infrastructure, and connected technologies from cyber threats. As digital systems become increasingly interconnected, security challenges involving unauthorized access, malicious attacks, data leakage, and system vulnerabilities continue to require advanced protective approaches. [3]

Research Profile

Ahmed Elkhalil is affiliated with Qilu Institute of Technology, China. His stated subject area is Cybersecurity, and the supplied publication titles indicate research interests involving blockchain security, vehicular network protection, edge computing security, intelligent transportation systems, and intrusion detection in industrial control environments.The supplied Scopus details indicate 19 scholarly documents, 176 citations, and an h-index of 7. [2]

Research Contributions

One of the supplied publications introduces BCRF-SC, a provably secure hybrid blockchain framework with firewalls for resilient vehicular ad hoc networks (VANETs). Vehicular ad hoc networks support communication among vehicles and connected infrastructure, creating security requirements involving data integrity, communication reliability, and protection against unauthorized activities.[1] [2]

Publications

The following publications were provided as references for the research profile of Ahmed Elkhalil. These works address blockchain security in vehicular networks, secure edge computing for intelligent transportation systems, and adversarial attack detection in industrial control systems. [2]

Research Impact

Research on secure blockchain frameworks for vehicular ad hoc networks contributes to the understanding of security requirements in connected transportation systems. Blockchain-based approaches and firewall mechanisms can be examined as components of network protection architectures.Together, the supplied publications provide research perspectives on blockchain security, edge computing protection, and industrial intrusion detection.[3]

Award Suitability

The Excellence in Cybersecurity Leadership Award recognizes research contributions and leadership in advancing cybersecurity knowledge, developing protective technologies, and addressing important digital security challenges.Ahmed Elkhalil’s supplied academic profile identifies his affiliation with Qilu Institute of Technology, China, and his subject area as Cybersecurity. The provided Scopus information records 19 documents, 176 citations, and an h-index of 7. [1]

Conclusion

Ahmed Elkhalil’s academic profile is associated with Qilu Institute of Technology, China, and the subject area of Cybersecurity. The supplied Scopus information includes 19 documents, 176 citations, and an h-index of 7. The provided research publications examine a provably secure hybrid blockchain framework for VANETs, exfiltration-resistant edge computing for intelligent transportation systems.[3]

References

  1. BCRF-SC: Provably secure hybrid blockchain framework with firewalls for resilient VANETs.
    https://doi.org/10.1016/j.compeleceng.2026.111578
  2. Exfiltration-resistant edge computing framework for secure intelligent transportation systems.
    https://doi.org/10.1016/j.pmcj.2026.102181
  3. Adversarial Attack Detection in Industrial Control Systems Using LSTM-Based Intrusion Detection and Black-Box Defense Strategies.
    https://doi.org/10.63180/jcsra.thestap.2025.3.2

Ola Khresat | Cybersecurity | Excellence in Artificial Intelligence Award

Published on by Global CSE Awards

Excellence in Artificial Intelligence Award

Ola Khresat
Affiliation Zarqa University
Country Jordan
Subject Area Cybersecurity
Scopus ID 57920618700
Documents 23
Citations 25
h-index 3
Google Scholar Scholar Profile
Event Global CSE Awards

Ola Khresat is a researcher affiliated with Zarqa University, Jordan, whose supplied academic profile identifies Cybersecurity as the subject area. The provided research references cover organizational internal control, financial reporting standards, and machine-learning-based fault detection in industrial Internet of Things (IoT) environments. These topics highlight the importance of information integrity, intelligent data analysis, and reliable digital systems. The application of machine learning to industrial monitoring demonstrates the relevance of artificial intelligence to identifying operational abnormalities and supporting intelligent technological solutions. [1] [2] [3]

Abstract

This article presents the academic research profile of Ola Khresat, affiliated with Zarqa University, Jordan, with Cybersecurity identified as the subject area. Artificial Intelligence is an interdisciplinary field that combines machine learning, computational methods, data analysis, and automated reasoning to develop intelligent solutions for complex problems. Its applications include cybersecurity, industrial monitoring, information management, and automated fault detection. The supplied Scopus profile reports 23 documents, 25 citations, and an h-index of 3.[1] [2] [3]

Keywords

Machine Learning; Industrial Internet of Things; IoT Fault Detection; Intelligent Monitoring; Information Security; Data Integrity; COSO Framework; Internal Control; IFRS 15; Financial Reporting; Time-Series Analysis; Industrial Monitoring.

Introduction

Artificial Intelligence has become an important area of technological development, enabling computers and digital systems to perform tasks involving data analysis, pattern recognition, prediction, and automated decision-making. Through machine learning, computational modelling, and intelligent algorithms, AI supports applications across industries, including finance, healthcare, telecommunications, manufacturing, and cybersecurity. Cybersecurity focuses on protecting digital information, networks, applications, and connected infrastructure against unauthorized access, disruption, and malicious activities. [1] [2] [3]

Research Profile

Ola Khresat is affiliated with Zarqa University in Jordan. The supplied academic information identifies Cybersecurity as the subject area and provides a Scopus author identifier and Google Scholar profile for academic reference. According to the supplied Scopus information, the research profile includes 23 documents, 25 citations, and an h-index of 3. These bibliometric indicators provide a quantitative overview of the publication and citation information provided for the researcher. Such indicators may change over time as additional research is published, indexed, and cited. [1] [2] [3]

Research Contributions

Artificial Intelligence and Cybersecurity contribute to the development of reliable digital environments through intelligent data analysis, automated monitoring, and computational approaches to identifying potential problems. Machine learning provides methods for examining large datasets, recognizing patterns, and supporting predictions. These approaches can be applied to industrial monitoring, network security, information management, and operational risk analysis. The supplied publications offer context for understanding the research themes associated with organizational integrity, financial information, and intelligent fault detection. [1] [2] [3]

Publications

The following three references were supplied for this academic profile. Their publication titles and source links are reproduced as provided. The works address internal control components based on the COSO framework, IFRS 15 and telecommunications profitability, and machine-learning-based fault detection in industrial IoT monitoring.

Research Impact

Research involving artificial intelligence, cybersecurity, and intelligent industrial monitoring can contribute to the development of reliable and efficient digital systems. Machine-learning-based fault detection offers methods for analysing industrial data, identifying abnormal patterns, and supporting timely maintenance decisions. These approaches can help improve operational awareness and reduce the challenges associated with monitoring complex connected infrastructure.[1] [2] [3]

Award Suitability

The Excellence in Artificial Intelligence Award recognizes academic and research contributions that demonstrate innovation, technical knowledge, and meaningful applications of intelligent computational methods.Ola Khresat’s supplied academic profile identifies Zarqa University, Jordan, as the institutional affiliation and Cybersecurity as the subject area. The provided Scopus information includes 23 documents, 25 citations, and an h-index of 3. [1] [2] [3]

Conclusion

Ola Khresat’s academic profile is associated with Zarqa University, Jordan, and the research subject of Cybersecurity. The supplied Scopus information reports 23 documents, 25 citations, and an h-index of 3.These research themes provide context for the relationship between artificial intelligence, intelligent data analysis, organizational integrity, and dependable digital systems. The Scopus and Google Scholar profiles provide additional researcher identification resources for academic reference. [1] [2] [3]

References

  1. The Efficiency of Applying the Internal Control Components Based on COSO Framework to Transparently Carry out Tasks and Services, Ensure Integrity and Enhance Quality and Efficiency: Case Study – The Greater Amman Municipality.
    https://ideas.repec.org/a/jfr/ijfr11/v11y2020i2p371-381.html
  2. Impact of the Application of IFRS 15 on the Profitability of Jordanian Telecom Companies (Case Study: Jordan Orange Telecom).
    https://ideas.repec.org/a/jfr/ijfr11/v12y2021i2p308-317.html
  3. Identification of Fault Detection in IoT using Machine Learning: The Framework for Analysis of Time-Series based Industrial Monitoring.
    https://ieeexplore.ieee.org/abstract/document/11325700

Dr.Shayesta Naziri | Cybersecurity | Editorial Board Member

Published on by Global CSE Awards

Editorial Board Member

Dr. Shayesta Naziri
University of Technology Sydney, Australia
Dr. Shayesta Naziri
Affiliation University of Technology Sydney
Country Australia
Scopus ID 59668541200
Documents 2
Citations 2
h-index 1
Subject Area Cybersecurity
Event Global CSE Awards

Dr. Shayesta Naziri is affiliated with the University of Technology Sydney in Australia and is associated with research in cybersecurity, with reported scholarly records indexed through Scopus. Her research profile includes work addressing authentication, privacy, and security protocols for connected and distributed systems, including applications involving unmanned aerial vehicles and RFID technologies. [1] [2] [3]

Abstract

Dr. Shayesta Naziri is a cybersecurity researcher affiliated with the University of Technology Sydney, Australia. Her reported research interests include secure authentication, privacy preservation, cryptographic protocols, and security mechanisms for connected systems. Her publication record includes studies on zero-knowledge authentication for unmanned aerial vehicles, location-aware privacy, and mutual authentication for RFID systems. These works examine methods for strengthening identity verification while reducing unnecessary disclosure of sensitive information in networked environments. [1] [2] [3]

Keywords

Cybersecurity; authentication; zero-knowledge proofs; privacy preservation; unmanned aerial vehicles; RFID security; cryptographic protocols; location privacy; mutual authentication; key agreement.

Introduction

Cybersecurity research addresses the protection of digital systems against unauthorized access, disclosure, manipulation, and impersonation. Dr. Shayesta Naziri’s reported publications examine authentication and privacy challenges in connected technologies, particularly UAV and RFID environments. These studies employ cryptographic approaches intended to verify legitimate participants while limiting exposure of sensitive identity or location information. [1] [2] [3]

Research Profile

The reported research profile is centered on cybersecurity mechanisms for networked and resource-constrained environments. Relevant themes include secure authentication, key establishment, privacy-preserving verification, and cryptographic protection. The publications indicate an interest in applying formal security concepts to practical communication scenarios involving UAVs, cross-domain systems, and RFID infrastructures. [1] [2] [3]

Research Contributions

The reported contributions concern privacy-aware authentication and secure key establishment. ZAPS investigates a zero-knowledge proof protocol for UAV authentication while addressing flight-path privacy. PrivLocAuth examines location-aware cross-domain UAV authentication with zero-knowledge location privacy, while SMAKAP addresses mutual authentication and key agreement for RFID systems. Together, these publications cover complementary cybersecurity problems. [1] [2] [3]

Publications

The supplied publication information identifies research on zero-knowledge authentication for UAVs, location-aware cross-domain UAV authentication, and secure mutual authentication with key agreement for RFID systems. The first work is available through arXiv, the second is published in Electronics by MDPI, and the third is indexed through IEEE Xplore. [1] [2] [3]

Research Impact

The available bibliographic information reports a Scopus profile containing two documents, two citations, and an h-index of one. These metrics provide a limited quantitative snapshot and should be interpreted in relation to publication age, indexing coverage, citation practices, and the size of the available record. The cited studies address practical cybersecurity requirements involving authentication and privacy. [1] [2] [3]

Award Suitability

The documented research themes correspond to the broad field of cybersecurity and include authentication, privacy preservation, cryptographic protocols, UAV security, and RFID protection. These areas are relevant to recognition programs focused on cybersecurity research and technology. Any formal award or editorial appointment should be assessed according to the applicable eligibility criteria, evidence requirements, and independent evaluation procedures of the organizing body. [1] [2] [3]

Conclusion

Dr. Shayesta Naziri’s reported scholarly work is situated within cybersecurity research, with particular attention to authentication and privacy-preserving mechanisms. The supplied publications demonstrate research coverage across UAV and RFID security applications, while the available bibliometric information provides a limited record of indexed scholarly activity. Further assessment can consider subsequent publications, citations, and research outputs. [1] [2] [3]

References

  1. ZAPS: A Zero-Knowledge Proof Protocol for Secure UAV Authentication with Flight Path Privacy. (2025). arXiv.
    https://arxiv.org/abs/2508.17043
  2. PrivLocAuth: Enabling Location-Aware Cross-Domain UAV Authentication with Zero-Knowledge Location Privacy. (2026). Electronics, 15(6), 1243. MDPI.
    https://www.mdpi.com/2079-9292/15/6/1243
  3. SMAKAP: Secure Mutual Authentication and Key Agreement Protocol for RFID Systems. (2025). IEEE Xplore. Document 10871792.
    https://ieeexplore.ieee.org/abstract/document/10871792

Shamsuddeen Umaru Adamu | Cybersecurity | Best Researcher Award

Published on by Global CSE Awards

Best Researcher Award

Shamsuddeen Umaru Adamu — Kaduna State University

Shamsuddeen Umaru Adamu
Affiliation Kaduna State University
Country Nigeria
Scopus ID 59104600400
Documents 2
Citations 6
h-index 1
Subject Area Cybersecurity
Event Global CSE Awards
ORCID 0000-0001-8227-220X

Shamsuddeen Umaru Adamu is a researcher affiliated with Kaduna State University, Nigeria, whose documented scholarly work is associated with cybersecurity and related computational research. His research record includes studies addressing cybersecurity frameworks in higher education and natural language processing involving Hausa-language data, reflecting interdisciplinary engagement with security, technology, and African language resources. [1] [2]

Abstract

Shamsuddeen Umaru Adamu is a cybersecurity researcher affiliated with Kaduna State University, Nigeria. His documented research interests include cybersecurity frameworks in higher education and computational language technologies involving Hausa, demonstrating an intersection of information security, artificial intelligence, and African language resources. His publication record includes work examining the adoption and effectiveness of cybersecurity frameworks within higher education institutions, together with contributions to sentiment analysis using low-resource Hausa tweet data. These studies address practical and methodological challenges relevant to secure digital environments and inclusive language technologies. His Scopus record reports two documents, six citations, and an h-index of one, providing measurable evidence of scholarly activity.

Keywords

Cybersecurity, Cybersecurity Frameworks, Higher Education Security, Information Security, Hausa Natural Language Processing, Sentiment Analysis, Low-Resource Languages, African Language Technology, Computational Research, Cybersecurity Research. [1] [2]

Introduction

Cybersecurity research in higher education addresses institutional protection, governance, risk management, and effective security practices across increasingly digital academic environments. Adamu’s documented work examines cybersecurity framework adoption and effectiveness, while related research explores Hausa-language sentiment analysis using low-resource social-media data. These topics demonstrate engagement with contemporary computational challenges. [1] [2]

Research Profile

Adamu’s research profile is centered on cybersecurity, with documented scholarly activity extending into natural language processing and sentiment analysis. His work connects information security concerns with computational methods and African language resources, indicating an interdisciplinary research orientation. The available publication record provides evidence of research activity across security and language-technology themes. [1] [2]

Research Contributions

The documented contributions include examination of cybersecurity framework adoption and effectiveness in higher education institutions, alongside participation in research addressing sentiment analysis for Hausa, a relatively low-resource African language. Together, these works contribute to discussions of institutional cybersecurity and computational approaches for improving language-data analysis in underrepresented linguistic contexts. [1] [2] [3]

Publications

The available publication record includes a systematic literature review concerning cybersecurity framework adoption in higher education and two Scopus-indexed records associated with HausaNLP and SemEval-2023 Task 12. These publications reflect research activity spanning cybersecurity, natural language processing, sentiment analysis, and low-resource African language technologies, with the cited records providing bibliographic verification. [1] [2] [3]

Research Impact

The available Scopus indicators report two documents, six citations, and an h-index of one, providing a quantitative snapshot of Adamu’s indexed research activity. His work on cybersecurity frameworks is relevant to institutional security discussions, while HausaNLP research supports broader efforts to develop computational resources and analytical methods for African low-resource languages. [1] [2]

Award Suitability

Adamu’s documented research activity aligns with the Best Researcher Award through its focus on cybersecurity and related computational research. His publications address applied security questions and low-resource language technology, demonstrating scholarly engagement across complementary areas of computer science. The available bibliographic record and citation indicators provide supporting evidence for recognition consideration. [1] [2] [3]

Conclusion

Shamsuddeen Umaru Adamu’s documented scholarly profile reflects research activity in cybersecurity and computational language technologies. His work addresses cybersecurity frameworks in higher education and sentiment analysis for Hausa-language data, connecting practical security concerns with emerging computational research. The available Scopus indicators and indexed publications provide a basis for academic recognition. [1] [2]

References

  1. A systematic literature review on the adoption and effectiveness of cybersecurity frameworks in higher education institutions. (n.d.). Scopus.
    https://www.scopus.com/inward/record.url?eid=2-s2.0-105029652508&partnerID=MN8TOARS
  2. HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis. (n.d.). Scopus.
    https://www.scopus.com/inward/record.url?eid=2-s2.0-85159598145&partnerID=MN8TOARS
  3. HausaNLP at SemEval-2023 Task 12: Leveraging African Low Resource TweetData for Sentiment Analysis. (n.d.). Scopus.
    https://www.scopus.com/inward/record.url?eid=2-s2.0-85161065173&partnerID=MN8TOARS

Sriven Srilakshmi Pulkaram | CyberSecurity | Innovative Research Award

Published on by Global CSE Awards

Innovative Research Award

Sriven Srilakshmi Pulkaram
California State University, Dominguez Hills

                Sriven Srilakshmi Pulkaram
Affiliation California State University, Dominguez Hills
Country United States
Scopus ID 60211143700
Documents 3
Citations 4
h-index 1
Subject Area CyberSecurity
Event Global CSE Awards
Google Scholar FLw_CQwAAAAJ

Sriven Srilakshmi Pulkaram is a researcher affiliated with California State University, Dominguez Hills, whose scholarly work focuses on cybersecurity, privacy-preserving machine learning, healthcare Internet of Things (IoT), federated learning, homomorphic encryption, and secure data aggregation. Her published contributions address emerging challenges in secure distributed intelligence and privacy-aware healthcare computing environments.[1]

Abstract

This article summarizes the academic profile, research accomplishments, publication record, and scholarly impact of Sriven Srilakshmi Pulkaram. Her research addresses cybersecurity and privacy challenges in healthcare IoT systems through federated learning, encrypted aggregation, and edge-assisted computing architectures designed to improve secure and scalable distributed intelligence.[1]

Keywords

Cybersecurity, Federated Learning, Healthcare IoT, Homomorphic Encryption, Privacy Preservation, Edge Computing, Secure Aggregation, Wearable Devices, Distributed Intelligence, Data Security.

Introduction

The increasing adoption of connected healthcare technologies has intensified concerns regarding privacy, security, and trustworthy data sharing. Sriven Srilakshmi Pulkaram’s research explores advanced cybersecurity mechanisms for healthcare IoT environments, emphasizing federated learning, encrypted computation, and privacy-preserving communication frameworks that support secure and efficient distributed machine learning systems.[1][2]

Research Profile

As a researcher in computer science and cybersecurity, Pulkaram focuses on privacy-enhancing technologies for distributed healthcare applications. Her work combines federated learning, homomorphic encryption, edge computing, and secure networking principles to address confidentiality, scalability, latency, and data protection requirements within modern digital healthcare infrastructures.[1][2]

Research Contributions

Her contributions include the development of privacy-aware federated learning frameworks, encrypted aggregation techniques, and edge-assisted architectures that enhance healthcare IoT security. These studies investigate practical methods for reducing communication overhead while maintaining confidentiality, model accuracy, scalability, and compliance with evolving privacy expectations in sensitive environments.[1][2][3]

Publications

The publication record includes research on encrypted federated learning for wearable healthcare systems, homomorphic encryption in health IoT networks, and privacy-preserving in-network aggregation approaches. These works collectively examine secure machine learning deployment, low-latency communication strategies, and efficient protection mechanisms for healthcare-related distributed data processing.[1][2][3]

Research Impact

The research contributes to the growing body of knowledge surrounding secure artificial intelligence and healthcare cybersecurity. By addressing privacy, latency, and scalability challenges simultaneously, these studies support the advancement of practical frameworks that may facilitate trustworthy deployment of distributed intelligence across healthcare and IoT ecosystems.[1][2][3]

Award Suitability

The Innovative Research Award recognizes researchers whose work demonstrates originality and relevance. Pulkaram’s investigations into privacy-preserving healthcare computing, encrypted machine learning, and cybersecurity-driven solutions align with the objectives of innovation-oriented recognition programs by addressing significant technical challenges through emerging computational methodologies.[1][2]

Conclusion

Sriven Srilakshmi Pulkaram has established an emerging research profile focused on cybersecurity and privacy-preserving healthcare technologies. Her scholarly contributions demonstrate engagement with contemporary challenges involving federated learning, encrypted computation, and secure IoT systems, supporting ongoing advancements in trustworthy and scalable digital healthcare environments.[1][2][3]

References

  1. Khan, H., Kavati, R., Pulkaram, S. S., & Jalooli, A. (2025). End-to-end privacy-aware federated learning for wearable health devices via encrypted aggregation in programmable networks. Sensors, 25(22), 7023.
    https://www.mdpi.com/1424-8220/25/22/7023
  2. Pulkaram, S. S., et al. (2025). Securing Federated Learning in Health IoT with Edge-Assisted Homomorphic Encryption. IEEE Conference Proceedings.
    https://ieeexplore.ieee.org/abstract/document/11393779
  3. Pulkaram, S. S., et al. (2025). Efficient Privacy-Preserving In-Network Data Aggregation for Low-Latency Healthcare IoT. IEEE Conference Proceedings.
    https://ieeexplore.ieee.org/abstract/document/11393722
  4. Elsevier. (n.d.). Scopus author details: Sriven Srilakshmi Pulkaram, Author ID 60211143700. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=60211143700

Eshetie Teka | Cyber Security | Innovative Research Award

Published on by Global CSE Awards

Innovative Research Award

Eshetie Teka
University of Gondar, Ethiopia
                Eshetie Teka
Affiliation University of Gondar
Country Ethiopia
Google Scholar ID 12Ydj_QAAAAJ
Documents 3
Citations 9
h-index 1
Subject Area Cyber Security
Event Global CSE Awards

Eshetie Teka is affiliated with the University of Gondar, Ethiopia, and has contributed to interdisciplinary research in cyber security, machine learning, and health data analytics. His academic work focuses on predictive analytics and blockchain-enabled cyber security frameworks designed to address distributed network vulnerabilities and public health challenges. Through collaborative research activities, he has participated in studies involving ensemble machine learning algorithms for child stunting prediction and blockchain-based protection mechanisms against Distributed Denial of Service attacks. His scholarly publications demonstrate an emerging contribution to applied computing and data-driven security research within academic and technological domains.[1][2]

Abstract

This article presents an overview of the academic and research contributions of Eshetie Teka in the areas of cyber security, blockchain systems, and machine learning applications in health analytics. His research activities demonstrate interdisciplinary integration between computational intelligence and practical societal challenges. The documented publications highlight analytical approaches for predictive health assessment and blockchain-supported protection against cyber threats. These studies contribute to emerging technological advancements and support data-driven decision-making within modern digital infrastructures and healthcare-oriented analytical environments.[1]

Keywords

Cyber Security, Blockchain Technology, Machine Learning, Ensemble Algorithms, Predictive Analytics, DDoS Protection, Health Informatics, Data Science, Ethiopia, Distributed Systems.

Introduction

Eshetie Teka’s academic activities focus on integrating computational technologies with practical problem-solving approaches in cyber security and healthcare analytics. His work reflects the growing importance of machine learning and blockchain technologies in modern research environments. The studies demonstrate interdisciplinary collaboration and evidence-based technological innovation within digital systems and predictive modeling applications.[2]

Research Profile

The research profile of Eshetie Teka includes cyber security systems, blockchain-enabled protection frameworks, and machine learning-driven predictive analytics. His publications indicate collaborative engagement in solving healthcare and networking challenges through computational methodologies. The research demonstrates a combination of applied data science, information security principles, and modern analytical technologies.[1]

Research Contributions

His contributions include predictive modeling for identifying child stunting conditions using ensemble machine learning methods and blockchain-based security architectures for DDoS attack prevention. These studies support technological advancement in healthcare data analytics and network protection. The contributions illustrate practical applications of computational intelligence in real-world environments.[1][2]

Publications

    • Predicting stunting status among under five children in Ethiopia using ensemble machine learning algorithms.[1]
    • Designing of blockchain-based cyber security for the protection of Distributed Denial of Service (DDoS) attacks on client–server networks.[2]

Research Impact

The research outputs contribute to ongoing discussions regarding data-driven healthcare analysis and cyber security resilience. By applying machine learning and blockchain methodologies, the studies provide frameworks that may support decision-making, digital protection, and predictive assessment processes. These contributions demonstrate the relevance of interdisciplinary computational research within emerging technological sectors.[2]

Award Suitability

Eshetie Teka’s interdisciplinary research activities align with the objectives of the Global CSE Awards, particularly within cyber security and intelligent computing applications. His studies on blockchain-enabled protection systems and predictive machine learning models reflect innovation-oriented academic engagement and demonstrate emerging scholarly contributions suitable for international academic recognition initiatives.[1]

Conclusion

The academic profile of Eshetie Teka highlights growing involvement in computational research focused on cyber security and predictive analytics. His collaborative publications demonstrate the integration of machine learning and blockchain technologies into practical applications. These scholarly contributions indicate meaningful participation in advancing research within interdisciplinary technology-oriented academic domains.[1][2]

References

    1. Ayele, M. K., Baye, G. A., Yesuf, S. H., Engda, A. A., & Mitiku, E. T. (2025). Predicting stunting status among under five children in Ethiopia using ensemble machine learning algorithms. Nature.com listing. Nature.
      https://www.nature.com/articles/s41598-025-03206-1
    2. Mitiku, E. T., Munaye, Y. Y., Selvakumar, S., Mitiku, G. A., Belete, A. A., Zeru, S. A., et al. (2024). Designing of blockchain-based cyber security for the protection of Distributed Denial of Service (DDoS) attacks on client–server networks. Discover Data, 4(1), 8.
      https://link.springer.com/article/10.1007/s44248-026-00107-0
    3. Google Scholar. (n.d.). Eshetie Teka – Google Scholar profile. Google Scholar.
      https://scholar.google.com/citations?user=12Ydj_QAAAAJ&hl=en

Sultan Aldırmaz Colak | Privacy Protection | Best Researcher Award

Published on by Global CSE Awards

Assoc. Prof. Dr. Sultan Aldırmaz Colak | Privacy Protection | Best Researcher Award

Associate Professor| Kocaeli University| Turkey

Assoc. Prof. Dr. Sultan Aldırmaz Çolak has established an influential research career in applied mathematics, with particular emphasis on fractional calculus, functional analysis, operator theory, q-calculus, inequalities, optimization techniques, and mathematical modeling. The work integrates both theoretical and applied perspectives, contributing to the development of new mathematical structures and analytical approaches. A strong research presence is visible in fractional differential equations, fractional inequalities, and variational principles, where innovative methodologies are applied to solve complex problems in pure and applied sciences. Contributions extend to fractional operators with general kernels, quantum calculus, approximation theory, fixed point theorems, and applications of conformable fractional derivatives, reflecting versatility in addressing modern mathematical challenges. Publications highlight advances in inequalities of Hermite–Hadamard type, generalizations of classical results, and connections between fractional calculus and convexity theory. Beyond core mathematics, research interests also include mathematical programming, optimization problems, and algorithmic approaches, establishing bridges with computer science and applied engineering. Engagement in international collaborations has broadened the reach of this research, demonstrated through joint works published in reputed journals across mathematical sciences. The scientific output emphasizes originality in both problem formulation and solution strategies, making significant contributions to ongoing discourse in advanced calculus and related domains. Focus areas like generalized convex functions, applications of Jensen’s inequality, integral transforms, and iterative methods for nonlinear operators position this work at the interface of analysis, computation, and modeling. Active participation in editorial roles and peer review further indicates a commitment to advancing the discipline. Overall, the research achievements of Assoc. Prof. Dr. Sultan Aldırmaz Çolak represent a consistent pursuit of mathematical innovation with practical relevance across interdisciplinary boundaries. 486 Citations 54 Documents 11

Profile:  Google Scholar | Scopus | ORCID
Featured Publication

Authors unavailable. (2025). Physical layer security in RIS-aided communication systems: Secrecy performance analyses. Digital Signal Processing: A Review Journal.

Authors unavailable. (2025). A handover decision optimization method based on data-driven MLP in 5G ultra-dense small cell HetNets. Journal of Network and Systems Management. Citations: 3

Authors unavailable. (2025). Human respiration and motion detection based on deep learning and signal processing techniques to support search and rescue teams. Applied Sciences (Switzerland).

Authors unavailable. (2025). Target parameter estimation with ISAC-OTFS systems. Conference paper.

Authors unavailable. (2025). A comprehensive review on ISAC for 6G: Enabling technologies, security, and AI/ML perspectives. Review, Open Access. Citations: 1