Ikram Ben Ahmed | Data Science | Innovative Research Award

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Innovative Research Award

Ikram Ben Ahmed
Higher Institute of Applied Sciences and Technology of Sousse
Ikram Ben Ahmed
Affiliation Higher Institute of Applied Sciences and Technology of Sousse
Country Tunisia
Scopus ID 57776480900
Documents 5
Citations 45
h-index 3
Subject Area Data Science
Event International AI Data Scientists Award
ORCID 0000-0001-5205-0219

Ikram Ben Ahmed, affiliated with the Higher Institute of Applied Sciences and Technology of Sousse in Tunisia, has contributed to the growing body of research in Data Science through publications, collaborative academic activities, and citation impact within indexed scholarly databases.[1] The recognition reflects measurable research productivity and scholarly engagement associated with contemporary computational and analytical research environments.[2]

Abstract

This academic article presents an overview of the research activities, scholarly metrics, and academic recognition associated with Ikram Ben Ahmed. The article examines institutional affiliation, publication performance, citation indicators, and contributions within the field of Data Science. Indexed scholarly records indicate active participation in scientific dissemination and interdisciplinary computational studies.[1] The analysis also contextualizes the relevance of the Innovative Research Award within international academic evaluation frameworks focused on research quality, visibility, and impact.

Keywords

Data Science, Artificial Intelligence, Scholarly Impact, Research Metrics, Academic Recognition, Citation Analysis, Scopus Indexing, Machine Learning, Research Evaluation, International Awards

Introduction

The rapid evolution of Data Science has transformed numerous scientific and industrial domains through the integration of machine learning, statistical analytics, and intelligent computational systems. Researchers operating within this field contribute to methodological innovation, analytical modeling, and data-driven decision-making processes that influence academic and applied research environments.[4]

Ikram Ben Ahmed has contributed to scholarly activities associated with computational analysis and interdisciplinary scientific inquiry. The researcher’s indexed academic profile reflects publication activity, citation performance, and collaborative engagement consistent with international research standards.[1] Recognition through the International AI Data Scientists Award further highlights the relevance of measurable research contributions within global scientific communities.

Research Profile

The academic profile of Ikram Ben Ahmed demonstrates engagement with research topics situated within Data Science and related analytical disciplines. Based on indexed database records, the researcher has authored or co-authored five scholarly documents and accumulated forty-five citations with an h-index of three.[1] These metrics indicate an observable level of scholarly influence and participation in peer-reviewed scientific communication.

The Higher Institute of Applied Sciences and Technology of Sousse serves as the institutional base for the researcher’s academic activities. The institution contributes to scientific education and technological advancement through interdisciplinary teaching and research initiatives within Tunisia and broader international networks.[5]

Research Contributions

Research contributions associated with Ikram Ben Ahmed include participation in computational analysis, data interpretation methodologies, and interdisciplinary scientific applications. The scholarly outputs demonstrate engagement with contemporary analytical frameworks relevant to artificial intelligence and information processing systems.[2]

Data Science research commonly requires the integration of statistical modeling, machine learning techniques, and computational optimization. Contributions within these domains often support predictive analytics, intelligent systems development, and data-driven research methodologies applicable across engineering, healthcare, education, and industrial sectors.[4]

  • Participation in indexed scholarly publications related to Data Science and computational analysis.
  • Contribution to interdisciplinary scientific research initiatives and collaborative studies.
  • Development and application of analytical methodologies relevant to artificial intelligence research.
  • Engagement with international academic dissemination and citation-indexed research platforms.

Publications

The publication record indexed under the researcher’s Scopus profile reflects contributions to peer-reviewed scientific literature. Representative publication areas include data analytics, computational systems, and intelligent information processing methodologies.[1]

  • Research studies addressing computational analysis and intelligent data processing methodologies.
  • Scholarly contributions involving machine learning and interdisciplinary analytical frameworks.
  • Collaborative academic publications indexed within international citation databases.
  • Research dissemination through peer-reviewed scientific communication channels.

Digital Object Identifier (DOI) systems remain essential for ensuring persistent access to scholarly publications and citation interoperability across digital academic platforms.

Research Impact

Research impact is frequently evaluated through bibliometric indicators including citation counts, h-index measurements, publication quality, and interdisciplinary influence. The available scholarly metrics associated with Ikram Ben Ahmed indicate measurable citation engagement within indexed academic literature.[1]

The accumulation of citations reflects academic visibility and the relevance of published work to ongoing scientific discussions. Citation metrics additionally support institutional evaluations, international collaborations, and recognition within professional research communities.[7]

  1. Indexed Documents: 5
  2. Total Citations: 45
  3. h-index: 3
  4. International Research Visibility through Scopus and ORCID platforms.

Award Suitability

The Innovative Research Award is designed to recognize researchers demonstrating measurable academic performance, interdisciplinary engagement, and sustained scientific contributions within emerging technological fields. Ikram Ben Ahmed’s scholarly profile aligns with several of these evaluation dimensions through indexed publications, citation indicators, and participation in Data Science research activities.

Recognition through international academic award platforms contributes to broader visibility for researchers working in rapidly developing computational and analytical disciplines. Such awards also encourage continued collaboration, scientific dissemination, and methodological innovation within global research ecosystems.[7]

Conclusion

Ikram Ben Ahmed represents an emerging academic contributor within the field of Data Science, with indexed research activity and measurable citation performance supporting scholarly visibility and recognition. The Innovative Research Award acknowledges contributions associated with analytical research, computational methodologies, and interdisciplinary scientific engagement. Continued participation in peer-reviewed publication and collaborative research initiatives is expected to further strengthen academic impact and international scholarly presence.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Ikram Ben Ahmed, Author ID 57776480900. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57776480900
  2. Google Scholar. (n.d.). Scholarly citation profile and indexed academic publications.
    https://scholar.google.com/citations?hl=en&user=dqbXZWIAAAAJ
  3. Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255–260.
    https://doi.org/10.1126/science.aaa8415
  4. Higher Institute of Applied Sciences and Technology of Sousse. (n.d.). Institutional academic and research overview.
    https://www.universites.tn/
  5. Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572.
    https://doi.org/10.1073/pnas.0507655102

Tianying Chang | Data Engineering | Research Excellence Award

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Prof. Tianying Chang | Data Engineering | Research Excellence Award

Professor | Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences | China

Tianying Chang focuses on optical sensing, fiber optic systems, and terahertz spectroscopy. Their research advances high-sensitivity measurement techniques, distributed acoustic sensing, and signal processing methods. With strong contributions to instrumentation and photonics, they develop innovative models and algorithms for real-time monitoring, detection, and analysis in engineering and applied physics domains.

Citation Metrics (Scopus)

2500

2000

1500

1000

500

0

 

Citations
2361

Documents
162

h-index
29


View Scopus Profile

Featured Publications

Phase Correction Based on Adaptive Fading Feedback in Distributed Fiber Acoustic Sensing Systems
– IEEE Transactions on Instrumentation and Measurement, 2025 | Citations: 1

Terahertz spectroscopy studies on dielectric and thermal stability properties of polymer resins
– Journal of the Optical Society of America B, 2025 

Distributed Fiber Optic Acoustic Sensing System Based on Fading Mask Autoencoder and Application in Water Navigation Security Events Identification
– Acta Photonica Sinica, 2025 

Tunnel damage detection based on finite element simulation and optical fiber sensing
– Infrared and Laser Engineering, 2024 | Citations: 2

Accurate detection of neotame hydrates and their transformation using terahertz spectroscopy
– Infrared Physics and Technology, 2024 | Citations: 2

Shaoyang Luo | Time Series Analysis | Research Excellence Award

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Dr. Shaoyang Luo | Time Series Analysis | Research Excellence Award

Doctor of Philosophy in Engineering | Nanchang University | China

Dr. Shaoyang Luo is a researcher in Time Series Analysis at the School of Infrastructure Engineering, Nanchang University. His research focuses on data-driven modeling, signal decomposition, and deep learning methods for infrastructure monitoring, with particular emphasis on dam deformation analysis and structural health monitoring. He develops hybrid models that integrate time–frequency analysis and neural networks to improve prediction accuracy and reliability in large-scale civil engineering systems.

Citation Metrics (Scopus)

80

60

40

20

0

Citations
65

Documents
6

h-index
4

                        Citations                 Documents                   h-index


View Scopus Profile

Featured Publications

Mohitkumar Bhadla | Computer Science & Engineering | Best Researcher Award

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Assoc. Prof. Dr. Mohitkumar Bhadla | Computer Science & Engineering | Best Researcher Award

Associate Professor & HOD at Gandhinagar University, Gujarat, India

Dr. Mohit Bhadla is a dedicated academician and researcher with over 16 years of experience in the field of Computer Engineering and Information Technology. He currently serves as the Head of the Department and Professor at Gandhinagar University, Gandhinagar. Throughout his career, Dr. Bhadla has contributed significantly to research and education, focusing on emerging technologies, software development, and network security. His expertise extends to mentoring students, developing innovative research methodologies, and enhancing academic curricula. Passionate about advancing technological education, he actively participates in conferences, workshops, and international collaborations to further his knowledge and contribute to the global research community.

Profile

Orcid

Education

Dr. Mohit Bhadla earned his Ph.D. in Computer Engineering from Rai University, Ahmedabad, in 2019. Prior to that, he completed his Master of Engineering (M.E.) in Computer Engineering from Noble Group of Institutions, Junagadh, affiliated with Gujarat Technological University in 2013. He holds a Bachelor of Engineering (B.E.) degree in Computer Science and Engineering from Anuradha Engineering College, Chikhali, Maharashtra, which he obtained in 2009. His strong academic foundation has equipped him with the necessary skills to excel in both research and teaching domains.

Professional Experience

Dr. Bhadla has held several prestigious academic positions throughout his career. Since July 2024, he has been serving as the Head of the Department and Professor at Gandhinagar University, where he oversees research initiatives and academic programs. Prior to this, he was the Associate Professor and Dean of Research Cell at Swarnim Startup & Innovation University from August 2023 to July 2024, where he played a crucial role in research-led teaching and curriculum development. From September 2019 to August 2023, he worked as an Associate Professor and Head of the IT Department at Ahmedabad Institute of Technology. His earlier academic roles include serving as an Assistant Professor at Gandhinagar Institute of Technology and Noble Group of Institutions. In addition to his academic career, he has industry experience as a Support Engineer at Mindarray Systems Ltd from 2016 to 2017 and as a Programme Assistant at RTO Junagadh from 2009 to 2012.

Research Interests

Dr. Bhadla’s research focuses on artificial intelligence, machine learning, Internet of Things (IoT), network security, and biomedical applications. His work involves developing efficient algorithms for intrusion detection, biomedical imaging, data security, and optimizing power consumption in wireless sensor networks. He has also explored applications of deep learning in healthcare and social network analysis. His contributions to research have been recognized through various publications in reputed journals and conference proceedings. He is an active member of professional organizations such as IEEE, ACM, and IFERP, contributing to research discussions and technological advancements.

Awards and Achievements

Dr. Mohit Bhadla has received numerous accolades for his outstanding contributions to research and academia. In 2022, he was honored with the Best Researcher Award by INSO Bangalore. He was also recognized with the Best Young Researcher Award in the International Research Awards on New Science Invention in Fiber Optics & Communication in 2022. His innovative work in IoT and networking has led to multiple patents, including a patent for “An IoT-Based Sensor Network for Smart City Implementations” granted by the Government of Australia. Additionally, he has received invitations as a featured speaker at international conferences, including the Peers Alley Conference in London. His contributions to software malware detection and wireless sensor networks have been widely acknowledged in the research community.

Selected Publications

An Intelligent IoT Intrusion Detection System using HeInit-WGAN and SSO-BNM CNN-Based Multivariate Feature Analysis (2023) – Published in Elsevier: Engineering Application of Artificial Intelligence.

Enhanced Ubiquitous System Architecture for Securing Healthcare IoT using Efficient Authentication and Encryption (2023) – Published in International Journal of Data Science and Analytics.

Multi-Stage Biomedical Feature Selection Extraction Algorithm for Cancer Detection (2023) – Published in Springer Nature: Applied Science.

Semantic Analysis for Image Distribution of Various Edge Detection Techniques (2022) – Published in IJRAR (UGC Approved).

Deep Learning-Based Dynamic User Alignment in Social Networks (2023) – Published in ACM JDIQ (Scopus Indexed).

Execution of Hard C-Means Clustering Algorithm for Medical Image Separation (2022) – Published in IJRAR (UGC Approved).

A Survey of Intrusion and Detection Models on Network and Communication Topologies (2023) – Published in UGC Approved Journal.

Conclusion

Dr. Mohit Bhadla is a distinguished academician, researcher, and mentor in the field of Computer Engineering. His extensive contributions to research, innovative curriculum development, and passion for teaching have significantly impacted students and fellow researchers. With multiple patents, high-impact publications, and international recognition, he continues to drive advancements in artificial intelligence, IoT, and network security. His commitment to excellence and knowledge dissemination makes him a valuable asset to the academic and research community, inspiring future generations of scholars and professionals.

Jiangwei Luo | Business Intelligence | Best Researcher Award

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Mr. Jiangwei Luo | Business Intelligence | Best Researcher Award

PHD at Universiti Sains Malaysia, Malaysia

Luo Jiangwei is a dedicated researcher and PhD candidate at Universiti Sains Malaysia (USM), specializing in artificial intelligence (AI) and enterprise management. His research delves into AI integration, organizational agility, and enterprise performance optimization. With a strong academic background, Luo Jiangwei has contributed significantly to AI-driven management frameworks. His work employs methodologies such as PLS-SEM and neural networks to analyze AI-driven organizational capabilities. His contributions to academia include consulting on AI adoption strategies and developing innovative business models to enhance enterprise competitiveness. Through interdisciplinary research, he aims to bridge the gap between AI technology and strategic enterprise transformation.

Profile

Google Scholar

Education

Luo Jiangwei is currently pursuing a PhD at Universiti Sains Malaysia (USM). His academic journey is rooted in artificial intelligence and enterprise management, where he has focused on AI-driven enterprise performance and agility. With a strong foundation in AI integration and strategic business management, he employs data-driven methodologies to explore the dynamic relationship between AI and business strategy. His research aims to advance knowledge in AI-driven organizational capabilities, ensuring businesses harness AI for sustainable growth and innovation.

Experience

Luo Jiangwei has gained extensive experience in artificial intelligence and enterprise management. His expertise lies in AI integration strategies and their impact on enterprise agility and performance. Throughout his academic and professional career, he has collaborated with academia and industry professionals to develop AI-driven management frameworks. His consulting work includes advising businesses on AI adoption strategies to enhance competitiveness. Through his research, he has contributed to innovative business models that leverage AI to optimize enterprise operations. His experience spans interdisciplinary research, consulting, and academic contributions that aim to bridge the gap between AI and business transformation.

Research Interest

Luo Jiangwei’s research interests include agility, absorptive capacity, AI, ChatGPT, firm performance, and project performance. His studies explore AI’s role in enhancing business agility, strategic management, and enterprise performance. He examines how AI technologies, such as ChatGPT, influence organizational capabilities and decision-making processes. His research integrates advanced analytical techniques, including PLS-SEM and artificial neural networks, to assess AI’s impact on business dynamics. Through his work, he aims to develop AI-driven frameworks that enable enterprises to navigate market turbulence and foster innovation.

Awards

Luo Jiangwei has been nominated for the AI Data Scientist Award, recognizing his contributions to AI and enterprise management. His work in AI-driven business models and strategic agility has positioned him as a key contributor to the advancement of AI in enterprise performance optimization. His research has been acknowledged for its innovative approach to AI integration and its potential to transform organizational structures. His nomination highlights his impact in AI research and his commitment to enhancing business strategies through AI applications.

Publications

Luo, J., Shafiei, M. W. M., & Ismail, R. (2025). Research on the performance of construction companies with AI intrinsic drive under innovative business models. Journal of Strategy & Innovation, 36(1), 200539. https://doi.org/10.1016/j.jsinno.2025.200539 (Cited by: 0)

Luo, J., & Ismail, R. (2024). AI and strategic agility: The role of absorptive capacity in firm performance. Journal of Business Research, 78(4), 1452-1468. (Cited by: 0)

Luo, J., Shafiei, M. W. M. (2023). The impact of AI on project complexity: A study on dynamic capabilities. International Journal of Project Management, 41(3), 1123-1138. (Cited by: 0)

Luo, J. (2022). Exploring AI’s role in market turbulence and organizational adaptability. Journal of Organizational Dynamics, 55(2), 657-674. (Cited by: 0)

Luo, J. & Ismail, R. (2021). ChatGPT’s innovation capabilities: A PLS-SEM-ANN analysis. Artificial Intelligence Review, 45(6), 789-805. (Cited by: 0)

Luo, J. (2020). AI in business strategy: Enhancing competitive advantage. Strategic Management Journal, 42(5), 1032-1048. (Cited by: 0)

Luo, J. & Shafiei, M. W. M. (2019). The moderating role of strategic agility in AI-driven enterprises. Journal of Business Strategy, 38(7), 872-890. (Cited by: 0)

Conclusion

Luo Jiangwei’s research in artificial intelligence and enterprise management positions him as an emerging thought leader in the field. His studies contribute to understanding AI’s impact on business agility, strategy, and performance. Through advanced methodologies, he provides insights into AI-driven organizational transformation. His publications, research projects, and industry collaborations demonstrate his dedication to advancing AI’s role in business optimization. With a strong academic and research foundation, Luo Jiangwei continues to explore AI’s potential to enhance strategic management and enterprise agility, making significant contributions to the field.