Sultan Ahmad | Artificial Intelligence | Best Researcher Award

Best Researcher Award

Sultan Ahmad
Prince Sattam bin Abdulaziz University
Sultan Ahmad
Affiliation Prince Sattam bin Abdulaziz University
Country Saudi Arabia
Scopus ID 57194429140
Documents 150
Citations 2389
h-index 27
Subject Area Artificial Intelligence
Event The Scientist Global Awards
ORCID 0000-0002-3198-7974

Sultan Ahmad is affiliated with Prince Sattam bin Abdulaziz University in Saudi Arabia and has established a notable research profile in the field of Artificial Intelligence. His scholarly contributions encompass interdisciplinary applications of intelligent systems, computational methodologies, and data-driven technologies. The academic recognition associated with the Best Researcher Award reflects sustained research productivity, international visibility, and measurable scholarly influence demonstrated through publications, citations, and collaborative scientific engagement.[1] The evaluation criteria for the award emphasize scientific quality, publication consistency, research impact, and contribution to the advancement of contemporary Artificial Intelligence research.[2]

Abstract

The Best Researcher Award recognizes academic excellence, sustained scholarly productivity, and impactful scientific contributions within the field of Artificial Intelligence. Sultan Ahmad has demonstrated a substantial record of publication activity and citation performance, supported by a recognized international research profile. His work reflects engagement with advanced computational methodologies, intelligent systems, and interdisciplinary innovation in Artificial Intelligence research.[1] The award evaluation framework considers research visibility, scholarly influence, citation metrics, and the broader significance of contributions to scientific and technological advancement.[2]

Keywords

Artificial Intelligence, Intelligent Systems, Machine Learning, Computational Research, Data Analytics, Scientific Publications, Citation Impact, Academic Excellence, Research Recognition, Interdisciplinary Innovation

Introduction

The field of Artificial Intelligence has experienced significant expansion in recent decades due to rapid advancements in computational infrastructure, algorithmic development, and data-driven technologies. Researchers in this domain contribute to diverse applications including automation, predictive analytics, intelligent decision-making, and human-computer interaction. Academic awards in this area are intended to recognize researchers whose work demonstrates measurable scholarly influence and long-term scientific value.[3]

Research Profile

The research profile of Sultan Ahmad demonstrates interdisciplinary engagement in Artificial Intelligence with a focus on computational methods, intelligent systems, and applied analytical frameworks. His scholarly output includes peer-reviewed publications indexed within internationally recognized databases. According to Scopus author metrics, the researcher has produced 150 indexed documents and accumulated 2389 citations, resulting in an h-index of 27.[1]

Research Contributions

Research contributions associated with Sultan Ahmad include scholarly investigations related to intelligent computation, data processing methodologies, and Artificial Intelligence-based analytical systems. Such contributions are significant within contemporary research environments where computational intelligence supports scientific modeling, automation, and predictive technologies.[3]

Publications

The publication record associated with Sultan Ahmad reflects sustained academic productivity and contribution to internationally indexed scientific literature. Publication activity in Artificial Intelligence commonly involves interdisciplinary collaboration, computational experimentation, and theoretical development supported by peer review processes.[1]. Representative DOI references relevant to Artificial Intelligence research and computational studies include internationally accessible digital identifiers that facilitate long-term scholarly retrieval and citation tracking.[5]

Research Impact

Research impact is commonly evaluated through citation analysis, publication indexing, scholarly visibility, and interdisciplinary relevance. The citation record of Sultan Ahmad demonstrates measurable influence within the research community and indicates that published work has contributed to ongoing scientific discussions and technological development.[1] An h-index of 27 reflects a balanced combination of publication productivity and citation performance. Such indicators are frequently used in academic assessment processes to evaluate long-term scientific contribution and the broader dissemination of research findings within international scholarly networks.[6]

Award Suitability

The Best Researcher Award emphasizes scientific quality, measurable research performance, publication consistency, and contribution to the advancement of knowledge. Sultan Ahmad’s research metrics and scholarly record demonstrate alignment with these evaluation principles. His publication output, citation influence, and academic engagement collectively support recognition within the context of international scientific achievement.[2]

Conclusion

Sultan Ahmad has established a recognized academic profile through sustained research activity in Artificial Intelligence and related computational disciplines. The documented publication record, citation performance, and scholarly visibility demonstrate ongoing contribution to scientific advancement and interdisciplinary technological research. The Best Researcher Award represents an acknowledgment of these achievements within an international academic framework dedicated to recognizing research excellence and scientific impact.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Sultan Ahmad, Author ID 57194429140. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57194429140
  2. The Scientist Global Awards. (n.d.). Research recognition and academic excellence award framework.
    https://thescientists.net/
  3. Measurement. (2026). An enhanced control strategy using ANFIS-FOPID for grid-tied DFIG based WECS with battery storage for better Sustainable Urban Environments. https://doi.org/10.1016/j.measurement.2025.120145
  4. Frontiers in Medicine. (2026). A scalable and reliable deep learning framework for enhanced brain tumor detection and diagnosis using AI-based medical imaging. https://doi.org/10.3389/fmed.2026.1738796
  5. Journal of Advances in Information Technology. (2026). PolyVision: Optimising Retinal Disease Detection Through Collaborative Neural Networks. https://doi.org/10.12720/jait.17.1.55-64
  6. Blockchain, Artificial Intelligence, and Future Research (2026). Can Generative AI Be a Solution or a Threat to Creative Industry Professionals? Assessing Readiness with the Rasch Model. https://doi.org/10.70211/bafr.v2i1.410

 

Christian Schachtner | Data Science | Research Excellence Award

Prof. Dr. Christian Schachtner | Data Science | Research Excellence Award

Full Professor Digital Public Administration | Hochschule RheinMain | Germany

Prof. Dr. Christian Schachtner is a Professor of Administrative Digitalization whose work focuses on digital transformation, organizational change, smart government, public law, sustainability, and new learning in the public sector. His research has significantly contributed to understanding smart city strategies, chief digital officer (CDO) roles, agile governance, and data-based public management. He has authored and co-authored over 20 scholarly publications, including articles in Smart Cities, Verwaltung und Management, and international conference proceedings. His work has received 98 citations, with an h-index of 6 and an i10-index of 3, reflecting growing academic and practical impact. Through interdisciplinary and international collaborations, his research supports municipalities in designing resilient, citizen-centered, and digitally enabled governance systems, directly influencing public sector modernization and sustainable administrative innovation.

Citation Metrics (Google Scholar)

98
75
50
25
0

Citations

98

h-index

6

i10-index

3

Citations

h-index

i10-index

View Google Scholar Profile
View Scopus Profile View ORCID Profile

Featured Publications


Smart government in local adoption

– ORAȘE INTELIGENTE ȘI DEZVOLTARE REGIONALĂ, 2021 . | Citations: 21.


New Work im öffentlichen Sektor?!

– Verwaltung und Management, 2019. | Citations: 10.


Handbuch Digitalisierung der Verwaltung

– utb, 2023. | Citations: 8.


Wise governance: Elements of the digital strategies of municipalities

– ORAȘE INTELIGENTE ȘI DEZVOLTARE REGIONALĂ, 2022. | Citations: 8.

Jamal Zraqou | Machine Learning | Research Excellence Award

Assoc. Prof. Dr. Jamal Zraqou | Machine Learning | Research Excellence Award

Associate Professor | University of Petra | Jordan

Assoc. Prof. Dr. Jamal S. Zraqou is an active researcher with demonstrated contributions across data-driven engineering, machine learning, cybersecurity, and digital transformation. He has authored 45 scholarly documents indexed in Scopus, accumulating 202 citations with an h-index of 9, reflecting consistent academic impact. His recent work addresses optimization techniques for engineering design, advanced machine learning methods for phishing detection, cybersecurity vulnerability analysis, and the strategic role of business intelligence in digital transformation. Dr. Zraqou has collaborated with a broad international network of over 60 co-authors, highlighting interdisciplinary and cross-sector engagement. His research supports practical problem-solving in engineering systems, information security, and decision intelligence, contributing to improved technological resilience, safer digital environments, and enhanced organizational competitiveness at societal and industrial levels.

Citation Metrics (Scopus)

202
150
100
50
0

Citations

202

Documents

45

h-index

9

Citations

Documents

h-index

View Google Scholar Profile
View Scopus Profile
View ORCID Profile

Featured Publications

Saifullah Khalid | Artificial Intelligence | Innovative Research Award

Dr. Saifullah Khalid | Artificial Intelligence | Innovative Research Award

Principal Scientist | IBMM RESEARCH | Sudan

Dr. Saifullah Khalid is a distinguished aviation and aerospace researcher renowned for his groundbreaking work in AI-driven aviation systems, air traffic management optimization, and unmanned aerial systems. With dual PhDs in engineering and a career spanning advanced aeronautical research, he serves as Principal Scientist at IBMM Research, Sudan. His academic background includes a PhD in Electronics and Communication Engineering from SN University, India (2013). Dr. Khalid’s expertise encompasses autonomous UAV systems, quantum-inspired optimization algorithms, sustainable aviation power systems, and digital tower operations. He has authored over 270 publications, including 38 Web of Science-indexed papers, and holds an impressive portfolio of 85 patents—50 as sole inventor—setting two world records for patent achievements. His professional experience extends to teaching and mentoring, supervising PhD candidates in AI-based air route optimization and guiding over 200 engineering projects. A committed academic leader, he has developed ICAO-compliant curricula and serves as Vice Chairman of the Academic Council Asia at NextGen University International. His awards include world records for patent excellence and international recognition for research innovation. His technical skills span MATLAB/Simulink, Python, UAV system design, and AI applications in aviation. 305 Citations; 67 Documents; h-index: 10

Profiles: Google scholar | Scopus | ORCID | ResearchGate

Featured Publications

  1. Khalid, S., & Dwivedi, B. (2011). Power quality issues, problems, standards & their effects in industry with corrective means. International Journal of Advances in Engineering & Technology, 1(2), 1–11. Citations: 167

  2. Nishad, D. K., Tiwari, A. N., Khalid, S., Gupta, S., & Shukla, A. (2024). AI-based UPQC control technique for power quality optimization of railway transportation systems. Scientific Reports, 14(1), 17935. Citations: 31

  3. Khalid, S. (2018). Performance evaluation of Adaptive Tabu Search and Genetic Algorithm optimized shunt active power filter using neural network control for aircraft power utility of 400 Hz. Journal of Electrical Systems and Information Technology, 5(3), 723–734. Citations: 30

  4. Khalid, S., Dwivedi, B., Kumar, N., & Agrawal, N. (2007). A review of state-of-art techniques in active power filters and reactive power compensation. National Journal of Technology, 3(1), 10–18. Citations: 26

  5. Khalid, S., & Dwivedi, B. (2010). Power quality: An important aspect. International Journal of Engineering Science and Technology, 2(11), 6485–6490. Citations: 25