Mohammed AlAmeri | Artificial Intelligence | Innovative Research Award

Innovative Research Award

Mohammed AlAmeri 
Khalifa University , United Arab Emirates

Mohammed AlAmeri
Affiliation Khalifa University
Country United Arab Emirates
Scopus ID 57203369001
Documents 14
Citations 40
h-index 5
Subject Area Artificial Intelligence
Event New Scientists Awards

Mohammed AlAmeri is a researcher affiliated with Khalifa University in the United Arab Emirates, with scholarly contributions associated with the field of Artificial Intelligence and computational technologies. His research profile reflects participation in scientific investigations involving intelligent systems, machine learning methodologies, and data-driven analytical approaches relevant to contemporary digital innovation. Indexed academic records demonstrate measurable scholarly engagement through publication activity, citation performance, and interdisciplinary research dissemination.[1]

Abstract

This article presents a structured academic overview of the research profile and scholarly contributions of Mohammed AlAmeri in the field of Artificial Intelligence. The profile highlights publication visibility, citation performance, and interdisciplinary scientific engagement associated with intelligent systems and computational technologies. Indexed academic records demonstrate participation in peer-reviewed research dissemination and measurable scholarly activity relevant to contemporary Artificial Intelligence research domains. The article further evaluates the suitability of the researcher for recognition within the New Scientists Awards program.[2]

Keywords

Artificial Intelligence; Machine Learning; Intelligent Systems; Computational Intelligence; Data Analytics; AI Research; Scientific Publications; Interdisciplinary Computing; Research Impact; Academic Recognition

Introduction

Artificial Intelligence has become one of the most transformative scientific and technological fields of the twenty-first century, influencing areas such as automation, predictive analytics, robotics, healthcare systems, cybersecurity, and smart infrastructure. Contemporary AI research integrates computer science, mathematics, engineering, and data science to develop intelligent computational systems capable of advanced learning and decision-making processes.[3]

 His scholarly profile reflects measurable academic participation through indexed publications, citation activity, and interdisciplinary research dissemination relevant to Artificial Intelligence and digital innovation.[1]

Research Profile

Mohammed AlAmeri is affiliated with Khalifa University and maintains an academic profile indexed within internationally recognized scholarly databases. His research metrics include citation-based indicators and publication records associated with Artificial Intelligence and related computational research areas. The profile reflects participation in peer-reviewed scientific dissemination and interdisciplinary collaboration.[1]

Research Contributions

The research contributions associated with Mohammed AlAmeri involve scientific activities related to Artificial Intelligence methodologies, intelligent computational systems, and data-driven analytical approaches. Such contributions are relevant to the advancement of machine learning applications, predictive modeling, and automated decision-support technologies used across multiple scientific and industrial sectors.[4]

Publication records and indexed citation activity indicate participation in peer-reviewed scientific communication and interdisciplinary collaboration. The integration of Artificial Intelligence into engineering, information systems, and technological innovation frameworks further emphasizes the contemporary relevance of this research domain.[2]

Publications

The publication profile of Mohammed AlAmeri demonstrates scholarly engagement with Artificial Intelligence and computational research themes through peer-reviewed academic dissemination. Indexed scientific outputs contribute to interdisciplinary discussions associated with intelligent systems and emerging digital technologies.[5]

  1. Peer-reviewed publications related to Artificial Intelligence methodologies and intelligent systems.
  2. Research outputs indexed through Scopus and other scholarly databases.
  3. Scientific contributions involving machine learning and computational analytics.
  4. Interdisciplinary publications associated with technological innovation and data science applications.

Research Impact

Research impact within Artificial Intelligence is frequently evaluated through publication dissemination, citation accumulation, and interdisciplinary scientific relevance. Mohammed AlAmeri’s academic profile includes indexed publications and citation activity demonstrating measurable engagement within the scientific research community. Citation-based indicators further support the visibility of his scholarly contributions within computational and AI-related research domains.[2]

The availability of indexed academic records through Scopus provides additional evidence of research accessibility and scholarly dissemination. Such indicators are commonly utilized within academic evaluation frameworks and scientific recognition programs to assess publication visibility and research influence.[1]

Award Suitability

The academic profile of Mohammed AlAmeri demonstrates characteristics commonly associated with eligibility for scientific recognition programs, including publication activity, interdisciplinary collaboration, and participation in emerging technological research domains. His work in Artificial Intelligence aligns with contemporary scientific priorities focused on intelligent systems, digital transformation, and computational innovation.[4]

The documented publication metrics, citation indicators, and interdisciplinary research relevance associated with Mohammed AlAmeri support consideration for recognition within the Innovative Research Award category.[5]

Conclusion

Mohammed AlAmeri has established a developing academic profile within the field of Artificial Intelligence through publication activity, indexed research dissemination, and scholarly engagement in computational research domains.  The documented academic contributions collectively support recognition within international scientific award initiatives focused on research excellence and emerging innovation.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Mohammed AlAmeri, Author ID 57203369001. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57203369001
  2. Elsevier. (n.d.). Research metrics and scholarly indexing for Artificial Intelligence publications. Scopus Database.
    https://www.scopus.com/
  3. Stanford Encyclopedia of Philosophy. (n.d.). Artificial Intelligence overview and scientific foundations.
    https://plato.stanford.edu/entries/artificial-intelligence/
  4. DOI Foundation. (2021). Artificial Intelligence and intelligent systems research publication.
    https://doi.org/10.1016/j.artint.2021.103558
  5. New Scientists Awards. (n.d.). International scientific recognition and academic excellence initiative.
    https://newscientists.net/

Hui Lyu | Artificial Intelligence and Machine Learning | Best Researcher Award

Dr. Hui Lyu | Artificial Intelligence and Machine Learning | Best Researcher Award

Student, Zibo Normal College | China

Dr. Hui Lyu is an interdisciplinary researcher specializing in complex-valued neural networks, infrared image enhancement, intelligent signal processing, data fusion, and optimization-based machine learning. Her peer-reviewed output includes 4 SCI-indexed journal articles and international conference papers, with publications in IEEE Sensors Journal, IEEE Access, Neural Processing Letters, and Signal, Image and Video Processing. Her research integrates adaptive convolutional filtering, quaternion extreme learning machines, and multisensor fault diagnosis frameworks. She is a contributor to national and municipal funded research on infrared vision systems, sensor testing, and complex neural learning algorithms, and holds 5 granted invention patents in infrared imaging and intelligent detection systems. Her work has received regional scientific achievement recognition.

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Manickam S | Artificial Intelligence and Machine Learning | Research Excellence Award

Mr. Manickam S | Artificial Intelligence and Machine Learning | Research Excellence Award

Assistant Professor | Saveetha Engineering College | India

Mr. Manickam S is an emerging researcher in Artificial Intelligence and Machine Learning, with focused contributions spanning data analytics, secure systems, intelligent networks, and applied AI for real-world optimization. His scholarly output includes peer-reviewed journal and international conference publications addressing graph-based road network optimization, learning-assisted pathfinding, and cryptographic multi-server authentication using elliptic curve digital signatures. His research demonstrates strong integration of machine learning algorithms with networking, security, and intelligent transportation systems. Mr. Manickam S has an active innovation portfolio, with multiple Indian patents published and granted in domains such as IoT-enabled robotics, smart agriculture, edge-AI energy monitoring, cloud-integrated IoT resource allocation, solar panel automation, and AI-driven healthcare analytics. His work reflects a translational R&D orientation, emphasizing scalable, deployable intelligent systems. According to Google Scholar, he has 8 citations across 3 research documents with an h-index of 1. He has received recognition for academic innovation and contributes to the research ecosystem through conference participation, interdisciplinary AI research, and technology-driven problem solving.

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Featured Publications

Secure multi server authentication system using elliptic curve digital signature
– IEEE ICCPCT Conference Proceedings, 2016 | Citations: 8

Optimizing Road Networks: A Graph-Based Analysis with Path-finding and Learning Algorithms
– International Journal of Intelligent Transportation Systems Research, 2024

Asif Muzaffar | Artificial Intelligence and Machine Learning | Research Excellence Award

Dr. Asif Muzaffar | Artificial Intelligence and Machine Learning | Research Excellence Award

Teaching Fellow | Birmingham City University | United Kingdom

Dr. Asif Muzaffar is a recognized researcher in Operations and Supply Chain Management, known for advancing quantitative modelling, sustainable operations, and digital supply chain innovation. With 816 citations, 45 documents, an h-index of 16, and an i10-index of 17, his scholarly influence is reflected through publications in leading journals, including Sustainable Production and Consumption, Sustainable Development, Operations Management Research, Technological Forecasting & Social Change, International Journal of Disaster Risk Reduction, and the Journal of Services Marketing. His research portfolio encompasses 21 peer-reviewed journal papers, multiple conference contributions, and ongoing works addressing dynamic pricing, newsvendor models, sustainable procurement, and consumer behavior in digital environments. Dr. Asif Muzaffar’s contributions span supply chain contracts, institutional pressures, triple bottom line sustainability, rebate mechanisms, and technology-enabled service innovations such as AR/VR. His work often integrates simulation modelling, optimization, and game-theoretic frameworks to generate actionable insights for resilient, low-carbon, and digitally enabled supply chain systems. He has disseminated his findings at major international conferences, contributing evidence-based perspectives on biased decision-making, rebate coordination, and supply chain optimization. His research leadership extends to mentoring graduate research, shaping sustainable supply chain methodologies, and contributing as a reviewer for high-impact journals including Technological Forecasting & Social Change and Sustainable Development. Through these scholarly contributions, Dr. Asif Muzaffar has established himself as an influential voice in contemporary sustainable operations and supply chain research.

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