Mohammed Boudaoud | Robotics | Young Scientist Award

Young Scientist Award

      Mohammed Boudaoud
Affiliation Université Polytechnique Hauts-De-France
Country France
Scopus ID 59715904300
Documents 3
Citations 5
h-index 1
Subject Area Robotics
Event International Popular Scientist Awards
ORCID 0009-0009-2991-0394

Mohammed Boudaoud

Université Polytechnique Hauts-de-France

Mohammed Boudaoud  the Young Scientist Award recognizes emerging researchers whose scholarly activities demonstrate promising contributions within their respective academic disciplines. Mohammed Boudaoud, affiliated with Université Polytechnique Hauts-de-France, has established a developing research profile in robotics through scholarly publications indexed in Scopus. His research activities contribute to technological innovation while supporting continued advancement in robotics and intelligent engineering systems.[1]

Abstract

Mohammed Boudaoud’s academic profile reflects participation in robotics research with publications indexed in international scientific databases. His work contributes to engineering knowledge related to robotic technologies while demonstrating scholarly engagement at an early career stage. Bibliometric indicators, including indexed publications, citations, and author metrics, provide measurable evidence of research activity suitable for academic evaluation.[1]

Keywords

Robotics, Intelligent Systems, Automation, Engineering Research, Young Scientist, Scopus Author, France, Research Publications, Academic Recognition, Innovation.

Introduction

The Young Scientist Award acknowledges researchers who have demonstrated measurable academic progress during the early stages of their careers. Evaluation commonly considers publication quality, research visibility, scholarly impact, institutional affiliation, and future research potential. Mohammed Boudaoud’s research profile represents ongoing contributions within robotics and aligns with internationally recognized academic assessment criteria.[1]

Research Profile

Affiliated with Université Polytechnique Hauts-de-France, Mohammed Boudaoud conducts research within the field of robotics. His Scopus author profile reports three indexed publications, five citations, and an h-index of one, indicating the early development of his scholarly record. These bibliometric indicators provide a transparent overview of academic productivity and research dissemination.[2]

Research Contributions

Robotics and Intelligent Engineering recognizes outstanding research contributions that advance robotics, automation, artificial intelligence, and intelligent systems. It honors researchers for impactful peer-reviewed publications, innovative technological developments, and internationally indexed scholarly achievements that drive progress in intelligent engineering and robotic applications.

Publications

The researcher’s publications are indexed in the Scopus database and contribute to the robotics literature. Individual publications include persistent identifiers such as Digital Object Identifiers (DOIs), facilitating permanent scholarly citation and accessibility where assigned by publishers.[3]

Research Impact

Research impact can be assessed through bibliometric indicators including citation counts, publication indexing, and h-index values. Although the research profile represents an early stage of academic development, existing publications demonstrate visibility within recognized scientific databases and establish a foundation for future scholarly growth.[2]

Award Suitability

Based on publicly available academic metrics, Mohammed Boudaoud demonstrates characteristics commonly associated with emerging researchers, including indexed scholarly publications, measurable citation activity, institutional research engagement, and specialization in robotics. These objective indicators support consideration for recognition programs focused on early-career scientific achievement while acknowledging that final award decisions depend upon the evaluation criteria established by the awarding organization.[4]

Conclusion

Mohammed Boudaoud’s academic profile illustrates an emerging contribution to robotics research through internationally indexed publications and measurable scholarly activity. Continued research productivity, collaboration, and scientific dissemination may further enhance the visibility and impact of his work within the international robotics community.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Mohammed Boudaoud, Author ID 59715904300. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=59715904300
  2. ORCID. (n.d.). Researcher Profile: Mohammed Boudaoud.
    https://orcid.org/0009-0009-2991-0394
  3. Crossref. (n.d.). Digital Object Identifier (DOI) Foundation. DOI reference information.
  4. International Popular Scientist Awards. (n.d.). Award information and nomination details.
    https://popularscientist.com/
  5. Boudaoud, M., Puig, V., Sentouh, C., El Najjar, M. E., & Cappelle, C. (2026). Zonotopic set-based fault detection for driver behavior monitoring. Control Engineering Practice.

Huaiqu Feng | Robot | Best Researcher Award

Dr. Huaiqu Feng | Robot | Best Researcher Award

Zhejiang University | China

Huaiqu Feng is an accomplished researcher and engineer from China with a strong academic background in agricultural mechanization engineering and automation. He completed his undergraduate studies in Automation at Hubei Normal University, where he built a solid foundation in control theory, intelligent systems, signal processing, and electronics. He then pursued a master’s degree in Agricultural Mechanization Engineering at Northeast Agricultural University, focusing on areas such as image processing, deep learning, computer vision, and advanced agricultural mechanics. His research interests center on the integration of intelligent control systems and machine vision technologies to improve agricultural equipment and automation. He has contributed to several scientific papers submitted to international SCI-indexed journals, addressing topics such as deep learning-based corn kernel selection and targeted pesticide spraying platforms. His research output includes 20 documents with 431 citations by 376 documents, reflecting his growing impact in the scientific community. His innovative work is also demonstrated through multiple patents for agricultural machinery and software copyrights related to neural network-based prediction and measurement systems. He has received various scholarships and awards for academic excellence and innovation, including recognition in national competitions such as the “Blue Bridge Cup” and the “Huawei Cup.” Beyond his technical achievements, he has demonstrated leadership through active involvement in student organizations, academic committees, and innovation programs, leading teams in robotics and intelligent control system design. His multidisciplinary expertise bridges automation, machine learning, and agricultural engineering, contributing to the advancement of smart farming technologies.

Profile: Scopus

Featured Publications

Feng, Huaiqu (2025). TD-CFD-DPM coupled method for multi-objective optimization of collision pollination parameters in hybrid rice seed production. Smart Agricultural Technology.

Feng, Huaiqu (2025). nUGV-1UAV robot swarms: Low-altitude remote sensing-based decentralized planning framework in-field environments. ISPRS Journal of Photogrammetry and Remote Sensing.