Mohammed Boudaoud | Robotics | Young Scientist Award

Published on by International Popular Scientist Awards

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.

Oleg Maschev | Robotics | Innovative Research Award

Published on by International Popular Scientist Awards

Innovative Research Award

Oleg Maschev
Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”

                 Oleg Maschev
Affiliation Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM”
Country Russia
Documents 1
Subject Area Robotics
Event International Popular Scientist Awards
ORCID 0009-0002-1846-2126

Oleg Maschev the Innovative Research Award article presents a scholarly overview of Oleg Maschev and his professional association with the Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM.” The profile highlights contributions within the field of robotics and evaluates the relevance of the researcher’s work to the objectives of the International Popular Scientist Awards. The article follows a neutral encyclopedic structure designed for academic recognition and research assessment.[1]

Abstract

This article documents the academic and research profile of Oleg Maschev in the area of robotics and agroengineering innovation. Affiliated with the Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM,” the researcher contributes to technological advancement through scientific investigation and engineering applications. The profile is presented in the context of evaluating eligibility and relevance for recognition through the International Popular Scientist Awards, which emphasize innovation, scientific contribution, and societal benefit.[2]

Keywords

Robotics, agroengineering, and automation systems are transforming modern industries through scientific innovation. Engineering research drives technology development, enhancing productivity, sustainability, precision, and efficiency while creating advanced solutions for agricultural and industrial challenges.

Introduction

Robotics continues to transform industrial, agricultural, and scientific environments through automation, intelligent systems, and data-driven operational models. Researchers working in this discipline contribute to productivity improvements, precision control technologies, and sustainable engineering solutions. Oleg Maschev’s affiliation with a specialized agroengineering research institution positions his work within a field where robotics can significantly influence agricultural modernization and technological efficiency.[1]

Research Profile

Oleg Maschev is associated with the Federal State Budgetary Scientific Institution “Federal Scientific Agroengineering Center VIM,” a research organization engaged in advancing engineering technologies relevant to agricultural systems and mechanized processes. The researcher’s documented activity is categorized within the subject area of robotics, reflecting involvement in technological development, system optimization, and engineering innovation.[3]

The available academic documentation demonstrates participation in scientific work that aligns with contemporary research directions involving automation, intelligent machinery, and the integration of advanced engineering methodologies within applied environments.[3]

Research Contributions

Research contributions within robotics commonly address challenges associated with machine autonomy, sensor integration, adaptive control mechanisms, and operational efficiency. The institutional environment in which Oleg Maschev conducts research supports multidisciplinary engineering approaches intended to enhance technological performance and practical implementation.[3]

Publications

Available records indicate one documented scholarly contribution associated with the researcher. Although detailed bibliographic information is limited within the provided dataset, the publication contributes to the researcher’s academic profile and serves as evidence of participation in formal scientific dissemination processes.[4]

Research Impact

The impact of robotics research extends beyond laboratory settings by supporting industrial modernization, precision operations, and sustainable engineering practices. Research conducted within agroengineering contexts contributes to technological readiness and promotes practical adoption of advanced systems. Such work is relevant to broader scientific goals involving efficiency, innovation, and digital transformation.[5]

The researcher’s institutional affiliation suggests engagement with scientific initiatives intended to address contemporary engineering challenges through evidence-based technological development and applied innovation.[3]

Award Suitability

The International Popular Scientist Awards recognize individuals whose research activities demonstrate scientific relevance, innovation, and potential societal value. Based on the available profile information, Oleg Maschev’s involvement in robotics research and affiliation with a specialized scientific institution align with key evaluation considerations frequently associated with research recognition programs.[2]

Conclusion

Oleg Maschev represents a research profile connected to the advancement of robotics within an agroengineering framework. Through institutional engagement and documented scholarly activity, the researcher contributes to ongoing technological development and scientific progress. The profile demonstrates characteristics consistent with academic recognition initiatives that value innovation, technical expertise, and contributions to applied research.[1]

References

  1. ORCID. (n.d.). Oleg Maschev ORCID profile,
    https://orcid.org/0009-0002-1846-2126
  2. International Popular Scientist Awards. (n.d.). Award objectives, evaluation criteria, and scientific recognition framework.
    https://popularscientist.com/
  3. Federal Scientific Agroengineering Center VIM. (n.d.). Institutional research activities and engineering innovation programs.
  4. Crossref. (n.d.). Digital Object Identifier (DOI) registration and scholarly publication indexing resources.
  5. Elsevier. (n.d.). Research trends in robotics, automation, and engineering innovation.

Peng Bo | Robotics | Excellence in Scientific Innovation Award

Published on by International Popular Scientist Awards

Dr. Peng Bo | Robotics | Excellence in Scientific Innovation Award

Tsinghua University | China

Dr. Peng Bo is a researcher specializing in control systems, networked autonomous vehicles, and advanced filtering techniques, with a focus on H∞ filtering and event-based control methods for complex networked systems. His work integrates rigorous mathematical modeling, augmented Lyapunov functional approaches, and innovative algorithm design to enhance stability, performance, and reliability in mass-switching autonomous multi-vehicle systems. With a strong foundation in system dynamics and networked control, he has contributed to several high-impact publications, demonstrating a practical yet theoretically robust research approach. His research has influenced both academic developments and real-world applications in intelligent transportation and autonomous systems, reflecting measurable impact through citations and collaborative contributions in his field. Dr. Peng Bo continues to advance methodologies for robust control and optimization in interconnected, dynamic environments.

Citation Metrics (Scopus)

20

15

10

5

0

Citations
10

Documents
5

h-index
2

🟦 Citations   🟥 Documents   🟩 h-index


View Scopus Author Profile

Featured Publications

Jinglin Li | Computer Science | Best Researcher Award

Published on by International Popular Scientist Awards

Mr. Jinglin Li | Computer Science | Best Researcher Award

Engineer | China National Nuclear Corporation | China

Li Jinglin is a researcher specializing in intelligent systems, reinforcement learning, and energy-efficient technologies for industrial and service applications. He holds advanced degrees in Instrument Science and Technology, Electrical Engineering, and Vehicle Engineering with a focus on new energy systems. His research encompasses the development of intelligent interactive service technologies for elderly care, optimization of energy-harvesting wireless sensor networks, and multi-task scheduling for energy-secured unmanned vehicles. He has led projects on digital twin platform technologies and vertical displacement control of nuclear fusion plasma, applying deep reinforcement learning to enhance system performance and replace traditional control methods. Li has extensive experience in algorithm design, including MATLAB-based reinforcement learning, adaptive dynamic programming, and multi-level exploration deep Q-network scheduling, with applications in optimal microgrid transmission, mobile charging sequence scheduling, and network monitoring. His work has resulted in multiple first-author publications in high-impact journals covering reinforcement learning, wireless sensor networks, and energy management, as well as conference contributions in control and automation. Beyond his technical expertise, he demonstrates strong analytical, problem-solving, and team collaboration skills, with experience in summarizing complex research findings and implementing practical solutions. Li actively engages in academic presentations and has earned recognition for his research achievements. In addition to his research, he maintains leadership roles in university sports teams, reflecting his commitment to teamwork, discipline, and resilience. His professional approach combines a proactive mindset, logical thinking, and a dedication to advancing intelligent and sustainable technological solutions across both industrial and service domains.

Profile: Scopus

Featured Publications

Li, J. (2024). A deep reinforcement learning approach for online mobile charging scheduling with optimal quality of sensing coverage in wireless rechargeable sensor networks. Ad Hoc Networks, 156, 103431.

Li, J. (2024). A reinforcement learning based mobile charging sequence scheduling algorithm for optimal sensing coverage in wireless rechargeable sensor networks. Journal of Ambient Intelligence and Humanized Computing, 15(6), 2869–2881.

Li, J. (2023). Mobile charging sequence scheduling for optimal sensing coverage in wireless rechargeable sensor networks. Applied Sciences, 13(5), 2840.

Li, J. (2024). A reinforcement learning based mobile charging sequence scheduling algorithm for optimal stochastic event detection in wireless rechargeable sensor networks. IEEE Transactions on Network and Service Management.

Li, J. (2024). A swarm deep reinforcement learning based on-demand mobile charging-scheduling and charging-time control joint algorithm for optimal stochastic event detection in wireless rechargeable sensor networks. Expert Systems with Applications.