Zulqurnain Sabir | Artificial Neural Networks | Best Researcher Award

Published on by Environmental Scientists

Best Researcher Award

Zulqurnain Sabir
Lebanese American University, Lebanon

Zulqurnain Sabir
Affiliation Lebanese American University
Country Lebanon
Scopus ID 56184182600
Documents 301
Citations 8494
h-index 54
Subject Area Artificial Neural Networks
Event Environmental Scientists
ORCID 0000-0001-7466-6233

Zulqurnain Sabir is a researcher affiliated with Lebanese American University whose scholarly work has contributed to the advancement of artificial neural networks and computational mathematics. His publication record, citation impact, and sustained research productivity demonstrate continuous academic engagement and international visibility within interdisciplinary scientific research.[1]

Abstract

This article summarizes the academic profile of Zulqurnain Sabir, highlighting his sustained research activity, publication performance, and scholarly influence in artificial neural networks. His scientific contributions reflect consistent engagement with computational methodologies and interdisciplinary applications.[1]

Keywords

Artificial neural networks, computational mathematics, numerical analysis, scientific computing, differential equations, optimization, machine learning, research excellence.

Introduction

Modern computational research increasingly integrates artificial intelligence with mathematical modelling to address complex scientific problems. Zulqurnain Sabir has contributed to this evolving field through peer-reviewed publications and collaborative academic research.[2]

Research Profile

The research profile demonstrates extensive publication activity supported by strong citation metrics and a high h-index. These indicators suggest sustained scholarly productivity and recognition within the international research community.[1]

Research Contributions

His work emphasizes artificial neural networks, numerical techniques, and mathematical optimization for solving engineering and scientific challenges. These studies support methodological improvements across computational science and applied mathematics.[3]

Publications

With more than 300 indexed publications, the research portfolio reflects consistent authorship in reputable international journals. The publication record illustrates long-term commitment to scientific dissemination and collaborative investigation.[1]

Research Impact

Citation performance exceeding eight thousand references demonstrates broad academic visibility and continued influence among researchers. Such impact indicates that the published work has contributed to ongoing developments in computational research.[4]

Award Suitability

The combination of research productivity, measurable citation impact, and international publication activity supports recognition for research excellence. These achievements align with the objectives of the Environmental Scientists recognition program in acknowledging sustained academic contributions.[5]

Conclusion

Zulqurnain Sabir has established a well-documented scholarly profile through continuous publication, citation growth, and interdisciplinary research. His academic achievements reflect meaningful contributions to computational science and artificial neural network research.[1]

External Links

References

  1. Elsevier. (n.d.). Scopus author details: Zulqurnain Sabir, Author ID 56184182600. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56184182600
  2. ORCID. (n.d.). Zulqurnain Sabir ORCID record.
    https://orcid.org/0000-0001-7466-6233
  3. Sabir, Z., Muhammad, N., Zhang, S., & Khan, I. (2026). Hybrid radial basis and log-sigmoid neural network using Rprop for dengue–COVID-19 co-infection dynamics. SSRN Electronic Journal (Preprint).
    https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6910764
  4. Sabir, Z., Kobba, T., & Fadel, H. (2026). A computational design-based scale conjugate neural network to solve the nonlinear Rabinovich–Fabrikant model. Journal of Circuits, Systems and Computers. Advance online publication
    https://www.worldscientific.com/doi/10.1142/S0218126626501203
  5. Sabir, Z., Bichbich, I., Umar, M., Salahshour, S., & Bayram, M. (2026). An artificial neural network based on radial basis methodology using delay effects in the Parkinson’s disease model. Computational Biology and Chemistry, 115, Article 109033.

Victor Erokhin | Neuromorphic Computing | Best Researcher Award

Published on by Environmental Scientists

Best Researcher Award

Victor Erokhin
Consiglio Nazionale delle Ricerche (CNR), Italy

Victor Erokhin
Affiliation Consiglio Nazionale delle Ricerche (CNR)
Country Italy
Scopus ID 7102811560
Documents 227
Citations 4,859
h-index 38
Subject Area Neuromorphic Computing
Event International Environmental Scientists Award
ORCID 0000-0002-8754-0012

The Best Researcher Award recognizes researchers whose scholarly achievements demonstrate sustained scientific productivity, interdisciplinary influence, and measurable research impact. Victor Erokhin of the Consiglio Nazionale delle Ricerche (CNR), Italy, has established a significant academic profile through contributions spanning neuromorphic computing, information technologies, computational systems, innovation studies, and interdisciplinary scientific research. His publication record, citation performance, and international visibility support consideration for academic recognition within the framework of the International Environmental Scientists Award.[1]

Abstract

Victor Erokhin has developed a multidisciplinary research portfolio characterized by contributions to computational technologies, innovation systems, cybersecurity methodologies, and emerging computing paradigms. With more than two hundred indexed publications and thousands of citations, his work demonstrates both scientific breadth and sustained scholarly relevance. The combination of academic productivity, citation influence, and interdisciplinary engagement provides a strong basis for recognition through a distinguished research award.[1]

Keywords

Neuromorphic Computing; Computational Intelligence; Cybersecurity; Scientific Innovation; Information Technology; Research Impact; Academic Excellence.

Introduction

The advancement of modern science increasingly depends on researchers capable of bridging multiple disciplines while maintaining methodological rigor. Victor Erokhin’s scholarly activities reflect this approach through investigations into computing technologies, labor-market innovation, digital security, educational systems, and technology-driven societal transformation. His research contributes to understanding complex interactions between technological development and practical implementation across scientific domains.[2]

Research Profile

Based at the Consiglio Nazionale delle Ricerche (CNR), Erokhin maintains an active research profile with documented international visibility. His Scopus metrics indicate substantial publication output, citation accumulation, and a strong h-index. These indicators suggest sustained engagement with topics that attract scholarly attention and contribute to ongoing scientific discourse.[1]

Research Contributions

  • Advancement of neuromorphic and computational intelligence research.
  • Studies addressing cybersecurity challenges, shellcode detection, and malicious script identification.
  • Research examining technological innovation and labor-market transformation.
  • Contributions to educational technology assessment and digital infrastructure evaluation.
  • Investigations related to environmental policy, regional energy conservation, and sustainable development strategies.

Publications

  • Monitoring Methods and Assessment of Educational Organizations’ Websites to Enhance Their Content (2025).
  • Changes in the Labor Market with the Introduction of Scientific and Technological Innovations into the Economy (2023).
  • Search for Malicious PowerShell Scripts Using Syntax Trees (2023).
  • Ecology and Regional Energy Conservation Policy (2022).
  • Analysis and Improvement of Methods for Detecting Shellcodes in Computer Systems (2021).

Research Impact

The impact of Erokhin’s work is reflected through citation activity, publication longevity, and the diversity of fields influenced by his research. His studies connect theoretical advances with practical applications, particularly in computing technologies and innovation systems. Such influence demonstrates the capacity of his research to support both academic inquiry and evidence-based decision making.[3]

Award Suitability

Victor Erokhin’s extensive publication portfolio, established citation record, interdisciplinary scope, and sustained research productivity align with the evaluation criteria commonly associated with major international research awards. His contributions to technological innovation, cybersecurity, environmental policy studies, and advanced computing provide evidence of scholarly excellence and long-term academic engagement.[4]

Conclusion

The academic achievements of Victor Erokhin demonstrate a combination of productivity, interdisciplinary collaboration, and measurable scientific impact. His body of work supports continued advancement in computing, innovation research, cybersecurity, and sustainability-related studies. These accomplishments provide a strong foundation for recognition through the Best Researcher Award within the International Environmental Scientists Award program.[5]

References

  1. Elsevier. (n.d.). Scopus author details: Victor Erokhin, Author ID 7102811560. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=7102811560
  2. Erokhin, V. (2025). Monitoring Methods and Assessment of Educational Organizations’ Websites to Enhance Their Content.
    https://doi.org/10.35266/1999-7604-2025-3-7
  3. Erokhin, V. (2023). Changes in the Labor Market with the Introduction of Scientific and Technological Innovations into the Economy.
    https://doi.org/10.22394/2410-132X-2023-9-4-18-31
  4. Erokhin, V. (2023). Search for Malicious PowerShell Scripts Using Syntax Trees.
    https://doi.org/10.26583/bit.2023.3.05
  5. Erokhin, V. (2022). Ecology and Regional Energy Conservation Policy.
    https://doi.org/10.36871/ek.up.p.r.2022.04.02.013
  6. Erokhin, V. (2021). Analysis and Improvement of Methods for Detecting Shellcodes in Computer Systems.
    https://doi.org/10.37791/2687-0649-2021-16-2-103-122

Tuniyazi Abudoureheman | Intelligent Systems | Research Excellence Award

Published on by Environmental Scientists

Dr. Tuniyazi Abudoureheman | Intelligent Systems | Research Excellence Award

Dr. Tuniyazi Abudoureheman | Intelligent Systems | Hiroshima University | Japan

Dr. Tuniyazi Abudoureheman is a dedicated researcher and Ph.D. student at Hiroshima University whose work focuses on advanced sensing, machine vision, and robotic system diagnostics, contributing meaningfully to the fields of high-frame-rate (HFR) imaging, vibration analysis, and automated detection systems. Dr. Tuniyazi Abudoureheman began his academic journey with foundational studies that eventually led him to pursue graduate-level research, culminating in his current doctoral studies where he continues to expand his expertise in robotics and intelligent sensing technology. Throughout his professional experience, Dr. Tuniyazi Abudoureheman has actively engaged in collaborative research projects, working alongside multidisciplinary teams to design, implement, and validate methods involving HFR video, wing-beat frequency detection, and robot health monitoring across multiple postures. His early work also includes contributions to multi-target tracking using Kalman Filtering in complex environments, demonstrating both versatility and technical depth even before entering advanced doctoral research. The core research interests of Dr. Tuniyazi Abudoureheman include high-speed imaging, robotic vibration analysis, automated industrial inspection, bio-inspired detection systems, and machine vision algorithms, all of which align with the evolving demands of next-generation intelligent robotics. His research skills span HFR camera-based data acquisition, signal processing, vibration modeling, robotic motion evaluation, and applied machine learning, supported by strong analytical ability and experience with experimental system design. Dr. Tuniyazi Abudoureheman has also developed valuable competencies in publishing scientific results, presenting at conferences, and contributing to collaborative engineering investigations, which collectively strengthen his academic and professional profile. Although early in his academic career, Dr. Tuniyazi Abudoureheman has already earned recognition through peer-reviewed publications, citations, and participation in reputable conferences such as IEEE SENSORS, positioning him as an emerging scholar in robotics and sensing technology. His work has received growing scholarly attention, reflected in increasing citation counts and inclusion in respected journals covering robotics and mechatronics. In conclusion, Dr. Tuniyazi Abdurrahman continues to advance as a promising researcher whose technical contributions, methodological rigor, and commitment to innovation place him on a strong path toward future academic excellence and impactful scientific discovery.

Academic Profile: ORCID | Google Scholar

Featured Publications:

  1. Li, J., Shimasaki, K., Tuniyazi, A., Ishii, I., & Ogihara, M. (2023). HFR video-based hornet detection approach using wing-beat frequency analysis. 3 citations.

  2. Abudoureheman, T., Wang, F., Shimasaki, K., & Ishii, I. (2025). HFR-video-based vibration analysis of a multi-jointed robot manipulator. 1 citation.

  3. Abudoureheman, T., Otsubo, H., Wang, F., Shimasaki, K., & Ishii, I. (2025). High-frame-rate camera-based vibration analysis for health monitoring of industrial robots across multiple postures.