Mr. Zhenyu Liu | Simulation Algorithms | Best Researcher Award

Inner Mongolia Agricultural University | China

Zhenyu Liu is a master’s degree candidate at the College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, specializing in agricultural engineering and information technology with a strong research focus on smart agricultural equipment and simulation-based optimization. His scholarly contributions include peer-reviewed publications indexed in SCI and Scopus, accompanied by documented citations and available research records. His Scopus profile reflects two indexed documents with an h-index of one, while Google Scholar also lists his publications and citations, verifying his emerging academic presence. His research documents, citation metrics, and publication outputs collectively highlight his early but impactful scientific development.

Publication Profile

Scopus

Education Background

Zhenyu Liu is currently pursuing a master’s degree at the College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, where he has developed a strong foundation in agricultural engineering, information technology, and intelligent equipment design. His coursework emphasizes agricultural machinery systems, discrete element simulations, and engineering data analysis. His academic journey is supported by participation in nationally guided scientific development projects, where he has gained experience in research documentation, simulation modeling, and practical field experimentation. His education further includes training in advanced software tools and exposure to interdisciplinary agricultural technologies that strengthen his capability for independent research and scientific publication.

Professional Experience

Zhenyu Liu has developed his professional experience through active involvement in research tasks within a Central Government Guided Local Science and Technology Development Fund Project, where he contributed to simulation design, model calibration, and mechanical interface analysis. His experience includes operation of agricultural machinery, execution of engineering experiments, and preparation of research documents for scientific dissemination. He has collaborated with faculty teams in analyzing agricultural material behavior using EDEM, preparing manuscripts for SCI journals, and documenting experimental outcomes. His professional exposure also extends to patent development, agricultural equipment evaluation, and contributing to collaborative academic outputs verified through Scopus and Google Scholar records.

Awards and Honors

Zhenyu Liu’s achievements include securing three authorized Chinese utility model patents related to agricultural machinery design and optimization, reflecting his commitment to research innovation. His publications in SCI-indexed journals demonstrate recognized scientific contribution, supported by citation records that validate his research impact. His documented output in Scopus and Google Scholar enhances his academic credibility, while participation in government-funded scientific research adds value to his professional development. Although early in his career, these accomplishments serve as evidence of his dedication to advancing agricultural engineering knowledge and earning academic recognition through verifiable documents, indexed publications, and measurable citation performance.

Research Focus

Zhenyu Liu’s research centers on smart agricultural machinery, discrete element simulation, agricultural material behavior modeling, and engineering optimization for crop mechanization. His work emphasizes calibration of simulation parameters, analysis of seed-material interactions, and evaluation of agricultural equipment performance through experimental validation. With publications indexed in SCI and Scopus, his research outputs are supported by documented citations and scholarly visibility across recognized databases. His focus also includes improving agricultural production efficiency using computational tools, advancing interface modeling of agricultural materials, and contributing verified scientific findings through peer-reviewed articles and research documents that showcase his growing academic and technical expertise.

Publications

Liu, Z., Yan, J., Liu, F., & Wang, L. (2025). Calibration and testing of discrete element simulation parameters for the presoaked Cyperus esculentus L. rubber interface using EDEM. Agronomy. Cited by documented sources in Scopus.

Yan, J., Liu, Z., & Liu, F. (2025). Calibration and analysis of seeding parameters of soaked Cyperus esculentus L. seeds. Applied Sciences. Cited by one Scopus-indexed article.

Assoc. Prof. Dr. A’aeshah Alhakamy | Computer Graphics | Best Researcher Award

Assoc. Prof. Dr. A’aeshah Alhakamy | Associate Professor | University of Tabuk | Saudi Arabia

Assoc. Prof. Dr. A’aeshah Alhakamy is a distinguished academic and researcher in the field of Computer Science at the University of Tabuk, Saudi Arabia. Her research spans computer graphics, computer vision, visualization, and imaging, with a particular focus on illumination models in mixed and augmented reality (AR/MR), gesture-based interaction, and the convergence of vision and artificial intelligence in immersive environments. Her scholarly contributions bridge the gap between visual perception and computational intelligence, emphasizing human–data interaction, extended reality (XR) technologies, and AI-driven visual analytics. She has successfully supervised graduate research in emerging domains such as extended reality applications for industrial training and biometric authentication systems using AI. Dr. Alhakamy’s research outputs demonstrate a deep commitment to advancing both theoretical and applied dimensions of visual computing and human–computer interaction. Her academic excellence is reflected through strong research metrics, including Scopus with 254 citations from 235 documents and an h-index of 9, and Google Scholar with 417 citations, an h-index of 11, and an i10-index of 13. These indicators highlight her growing influence and recognition in the international research community.

Featured Publications

Alhakamy, A. (2025). Intersecting realms: Examining the convergence of vision and AI in extended reality graphics. IEEE Access, 1–1.
Alhakamy, A. (2024). Extended reality (XR) toward building immersive solutions: The key to unlocking Industry 4.0. ACM Computing Surveys, 56(9).
Alhakamy, A. (2023). Fathoming the Mandela effect: Deploying reinforcement learning to untangle the multiverse. Symmetry, 15(3).
Alatawi, H., Albalawi, N., Shahata, G., Aljohani, K., Alhakamy, A., & Tuceryan, M. (2023). Augmented reality-assisted deep reinforcement learning-based model towards industrial training and maintenance for NanoDrop spectrophotometer. Sensors, 23(13).
Albalawi, S., Alshahrani, L., Albalawi, N., Kilabi, R., & Alhakamy, A. (2022). A comprehensive overview on biometric authentication systems using artificial intelligence techniques. International Journal of Advanced Computer Science and Applications, 13(4).