Wenyan Wu | Modeling | Best Researcher Award

Wenyan Wu | Modeling | Best Researcher Award

Dr. Wenyan Wu at Guangdong University of Technology | China

Dr. Wenyan Wu is an emerging researcher whose work focuses on the intersection of artificial intelligence, multimodal learning, and intelligent systems with applications in emotion recognition, sentiment analysis, and human-computer interaction. Since creating her ORCID record in August 2022, Dr. Wu has actively contributed to advancing research in cross-modal data analysis, integrating deep learning frameworks with cognitive and affective computing techniques. Her recent publication, โ€œModality-Enhanced Multimodal Integrated Fusion Attention Model for Sentiment Analysisโ€ (Applied Sciences, 2025), introduces a novel attention-based fusion approach to improve sentiment analysis accuracy by effectively capturing inter-modal dependencies across text, audio, and visual cues. In โ€œCollaborative Analysis of Learnersโ€™ Emotional States Based on Cross-Modal Higher-Order Reasoningโ€ (Applied Sciences, 2024), Dr. Wu explores emotion-aware learning environments, presenting innovative reasoning mechanisms for identifying and analyzing learnersโ€™ affective states to enhance adaptive education systems. Her research on โ€œMask-Wearing Detection in Complex Environments Based on Improved YOLOv7โ€ (Applied Sciences, 2024) demonstrates her interdisciplinary expertise, combining computer vision and deep neural networks to address real-world safety monitoring challenges. Earlier, her foundational study, โ€œA Novel Method for Cross-Modal Collaborative Analysis and Evaluation in the Intelligence Eraโ€ (Applied Sciences, 2022), laid the groundwork for her later research by proposing an integrated model for data collaboration across modalities in intelligent environments. Dr. Wuโ€™s scholarly output reflects her strong analytical and technical acumen, emphasizing multimodal integration, attention mechanisms, and deep learning optimization. Her contributions not only advance theoretical understanding but also provide practical frameworks for developing emotionally intelligent and context-aware AI systems, bridging the gap between computational models and human-centered design in modern intelligent applications.

Profile: Orcidย 

Featured Publicationsย 

Jiangdong Xu | Modeling | Best Researcher Award

Jiangdong Xu | Modeling | Best Researcher Award

Mr. Jiangdong Xu at Shandong University of Technology | China

Jiangdong Xu is a dedicated researcher affiliated with Shandong University of Technology in Zibo, Shandong, China. As a first author, he has contributed significantly to advancements in agricultural machinery and simulation modeling, particularly in the design of vertical threshing drums under high-moisture conditions and in developing a discrete meta-model of crushable maize kernels. His work addresses critical issues in crop processing efficiency and precision. Jiangdongโ€™s research demonstrates both theoretical depth and experimental innovation, earning him publication in high-impact SCI journals and recognition for pioneering discrete element modeling techniques in agricultural engineering.

Professional Profile

ORCID

Education

Mr. Jiangdong Xu holds a Bachelor’s degree in Agricultural Engineering . He is either pursuing or has completed postgraduate research at Shandong University of Technology, reflecting his active engagement in academic and applied research in the field.

Experience

Mr. Xu is currently a researcher at Shandong University of Technology in Zibo, China. He has contributed as both lead and co-author to several SCI-indexed publications, particularly within Zones II to IV. His expertise includes the use of EDEM simulation software for mechanical modeling and parameter testing. Additionally, he has been practically involved in machinery design and orthogonal experimental analysis, highlighting his applied engineering skills and analytical capabilities

Professional Development

Jiangdong Xu has continuously expanded his research capabilities by combining advanced modeling tools with experimental testing. His work on maize threshing mechanics and seed crush simulations reflects a growing expertise in discrete element modeling (DEM), particularly in agricultural applications. He actively engages in collaborative research and stays updated with cutting-edge simulation software like EDEM. Jiangdong also contributes to scholarly publishing as a first and third author in recognized SCI journals. His ability to translate complex mechanical behavior into accurate digital simulations marks his professional development in both academic and applied engineering domains.

Research Interestsย 

Jiangdong Xu’s research focuses onย Agricultural Engineering and Computational Modeling, particularly the use ofย Discrete Element Method (DEM)ย for simulating crop mechanicsย . His primary interests includeย threshing mechanism optimization,ย crushable seed kernel simulation, andย mechanical property testingย of agricultural materials. He specializes in reducing breakage in high-moisture maize threshing, improving machinery efficiency, and creating metamodels for accurate simulation of seed interactions. His work bridges experimental mechanics with computational simulation to enhance the precision and performance of agricultural equipmentโ€”contributing innovative solutions to global food engineering challenges.

Awards and Recognitionsย 

Jiangdong Xu has received recognition for his pioneering work in the field of agricultural machinery and simulation modeling. His first-author paper on the design of a vertical threshing drum under high-moisture conditions was published in an SCI Zone IV journal, while his innovative meta-modeling work on maize kernel crushability, a first in international research, was published in a Zone II journal with an impact factor of 3.6. He is also a contributing third author to a Zone II Top journal submission with an impact factor of 5.3, reflecting the academic value and impact of his interdisciplinary research contributions.

Top Noted Publicationsย 

Title: Discrete Meta-Modeling Method of Breakable Corn Kernels with Multi-Particle Sub-Area Combinations
Year: 2025

Memet ลžahin | Modeling | Best Researcher Award

Memet ลžahin | Modeling | Best Researcher Award

Prof. Dr. Memet ลžahin, Gaziantep University, Turkey.