Muhammad Bilal zia | Agriculture | Best Researcher Award

Published on by Plant Scientist

Mr. Muhammad Bilal zia | Agriculture | Best Researcher Award

University of Southern Queensland | Australia

Muhammad Bilal Zia is a researcher and educator in Information Technology, currently pursuing a PhD at the University of Southern Queensland, Australia. He holds a Master’s degree in Computer Science from Taiyuan University of Technology, China, and a Bachelor’s degree from The Islamia University of Bahawalpur, Pakistan. He has teaching experience across Australian and international institutions, delivering courses in data science, artificial intelligence, and analytics. His research focuses on deep learning, computer vision, and medical image analysis, particularly in disease detection. He has published in reputed Q1 journals and received a Chinese Provincial Scholarship, contributing significantly to AI-driven healthcare solutions.

                          Citation Metrics (Scopus)
8
6
4
2
0

Citations
3

Documents
4

h-index
1

Citations

Documents

h-index

View Scopus Profile

Featured Publications

Wenbin Zhang | Precision Agriculture | Research Excellence Award

Published on by Plant Scientist

Prof. Dr. Wenbin Zhang | Precision Agriculture | Research Excellence Award

Kunming University | China

Professor Wenbin Zhang, Ph.D., is a distinguished academic in mechanical and electrical engineering at Kunming University, serving as a full professor and master’s adviser in the Department of Intelligent Manufacturing Engineering. Over nearly fifteen years of teaching, he has developed and authored laboratory guidebooks for measurement technology, PLC application, and mechanical innovation design. His research focuses on condition monitoring, intelligent fault diagnosis, signal processing, and innovation in mechanical design. He leads a major project funded by the National Natural Science Foundation of China, as well as a provincial innovation-team initiative, and has built a key laboratory and research team at his university. He has published over 100 papers, with more than 50 in EI or SCI-indexed journals, and holds over 100 national patents. According to his Google Scholar profile, he has an h-index of 11, 394 citations, and 82 Documentation, highlighting his strong research influence. Through his integrated excellence in teaching, research, and innovation, Dr. Zhang is recognized as a technological leader in Yunnan Province and is part of the “Yunnan 10,000 Talents Program.”

Profile: Scopus

Featured Publications

Zhang, W., Wang, Y., Tan, Y., Guo, D., & Pu, Y. (Year not provided). Application of adaptive local iterative filtering and permutation entropy in gear fault recognition. Mathematical Problems in Engineering.

Zhang, W., Min, J., Wang, Y., Pu, Y., Jiang, J., Guo, D., & Yu, L. (2022). Application of adaptive local iterative filtering in axis trace purification of turbine generator rotor. Journal of Mechanical Science and Technology.

Cui, B., Guo, P., & Zhang, W. (2023). Research on fault diagnosis of rolling bearing based on the MCKD-SSD-TEO with optimal parameters. Journal of Mechanical Science and Technology.

Guo, P., Cui, B., & Zhang, W. (2024). Cross-device target migration intelligent diagnosis method of wind power gearbox faults. Measurement Science and Technology

Zhao, C., Yin, Z., Zhang, W., Guo, P., & Ma, Y. (2024). Identification of apple watercore based on ConvNeXt and Vis/NIR spectra. Infrared Physics and Technology,

Yang Hu | Sustainable Agriculture | Best Researcher Award

Published on by Plant Scientist

Mr. Yang Hu | Sustainable Agriculture | Best Researcher Award

Central South University of Forestry and Technology | China

Hu Yang is a researcher specializing in artificial intelligence applications in agriculture and forestry, currently with the Artificial Intelligence Application Research Institute at Central South University of Forestry and Technology. With a focus on multi-modal data fusion, computer vision, and deep learning, Hu has contributed to over 10 peer-reviewed publications in high-impact journals, including Computers and Electronics in Agriculture, The Plant Journal, Information Fusion, and European Journal of Agronomy, with several manuscripts under revision or review. His work has achieved a total of 5documents, over 13 citations, and an h-index of 2, reflecting a strong influence in AI-driven plant disease recognition, image segmentation, and data augmentation techniques. Hu has led multiple projects funded by the National Natural Science Foundation and university-level innovation programs, including multimodal agricultural and forestry disease assessment systems and forest area road crack detection using reinforcement learning. His research interests include multi-modal machine learning, image-based disease detection, precision agriculture, and smart forestry monitoring. Recognized with numerous awards such as the National Scholarship (2025) and Outstanding Graduate (2024), Hu continues to advance AI frameworks that bridge cutting-edge computational methods with practical applications, aiming to improve crop health, sustainable forestry, and environmental protection through intelligent, data-driven solutions.

Profile: Scopus

Featured Publication

Mendes, L. de C., et al. (2025). AMF: A multi-modal framework for crop leaf diseases segmentation. Computers and Electronics in Agriculture.

Md Ashraful Haque | Precision Agriculture | Best Researcher Award

Published on by Plant Scientist

Dr. Md Ashraful Haque | Precision Agriculture | Best Researcher Award

ICAR Indian Agricultural Statistics Research Institute | India

Dr. Md. Ashraful Haque is a Scientist in the Division of Computer Applications at ICAR-Indian Agricultural Statistics Research Institute, New Delhi, with over five years of professional experience in artificial intelligence applications in agriculture. He earned his M.Sc. (2016) and Ph.D. (2022) in Computer Applications from ICAR-Indian Agricultural Research Institute under the supervision of Dr. Sudeep Marwaha. His research focuses on artificial intelligence, machine learning, deep learning, computer vision, and digital as well as hyperspectral image processing for solving complex agricultural problems such as crop disease detection, pest identification, stress analysis, and livestock image interpretation. He has published 20 journal articles, 4 book chapters, and 2 computational tools, with his research gaining wide recognition (h-index: 8, 339 citations). Dr. Haque has contributed to international collaborations with IIT Delhi, ICAR institutes, and several universities, and has developed impactful digital tools like AIDISC and WIAYFS. He is the recipient of prestigious fellowships and awards, including the Maulana Azad National Fellowship, ICAR-JRF, IARI Ph.D. Fellowship, and Nehru Memorial Gold Medal. With strong expertise in AI-driven agriculture, he continues to innovate toward sustainable farming solutions. His work demonstrates high relevance, impact, and future research potential in smart agriculture.

Profiles: Scopus | Google Scholar | Orcid

Featured Publications

“MuSiC V1.0: A Software Solution for Automated Mustard Silique Count Using YOLOv5”
“An enhanced vision transformer network for efficient and accurate crop disease detection”

“PanicleDet: a deep learning-based model for detection of panicle stages in paddy”

“A comparative analysis of deep learning-based techniques for miRNA prediction associated with mRNA sequences”

“ADNet: An Attention Embedded DenseNet121 Model for Weed Classification”

“Convolution Neural Network (CNN)-Based Live Pig Weight Estimation in Controlled Imaging Platform”
“Rice Disease Identification Using Vision Transformer (ViT) Based Network”