Muhammad Fahad | Crop Sciences | Best Researcher Award

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Mr. Muhammad Fahad | Crop Sciences | Best Researcher Award

Muhammad Fahad is a PhD candidate in Crop Genetics and Breeding at Zhejiang University, China, focusing on abiotic stress tolerance, epigenetic regulation, and non-coding RNAs in crops. He holds an M.Sc. (Hons.) in Plant Breeding and Genetics from Bahauddin Zakariya University, Pakistan. His research involves molecular techniques such as gene cloning, CRISPR-Cas9, and transcriptomics, with ongoing projects in Brassica napus and rice. Fahad has published on plant stress responses, reviewed for leading journals, and received multiple academic awards, including a Best Poster Award as a CSC scholar.

Mr. Muhammad Fahad | Zhejiang University | China

Profile

SCOPUS ID

ORCID ID

GOOGLE SCHOLAR

🎓Education

  • Muhammad Fahad is currently a PhD candidate in Crop Genetics and Breeding at the College of Agriculture & Biotechnology, Zhejiang University, China, under the supervision of Prof. Wu Liang. He began his doctoral studies in September 2021. Prior to this, he completed his M.Sc. (Hons.) in Agriculture with a specialization in Plant Breeding and Genetics from Bahauddin Zakariya University, Multan, Pakistan. His graduate studies spanned from August 2014 to February 2021.

👨‍🏫 Experience

  • Muhammad Fahad is currently a PhD candidate in Crop Genetics and Breeding at the College of Agriculture & Biotechnology, Zhejiang University, China, under the supervision of Prof. Wu Liang. He began his doctoral studies in September 2021. Prior to this, he completed his M.Sc. (Hons.) in Agriculture with a specialization in Plant Breeding and Genetics from Bahauddin Zakariya University, Multan, Pakistan. His graduate studies spanned from August 2014 to February 2021.

🏆Awards and Recognitions

  • In 2024, he received the Best Poster Award as a CSC scholar at Zhejiang University. His achievements also include an appreciation certificate and an exchange student fellowship from the Zhejiang Academy of Agricultural Sciences in 2020, and a Best Performance award from the Strengthening Participatory Organization in 2019.

💡Skills and Certifications

  • Muhammad Fahad possesses a diverse and advanced skill set in the fields of crop sciences, molecular biology, and agricultural biotechnology. He is highly proficient in gene cloning, CRISPR-Cas9 genome editing, protein-protein interaction studies, and tissue culture techniques. His expertise extends to cutting-edge areas such as DNA methylation, epigenetic regulation, and non-coding RNA analysis in plants. Fahad is also skilled in bioinformatics and statistical analysis, with hands-on experience using R, Python, SPSS, and Linux for transcriptomic and epigenomic data interpretation. In addition to his technical abilities, he is an accomplished scientific writer and peer reviewer, with a proven track record of publishing in high-impact journals. His collaborative nature, cross-cultural research experience, and commitment to innovation make him a valuable contributor to both academic and applied agricultural research.

🔬 Research Focus

  • His primary research interests include abiotic stress tolerance, plant breeding, epigenetic regulation in crops, and the role of non-coding RNAs in stress responses and genetic regulation.

🌎Conclusion

  • With a consistent record of scientific productivity, innovative research direction, technical proficiency, and international collaboration, Muhammad Fahad is highly suitable for the Best Researcher Award. His contributions not only enhance academic understanding but also pave the way for practical solutions to pressing agricultural challenges. Recognizing him with this award would honor a researcher who is truly shaping the future of crop sciences.

📖Publications

  •  MicroRNA gatekeepers: Orchestrating rhizospheric dynamics
    Authors: Muhammad Fahad, Leeza Tariq, Wanchang Li, Liang Wu
    Journal: Journal of Integrative Plant Biology

  •  MicroRNA regulation and environmental sensing in grasses
    Authors: Sajid Muhammad, Muhammad Fahad, Weijun Zhou, Liang Wu
    Journal: Grass Research

  • Comparative Analysis of Phytohormone Biosynthesis Genes Responses to Long-Term High Light in Tolerant and Sensitive Wheat Cultivars
    Authors: Zhi-Ang Li, Muhammad Fahad, Wan-Chang Li, Leeza Tariq, Miao-Miao Liu, Ya-Nan Liu, Tai-Xia Wang
    Journal: Plants

  • Underground communication: Long non-coding RNA signaling in the plant rhizosphere
    Authors: Muhammad Fahad, Leeza Tariq, Sajid Muhammad, Liang Wu
    Journal: Plant Communications

  • Comparative and functional analysis unveils the contribution of photoperiod to DNA methylation, sRNA accumulation, and gene expression variations in short‐day and long‐day grasses
    Authors: Xia Wu, Siyi Chen, Feng Lin, Fahad Muhammad, Haiming Xu, Liang Wu
    Journal: The Plant Journal

Zili Chen | Smart Agriculture | Best Researcher Award

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Mr. Zili Chen | Smart Agriculture | Best Researcher Award

Zili Chen is currently pursuing graduate studies at Henan Normal University, specializing in Agricultural Engineering and Information Technology. Before his master’s degree, he worked in software development at Zhejiang Jiuzhou Tuoxin Information Service Co., Ltd. His research focuses on applying computer vision and deep learning in agricultural remote sensing, particularly in disease monitoring. He has published academic papers in international journals and won the Best Graduate Oral Presentation Award at the 5th Remote Sensing Conference on Vegetation Diseases and Pests Graduate Forum. His ongoing projects include intelligent monitoring systems for tobacco production and digital twin systems for agricultural big data.

Mr. Zili Chen | Institute of Agricultural Information Technology, Henan Academy of Agricultural Sciences | China

Profile

SCOPUS ID

🎓 Education

  • Zili Chen is currently pursuing a graduate degree in Agricultural Engineering and Information Technology at Henan Normal University. His academic journey has equipped him with expertise in computer vision and deep learning applications in agricultural remote sensing.

💼 Experience

  • Before beginning his master’s studies, Zili Chen worked in software development at Zhejiang Jiuzhou Tuoxin Information Service Co., Ltd., where he gained practical experience in information technology and data processing. His industry background complements his research, allowing him to bridge the gap between theoretical advancements and real-world applications.

🔥 Awards and Achievements

  • Zili Chen has been recognized for his outstanding research contributions, winning the Best Graduate Oral Presentation Award at the 5th Remote Sensing Conference on Vegetation Diseases and Pests Graduate Forum. His work has also been published in reputable international journals, further demonstrating the impact of his research.

🛠️ Skills and Certifications

  • Zili Chen specializes in deep learning algorithms, computer vision, and agricultural remote sensing. His expertise extends to software development, data analysis, and artificial intelligence applications in agriculture. He is currently applying for a national invention patent for a Method and System for Tobacco Leaf Disease Spot Segmentation Based on Multi-Scale Residual Dilated Convolution, reflecting his commitment to technological innovation in smart agriculture.

🔬 Research Focus

  • His primary research interests lie in the application of computer vision and deep learning for agricultural disease monitoring. He has contributed to improving segmentation accuracy for tobacco leaf lesions through advanced deep learning models, significantly enhancing recognition efficiency. His research has been applied in intelligent monitoring systems for high-end agricultural products and has been integrated into national key research projects.

Conclusion

  • Based on his research impact, technological innovations, industry collaborations, and academic recognition, Zili Chen is a strong candidate for the Research for Best Researcher Award. His expertise in agricultural remote sensing and deep learning not only contributes to scientific knowledge but also drives practical advancements in precision farming and smart agriculture solutions. His award-winning presentation skills, peer-reviewed publications, and contributions to national research projects make him a deserving nominee for this prestigious recognition.

📄Publications

  • MD-Unet for tobacco leaf disease spot segmentation based on multi-scale residual dilated convolutions
    Authors: Zili Chen, Yilong Peng, Jiadong Jiao, Wei Lin, Yan Guo
    Journal: Scientific Reports, 2025

Pingchuan Zhang | Intelligent Agriculture | Best Researcher Award

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Prof. Pingchuan Zhang | Intelligent Agriculture | Best Researcher Award

Pingchuan Zhang, born in Wuyang County, Henan Province, China, in 1968, is a distinguished professor and researcher specializing in IoT and intelligent agriculture systems. He earned his B.S. in Prospecting Engineering from Chengdu University of Technology, M.S. in Computer Software and Theory from the University of Zhengzhou, and Ph.D. in Microelectronics and Solid Physics from Huazhong University. With over two decades of academic experience, he serves as an Associate Professor at Luohe Vocational Technology College and a Master’s Supervisor in Agriculture Engineering and Information Technology. A senior member of the China Electronics Society, he has authored nine books, published over 40 articles, and holds more than 10 patents. His research focuses on IoT applications, intelligent systems, and sensing technologies.

Prof. Pingchuan Zhang | Henan Institute of Science and Technology | China

Profile

SCOPUS  ID

🎓 Education

  • Pingchuan Zhang completed his Bachelor of Science degree in Prospecting Engineering at Chengdu University of Technology in 1991. He earned his Master’s degree in Computer Software and Theory from the University of Zhengzhou in 2005 and later achieved a Ph.D. in Microelectronics and Solid Physics from Huazhong University in 2012.

💼 Experience

  • From 2000 to 2008, he served as a Research Assistant Professor and Instructor. Since 2009, he has been an Associate Professor in the Department of Electronical Mechanical Engineering at Luohe Vocational Technology College. In the fall of 2019, he was appointed as a Distinguished Professor in the field of the Internet of Things (IoT) and became a Master’s Supervisor in Agriculture Engineering and Information Technology.

 🏆 Honors and Awards

  • Pingchuan Zhang is recognized as a senior member of the China Electronics Society and holds distinguished positions in academia. He has contributed extensively to the field through his authorship of nine books, over 40 academic articles, and more than 10 patented inventions.

🛠️ Skills and Certifications

  • He has expertise in IoT and Physical Agriculture, intelligent systems, and sensing technologies. His research and technical contributions focus on developing advanced systems for agricultural applications and improving IoT-based intelligent systems.

🔬 Research Focus

  • Pingchuan Zhang’s research focuses on integrating IoT technologies with physical agriculture, exploring intelligent systems, and advancing sensing technologies to drive innovation and sustainability in the agricultural and technological domains.

Conclusion

  • Pingchuan Zhang demonstrates exceptional qualifications and achievements that make him a strong candidate for the Best Researcher Award. His contributions to research, innovation, and education, coupled with his professional recognition, underscore his suitability for this prestigious accolade.

📄Publications

  • Design and Initial Tests of a Fast Neutron Radiography Detector Prototype with Silicon Photomultiplier Readouts
    Authors: Chen, X., Tang, B., Chen, R., Wang, Y., Liu, Y.
    Journal: Applied Sciences (Switzerland), 2024, 14(13), 5536
  • Research on Peach Phosphorus Deficiency Detection Based on Improved Faster R-CNN
    Authors: Hu, Y., Zhang, Y., Zhang, P., Chen, Z., Chen, X.
    Journal: Journal of Chinese Agricultural Mechanization, 2024, 45(4)
  • Recognition of Peach Tree Yellow Leaf Disease under Complex Background Based on Improved Faster-RCNN
    Authors: Zhang, P., Hu, Y., Zhang, Y., Chen, Z., Chen, X.
    Journal: Journal of Chinese Agricultural Mechanization, 2024, 45(3)
  • Investigation of DRA and Non-DRA in Locust Compound Eye on the Phototactic Response of Locust
    Authors: Liu, Q.H., Liu, M.H., Yang, B., Cui, J.X., Zhao, H.Y.
    Journal: International Journal of Agricultural and Biological Engineering, 2024, 17(5), pp. 81–87
  • Peculiar Influence of Linearly Polarized Spectrum Illumination Patterns on the Sensitivity Characteristics of Locust Response to Polarized Light
    Authors: Liu, Q., Zhao, H., Zhang, P., Cui, J., Gao, G.
    Journal: International Journal of Agricultural and Biological Engineering, 2024, 17(2), pp. 59–67