Zohaib Khan | Engineering and Technology | Excellence in Research Award

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Dr. Zohaib Khan | Engineering and Technology | Excellence in Research Award

Jiangsu University | China

Zohaib Khan is a PhD candidate in Control Science and Engineering at Jiangsu University, specializing in machine learning–driven perception and control for intelligent robotic systems. With over six years of research and applied experience, his work bridges deep learning, computer vision, and real-time robotic control, with a strong focus on agricultural robotics and precision farming. He has authored more than 10 high-impact SCI-indexed journal articles, achieving an h-index of 6, with 11 research documents and 121 citations. His research interests include object detection and segmentation (YOLO series, transformer-based models, RCNN), vision-guided navigation, precision spraying, and robust control of autonomous robots in unstructured environments. Zohaib has contributed as both first and co-author to leading journals such as Computers and Electronics in Agriculture, Agronomy, Sensors, and IEEE Transactions on Industrial Electronics. Alongside research, he has extensive experience supervising student projects and developing real-time AI pipelines using Python, PyTorch, OpenCV, ROS, and C/C++. His academic excellence is recognized through multiple national and international awards, including innovation, debate, and research excellence honors. Overall, Zohaib Khan represents a strong blend of theoretical rigor and practical AI deployment, aiming to advance large-scale industrial and agricultural perception systems.

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Featured Publications

Sun Yubing | Computer Science and Artificial Intelligence | Best Researcher Award

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Dr. Sun Yubing | Computer Science and Artificial Intelligence | Best Researcher Award

Wenzhou University | China

Dr. Yubing Sun earned his PhD from Zhejiang University and currently serves as a lecturer at Wenzhou University, where he leads research efforts on advanced gas-sensor technologies and their systems for agricultural applications. His research focuses on improving sensitivity, selectivity, stability and drift compensation of gas sensors, and deploying sensor systems for field-scale agricultural monitoring. While a formal h-index, total document count and citation count are not publicly verified, his publication record and successful leadership in multiple national and provincial projects underscore his growing research impact. He has secured competitive funding, participated in multidisciplinary teams, and supervised student-led work bridging sensor hardware and agricultural field deployment. His contributions have been recognized via institutional awards and research grants. Looking ahead, Dr. Sun aims to translate lab-scale gas-sensor innovations into robust agricultural-system platforms, contributing to precision agriculture and sustainable crop monitoring.

Profile : Orcid

Featured Publications

Sun, Y., Huang, J., & Zheng, Y. (2025, September 9). Study on the determination of pest attack time of tea plant by gas sensor. Annals of Applied Biology.

Sun, Y., & Zheng, Y. (2024, December 2). Application of MOS gas sensors for detecting mechanical damage of tea plants. Journal of Agricultural Engineering.

Sun, Y., & Zheng, Y. (2024, June). Prediction of tomato plants infected by fungal pathogens at different disease severities using E-nose and GC–MS. Journal of Plant Diseases and Protection.

Yu, W., & Sun, Y. (2024, March). A method for detecting gas applied in seed germination with varying concentration based on gas sensors. Measurement.

Sun, Y., & Zheng, Y. (2023, July 24). A method of gas sensor drift compensation based on intrinsic characteristics of response curve. Scientific Reports.

lifei wei | Sustainable Development | Best Researcher Award

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Prof. lifei wei | Sustainable Development | Best Researcher Award

Hubei University | China

Professor Lifei Wei, a distinguished scholar at Hubei University, serves as Professor and Doctoral Supervisor with expertise in intelligent remote sensing image processing, agricultural remote sensing, ecological monitoring, and GIS big data analytics. He earned his advanced degrees in engineering and has established himself as a leading academic voice in the field of ecological remote sensing. With over 20 completed and ongoing research projects, his scientific output includes numerous high-impact journal publications indexed in SCI and Scopus. His research profile highlights an h-index of 22, more than 1,604 citations, and several influential works widely recognized in the international community. In addition to academic achievements, Prof. Wei is the Deputy Director of a Hubei Key Laboratory and holds the title of EU Senior Engineer, contributing significantly to interdisciplinary collaborations and consultancy projects in remote sensing applications. He has served as a reviewer for over 20 prestigious journals, including IEEE GRSL, ISPRS, and Remote Sensing, reflecting his standing in the scientific community. His contributions have been acknowledged through multiple awards, grants, and leadership positions. Dedicated to advancing ecological sustainability through technological innovations, Prof. Wei’s impactful career continues to shape remote sensing research and inspire future scholars globally.

Profile : Scopus

Featured Publications

Tang, J., Zhang, F., Chan, N. W., Li, Z., Ma, X., Wei, L., … & Tan, M. L. (2025). Water color remote sensing models: Inversion mechanisms, optimization, and challenges. Journal of Sea Research, 102622.

Feng, Z., Zhang, F., Cai, X., Liu, C., Wu, D., Zhu, Z., … Wei, L. (2025). Quantitative inversion of suspended particulate matter in Ebinur Lake, an arid region: Evidence based on radiative transfer mechanism model. Journal of Hydrology: Regional Studies, 61, 102714.

Zhou, J., Xu, H., Jim, C. Y., … Wei, L. (2025). Spatiotemporal dynamics of land use and landscape in coastal Zhejiang using multiple methods. iScience.

Regional variations in lake areas in China due to human and natural environmental factors since 1990. Ecological Indicators(2025).

Sentinel-2 and UAV Hyperspectral Image Data Fusion Used in Natural Disasters Cause Soil Pollution of the Distribution Map. Land Degradation & Development(2025).