Assistant Professor | University of Agriculture | Pakistan
Dr. Muhammad Faheem is a distinguished researcher specializing in Agricultural Mechanization, Robotics in Agriculture, Intelligent Automation, and Control Engineering, with a strong body of work advancing smart and sustainable farming technologies. His research focuses on developing autonomous systems, machine-vision tools, and sensor-based intelligent solutions that enhance precision agriculture, optimize resource efficiency, and improve post-harvest handling processes, with emerging interests in deep-learning applications, multisensory navigation, and automated crop-quality assessment. With key academic appointments, including his role as Assistant Professor at the University of Agriculture Faisalabad and research affiliation with Jiangsu University, China, he has contributed extensively to engineering innovative systems for real-time agricultural problem-solving. Dr. Faheem’s major contributions include pioneering CNN-based defect detection frameworks for photovoltaic cells, intelligent sensor-guided variable-rate spraying systems, and advanced autonomous navigation technologies for multi-crop field environments; he has also significantly advanced post-harvest robotics through novel vibration-reduction mechanisms and fruit-handling models, in addition to impactful work on sustainable technologies such as smart composting, biogas systems, and solar thermal collectors. His research has influenced diverse areas including climate-responsive agricultural management, disease-detection systems using deep learning, and high-precision fruit-picking robotics—contributions reflected in widely cited publications across leading journals in energy engineering, environmental sciences, precision agriculture, and smart automation. Dr. Faheem’s impact vision centers on accelerating the global transition toward intelligent, autonomous, and environmentally responsible farming systems by integrating robotics, machine learning, and sensor fusion into practical agricultural operations. Through his interdisciplinary work, he aims to contribute to resilient food production, reduced environmental footprints, and enhanced technological adoption in agriculture worldwide, ensuring that innovations in automation and sustainability directly benefit farmers, industry stakeholders, and the broader scientific community.
Featured Publications
1. Akram, M. W., Li, G., Jin, Y., Chen, X., Zhu, C., Zhao, X., Khaliq, A., Faheem, M., et al. (2019). CNN-based automatic detection of photovoltaic cell defects in electroluminescence images. Energy, 189, 116319.
2. Abbas, I., Liu, J., Faheem, M., Noor, R. S., Shaikh, S. A., Solangi, K. A., & Raza, S. M. (2020). Different sensor-based intelligent spraying systems in agriculture. Sensors and Actuators A: Physical, 316, 112265.
3. Xie, B., Jin, Y., Faheem, M., Gao, W., Liu, J., Jiang, H., Cai, L., & Li, Y. (2023). Research progress of autonomous navigation technology for multi-agricultural scenes. Computers and Electronics in Agriculture, 211, 107963.
4. Javed, T., Afzal, I., Shabbir, R., Ikram, K., Zaheer, M. S., Faheem, M., Ali, H. H., et al. (2022). Seed coating technology: An innovative and sustainable approach for improving seed quality and crop performance. Journal of the Saudi Society of Agricultural Sciences, 21(8), 536–545.
5. Ajmal, M., Shi, A., Awais, M., Mengqi, Z., Zihao, X., Shabbir, A., Faheem, M., et al. (2021). Ultra-high temperature aerobic fermentation pretreatment composting: Parameters optimization, mechanisms and compost quality assessment. Journal of Environmental Chemical Engineering, 9(4), 105453.