Hamza Rafique
Doctoral Researcher (WP2, Digital Innovations)
Lahore University of Management Sciences (LUMS)
Hamza Rafique is an aeronautical engineer by profession and a remote sensing expert by training. His research interests focus on developing remote sensing–based technological innovations for smallholder farming systems in Pakistan. He is particularly interested in applying geospatial technologies to improve agricultural monitoring, decision-making, and resource management, while also examining the social dimensions that influence the adoption and impact of technological interventions in smallholder-driven agricultural systems.
Research interests
- Satellite remote sensing
- Machine learning
- Precision agriculture
- Irrigation decision support tools
- Socio-hydrological systems analysis
Work experience and education
2022 - present
PhD research
Lahore University of Management Sciences, Pakistan
Topic: On-Farm Irrigation Scheduling: A Scalable Data-Driven Optimization Framework for Smallholder Systems
2024
Guest PhD Researcher
University of Hildesheim, Germany
Topic: Hyperspectral satellite imagery for grassland biodiversity estimation
2020 – 2022
Team Lead, AI Application Lab
CENTAIC, Rawalpindi, Pakistan
Topic: Artificial intelligence (AI) based decision support tools
2019 – 2020
Research Assistant
Air University, Islamabad, Pakistan
Topic: Deep learning for object detection and localization
2018 – 2020
M.Sc. Avionics Engineering
Air University, Islamabad, Pakistan
Thesis: Deep Learning-Based Post-Calamity Building Damage Assessment Using Satellite Imagery
2014 – 2018
Design Engineer
Avionics Research Center, Peshawar, Pakistan
Topic: Embedded systems and SDR-based GNSS/radar emulation
2009 – 2013
B.E. Avionics Engineering
National University of Science and Technology, Risalpur, Pakistan
Topic: Heading Control of a Fixed Wing UAV Using Alternate Control Surfaces
Selected publications
[preprint] Hamza Rafique, and Abubakr Muhammad “Calibration and validation of field scale soil moisture estimates from an Energy Balance Model for the data-scarce Indus River Basin”, Journal of Hydrology: Regional Studies
[preprint] Hamza Rafique, Abubakr Muhammad, and Jawairia Ishfaq, "Thermal Guided Super Resolution for Real-time Downscaling of SMAP," in IEEE Geoscience and Remote Sensing Letters (2026)
[preprint] M. Ibrahim Rana, Hamza Rafique and Hassan Jaleel , "Satellite-Anchored UAV Sensing System for High-Resolution Soil Moisture Mapping," Computers and Electronics in Agriculture (2026)
Asif, A., Rafique, H., Jadoon, K. et al. Change-centric building damage assessment across multiple disasters using deep learning. Int J Data Sci Anal 20, 1915–1931 (2025). https://doi.org/10.1007/s41060-024-00577-y
Conference presentations
H. Rafique, R. Zainab, Z. Ahmad and A. Muhammad, "A Quality Assured in-situ Real-Time Soil Moisture Monitoring Network for the Indus Basin," IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, Athens, Greece, 2024, pp. 5155-5161, doi: 10.1109/IGARSS53475.2024.10642900
H. Rafique and A. Muhammad, "A deep learning framework for Farm-scale soil moisture retrievals: A case study for a data-scarce Region," IGARSS 2026 - 2026 IEEE International Geoscience and Remote Sensing Symposium, Washington, D.C., 2026
M. Ahmad, H. Rafique and A. Muhammad, "Exploring the Application of Machine Learning for Soil Moisture Forecasting over In-situ Soil Moisture Sensors Network," 2024 Horizons of Information Technology and Engineering (HITE), Lahore, Pakistan, 2024, pp. 1-5, doi: 10.1109/HITE63532.2024.10777226