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Glacial Lake Outburst Flood Risk Assessment in High Mountain Asia
A logistic-regression approach using remote-sensing parameters to assess GLOF risk, presented at IGARSS 2024 in Athens.
Achievements
Recognized at the frontier of the field.
Our Earth-observation and remote-sensing work has earned international awards, competitive research funding, and peer-reviewed publications, alongside active leadership in the geoscience community.
Awards & grants
Milestones that matter.
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Award · 1st Prize
IEEE GRSS EO4SDG
First-place winning submission in the IEEE Geoscience & Remote Sensing Society's REACT competition for Earth Observation and the Sustainable Development Goals.
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Research Funding
SNSF SPIRIT Grant, 364, 012 CHF
A 48-month, Swiss-funded research programme on large-scale landslide hazard assessment via time-series satellite radar interferometry, with ETH Zurich and UET Lahore.
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Recognition
CleanTech 2022 Challenge
Distinction in the CleanTech 2022 Challenge, reflecting our commitment to innovation in environmental technology and capacity-building.
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Community
Lahore IEEE GRSS Chapter
Helped establish Lahore's IEEE Geoscience & Remote Sensing Society chapter (2023) to build local capacity in remote sensing and spatial analytics.
Publications & talks
Peer-reviewed & presented.
Our research is published in leading IEEE venues. A selection of recent papers, with the full record on Google Scholar.
IEEE · Peer-reviewed
PKLandSeg: Annotation-Guided Hybrid CNN–Vision Transformer for Landslide Segmentation
A hybrid CNN–Vision Transformer architecture, guided by annotation strategy, for accurate landslide segmentation from satellite imagery.
Read on IEEE Xplore ↗IEEE · Peer-reviewed
LADI: Landslide Activity Detection Index Based on InSAR Coherence and Sensitivity
A novel index for detecting landslide activity from satellite radar interferometry, combining InSAR coherence and sensitivity analysis for hazard monitoring.
Read on IEEE Xplore ↗More talks & papers
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Glacial Lake Mapping using a Remote-Sensing Geo-Foundation Model
Published in the International Journal of Applied Earth Observation and Geoinformation, developed with ETH Zurich and the Chinese Academy of Sciences.
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Oil-Spill Detection from SAR Imagery using Deep Learning
An invited tutorial delivered at the 9th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR 2025), Matsue, Japan.
Partner with a proven team.
Award-winning research, delivered as production software. Let's build what's next.