Masoud Mahdianpari

Masoud Mahdianpari is a Cross-appointed Professor between Memorial University's Department of Electrical and Computer Engineering and C-CORE, where he serves as Remote Sensing Technical Lead. He holds a PhD in Electrical Engineering from Memorial University, complemented by graduate degrees from the University of Tehran.

His research specializes in advanced remote sensing techniques, including PolSAR data processing, multi-sensor fusion, and deep learning applications for environmental monitoring. Primary research domains encompass wetland ecosystem mapping, agricultural surveillance, and Arctic landscape analysis using satellite data and geo big data platforms.

Mahdianpari's publications demonstrate a consistent focus on machine learning applications in earth observation, with recent work emphasizing wetland biomass quantification, methane emission tracking, and wildfire prediction using convolutional neural networks and transformer architectures.

• T. David Collett Best Industry Paper Award (2020)
• ESRI Map Award for 'Big Data for Big Country' (2020)
• Microsoft AI for Earth Grant (2018-2019)
• Outstanding Reviewer Award for Remote Sensing of Environment (2018)
• RDC Ocean Industries Student Research Award (2016-2019)
• PhD Comprehensive Examination Pass with Distinction (2017)

He coordinates research initiatives at C-CORE's remote sensing division and mentors graduate students in the GeoBigData Laboratory. Current projects include developing novel CNN-Transformer hybrid models for wetland classification and satellite-based methane monitoring systems.