I am a SAR Remote Sensing and AI scientist with experience across industries, such as space, maritime, oil & gas, critical infrastructure, telecommunications and healthcare. My area of expertise is: machine learning, synthetic aperture radar and more broadly in geospatial data analysis.

Previously, I worked at the European Space Agency (ESA) in ESTEC. I was part of the RF Payloads and Technology division. Some of the work includes: 

• geophysical parameter retrievals for [biomass estimation] from GNSS navigation signals.
• early-warning maritime monitoring using Synthetic Aperture Radar (SAR) [detect], [classify]
• edge AI algorithms (from algorithmic prototyping in PyTorch/CUDA to hardware implementation on FPGAs),
• on-board raw SAR data quantization and compression [compression], 
• end-to-end mission performance simulation analysis (electromagnetic scattering, on-ground data processing and retrievals).

I worked with various companies, hospitals and government research institutes to incorporate AI algorithms across their operations. You can find more information about my collaborations and our work in Publications.

I completed a Ph.D. in Physics (applied Bayesian Machine Learning) at the Cavendish Laboratory, University of Cambridge [thesis]. At the same institution, I was an Adjunct Lecturer in machine learning for two years [notes]. Earlier, I completed a master's degree in Scientific Computing at the University of Cambridge and an undergraduate degree in Electronic and Information Engineering at Imperial College London.