Summary
Shaunak De is a Principal Systems Engineer at Capella Space with 11 years of experience combining radar remote sensing, machine learning, and production systems engineering. He holds a PhD focused on machine learning for radar remote sensing and has driven R&D and productization of SAR algorithms for change detection, flood segmentation, and on-board processing. At Capella and previously Orbital Insight he built scalable pipelines handling millions of km2 of imagery annually, delivered a flood detector with 0.88 balanced accuracy, and developed Bayesian fusion methods that became product differentiators. He bridges deep academic expertise—novel physics-aware neural architectures and semi-supervised techniques—with hands-on subsystem design, test automation, and on-orbit signal-processing requirements. Based in San Francisco, he’s as comfortable prototyping novel deep-learning models as he is architecting operational RF subsystems and automated validation tooling. An uncommon strength is his ability to translate scattering physics into deployable ML models that maintain high accuracy under limited training data.
11 years of coding experience
6 years of employment as a software developer
Indian Institute of Technology Bombay
Vocational, Electronics, Vocational, Electronics at Acharya A. V. Patel College
ICSE, ICSE at Chatrabhuj Narsee Memorial School
Bachelor of Engineering - BE, Electrical and Electronics Engineering, Bachelor of Engineering - BE, Electrical and Electronics Engineering at University of Mumbai
Italian, English, Hindi, Urdu, Bengali, Marathi, Gujarati