Summary
Mohsen Naji is a Staff Algorithm Engineer with 8 years of experience building real-time signal processing and machine learning algorithms for physiological sensing and wearable health devices. He has deep domain expertise across EEG, ECG, EMG, PPG, SCG, speckle plethysmography, short-wave IR spectroscopy and CGM, and a track record of deploying models from Python into embedded C for commercial products. At Dexcom he contributes to the G7 CGM algorithm and previously led CNIBP, blood-pressure and hydration algorithm efforts at Sotera and Rockley, respectively, demonstrating end-to-end ownership from cloud analysis to on-device implementation and SQA. His background includes postdoctoral research in sleep-related cardiac and brain signal analysis, giving him a strong foundation in physiology-driven algorithm design. Known for translating large clinical datasets into robust, regulatory-ready algorithms, he combines academic rigor with product-focused pragmatism. Based in Mission Viejo, CA, he is passionate about applying advanced sensing to improve global health outcomes.
8 years of coding experience
8 years of employment as a software developer
University of California, San Diego
Doctor of Philosophy (PhD) Biomedical Engineering, Doctor of Philosophy (PhD) Biomedical Engineering at SRBIAU
Middle and High school, Middle and High school at National Organization for Development of Exceptional Talents (Sampad)
Persian, English