Alexander Kononenko is a Senior Researcher with 12+ years in algorithm development and over two decades of physics-driven research experience, currently leading advanced non-invasive hemoglobin measurement methods at OrSense Ltd. He combines deep physical modeling of multi-channel optical signals with practical machine learning and DSP to separate physiological signal components, detect outliers, and improve measurement accuracy in clinical deployments worldwide. His work uniquely ties a first-principles light absorption and scattering model to statistical analysis and ML pipelines—enabling root-cause identification of measurement errors rather than just empirical fixes. Comfortable with Matlab, Python and TensorFlow, he has a track record of turning complex physiological phenomena into robust, deployable algorithms and has published prior research in solid state and nonlinear physics.
Contributions:28 commits, 27 pushes, 1 branch in 2 years 5 months
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