In-Sensor Spectral Machine Learning with Electrically Tunable Bipolar Photodetectors

We report spectral kernel machines leveraging electrically tunable photodetectors for in-sensor machine-learning analysis of spectral data at low power and high speed. This innovation opens opportunities for diverse applications, from chemometrics to semiconductor metrology.