We propose a compact noninvasive glucose monitoring system using polarized light, where a user simply needs to place her palm on the device for measuring her current glucose concentration level. The primary innovation of our system is the ability to minimize light scattering from the skin and extract weak changes in light polarization to estimate glucose concentration, all using lowcost hardware. Our system exploits multiple wavelengths and light intensity levels to mitigate the effect of user diversity and confounding factors (e.g., collagen and elastin in the dermis). It then infers glucose concentration using a generic learning model, thus no additional calibration is needed. We design and fabricate a compact (17 cm × 10 cm × 5 cm) and low-cost (i.e., <$250) prototype using off-the-shelf hardware. We evaluate our system with 41 diabetic patients and 9 healthy participants. In comparison to a continuous glucose monitor approved by U.S. Food and Drug Administration (FDA), 89% of our results are within zone A (clinically accurate) of the Clarke Error Grid. The absolute relative difference (ARD) is 10% . The 𝑟 and 𝑝 values of the Pearson correlation coefficients between our predicted glucose concentration and reference glucose concentration are 0.91 and 1.6 × 10 −143 , respectively. These errors are comparable with FDA-approved glucose sensors, which achieve ≈90% clinical accuracy with a 10% mean ARD. CCS CONCEPTS• Human-centered computing → Ubiquitous and mobile computing; • Hardware → Sensor devices and platforms.