Researchers at Stanford have developed a non-destructive method for generating and patterning optical color centers with nanoscale resolution without the need for high energy radiation. Color centers, which are optically active defects within the lattice structur
Stanford researchers have developed deep learning methods which can more precisely localize the position and orientation of a camera in the lung anatomy in real-time.
Researchers at Stanford have developed a new water-based disinfectant with the potential to destroy a wide variety of pathogens and significantly improve healthcare settings.
Stanford researchers at the Xing Lab have developed a novel technique to enable retrospective tuning of soft tissue contrast in MRI (i.e. adjusting the contrast after the image acquisition) using a deep learning-based strategy.
Engineers at Stanford have invented a smart toilet platform that will autonomously monitor excreted waste from humans. We describe easily deployable hardware and software for the long-term analysis of a user's excreta through data collection and models of human health.
Researchers at Stanford have developed reactive oxygen species (ROS) sensing nanoparticles (NP) that can amplify Raman fingerprint signals and detect ROS changes.
A team of Stanford engineers have developed an accurate, robust location-based security method using signals from distinct classes of communication systems.
Stanford researchers have developed a high throughput, low energy consumption, optical method for real-time, image differentiation (image sharpening) using a photonic crystal slab.
Stanford researchers have prototyped a medical assistive device which improves efficiency of female self-catheterization by utilizing anatomical landmarks to aid accurate catheter placement in the urethra.
A team of Stanford researchers has developed ReMatch, an efficient, data-driven DER (distributed energy resources) planning and decision support framework that accounts for a range of complexities to optimize energy resource planning.
Stanford researchers at the Prakash Lab have developed Octopi, a low-cost ($250-$500) and reconfigurable autonomous microscopy platform capable of automated slide scanning and correlated bright-field and fluorescence imaging.
Stanford researchers at the Moore Lab have developed an algorithm for on-line, real time post processing of large amounts of neuronal data from high-density, multi-channel electrophysiological recordings to identify which neurons were firing (on-line spike recovery).