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Stanford researchers have developed a patented microscopy method which can provide chemical identification of molecular structures with radiation spectroscopy at nanometer or near-atomic scales, which is one of the most challenging problems in microscopy.

Stanford engineers have developed an optical modulator to enable low-cost and high spatial-resolution time-of-flight imaging and LiDAR with low-cost standard image sensors.

Stanford researchers in the WE3 and S3 Labs developed a cloud-based computation and predictive control platform for wastewater treatment facilities energy storage and energy generation. Wastewater treatment is energy and cost intensive.

Robots will need sensory skins to safely interact with humans and navigate more complex environments than factory work cells. This invention is a new stretchable pneumatic sensor skin that can feel its surroundings and reach for objects in constrained environments.

Researchers at Stanford have developed a new path planning algorithm that enables autonomous multi-drone aerial surveys over large-scale environments. Their system solves the problem of finding routes over large areas in order to complete aerial survey tasks in reduced time.

Multiplexed analysis of biological components is critical for classifying molecular subtypes of heterogeneous tumors to provide patient-specific therapies.

Liquid electrolytes in lithium-ion batteries have high ion-conductivity at room temperature, but lose this feature as temperature increases.

Stanford researchers in the Kanan group have developed a electrolysis cell for generating and extracting liquid and gas product streams from CO and CO₂.

Researchers at Stanford have developed an imitation learning method, IQ-Learn, shown to surpass existing methods in some applications.

Stanford researchers have developed a self-affirmation web application to improve students' mental wellbeing.

Researchers at Stanford have developed a cloud-based behind-the-meter (BTM) system that can cut energy costs and reduce reliance on the grid close to 93% respectively.

Stanford researchers have developed new Fast Quick Error Detection (Fast QED) tests that are four orders of magnitude faster than standard QED tests while also preserving quick error detection properties.

Stanford researchers have designed a systematic technique for post-silicon validation in system-on-chips (SoCs).

The Foundational QED embodies a set of source code files for performing the basic EDDI, CFCSS, and CFTSS QED transformations for creating tests with extremely short error detection latencies and high error detection coverage.

During post-silicon validation and debug, manufactured integrated circuits (ICs) are tested in actual system environments to detect and fix design flaws (bugs). Existing techniques are costly due to ad hoc, manual methods.