Amin Arbabian and PhD candidates Aidan Fitzpatrick and Ajay Singhvi combine light and sound to see underwater
The “Photoacoustic Airborne Sonar System” could be installed beneath drones to enable aerial underwater surveys and high-resolution mapping of the deep ocean.
Thaibao Phan and Grayson Zulauf receive Best Paper Award at the 2020 Control and Modeling in Power Electronics (COMPEL) Workshop
The PhD candidates paper is titled "1 kW, Multi-MHz Wireless Charging for Electric Transportation”, and was a collaborative project between SUPERlab and Fan Lab.
Kwabena Boahen describes Neuromorphic Computing in 'The Future of Everything' podcast
Listen to Kwabena and a fellow bioengineer in "How to build a super-efficient super-computer”.
James Zou's research highlights bias of machine learning
In a new paper with students Antonio Ginart and Eva Zhang, they describe how algorithms can have serious implications for both companies and consumers.
Dorsa Sadigh’s novel AI blends algorithms
The combined algorithm (latent action with shared autonomy) was both faster and easier for users to control than the latent action algorithm alone or the standard controller either alone or with shared autonomy.
Chelsea Finn receives Samsung AI Researcher of the Year
2020 marks the inaugural Samsung AI Researcher of the Year awards. The award identifies prominent emerging researchers in the field from around the world and supports their research activities.
PhD candidate Pin Pin Tea-mangkornpan’s research featured in The Guardian
Her research involves computational psychology, focusing on using facial recognition systems to study interpersonal relationships.
Andrea Montanari's deep learning collaboration
The project expects to gain a theoretical understanding of deep learning.
STEM to SHTEM 2020 Program yields multidisciplinary research, with wealth of insights
The internship is designed for high school students who lack confidence in their STEM skills, whose talents lie outside STEM, or who aren’t yet sure about their future academic plans.
Gordon Wetzstein and PhD candidate David Lindell create algorithm that reconstructs hidden scenes
Using a new algorithm, Stanford researchers have reconstructed the movements of individual particles of light to see through clouds, fog and other obstructions.