Accelerating the pace of engineering
The 2019-20 School of Engineering MathWorks Fellows are using MATLAB and Simulink to advance discovery and innovation across disciplines.
The 2019-20 School of Engineering MathWorks Fellows are using MATLAB and Simulink to advance discovery and innovation across disciplines.
Qubits made from strontium and calcium ions can be precisely controlled by technology that already exists.
Model tags road features based on satellite images, to improve GPS navigation in places with limited map data.
A new method determines whether circuits are accurately executing complex operations that classical computers can’t tackle.
Associate Professor Yury Polyanskiy is working to keep data flowing as the “internet of things” becomes a reality.
Models that map these relationships based on patient data require fine-tuning for certain conditions, study shows.
Using mathematical theory, Virginia Williams coaxes algorithms to run faster or proves they’ve hit their maximum speed.
Machine-learning system should enable developers to improve computing efficiency in a range of applications.
As natural language processing techniques improve, suggestions are getting speedier and more relevant.
Using limited data, this automated system predicts a company’s quarterly sales.
Weekend robotics workshops help middle and high school girls dispel “computing phobia.”
Objects are posed in varied positions and shot at odd angles to spur new AI techniques.
A new computational imaging method could change how we view hidden information in scenes.
Model registers “surprise” when objects in a scene do something unexpected, which could be used to build smarter AI.
Circuit design offers a path to “spintronic” devices that use little electricity and generate practically no heat.