Computer science meets economics
Constantinos Daskalakis adapts techniques from theoretical computer science to game theory.
Constantinos Daskalakis adapts techniques from theoretical computer science to game theory.
Low-power chip processes 3-D camera data, could enable wearable device to guide the visually impaired.
Automatic bug-repair system fixes 10 times as many errors as its predecessors.
System for handling massive digital datasets could make impossibly complex problems solvable.
Motion-planning algorithms allow drones to do donuts, figure-eights in object-filled environments.
Model that predicts time from gate departure to takeoff could cut airport congestion, fuel waste.
“3-D physics engine” from the Computer Science and Artificial Intelligence Laboratory simulates the human brain to infer physical properties.
Algorithms could learn to recognize objects from a few examples, not millions; may better model human cognition.
Future versions of an algorithm from the Computer Science and Artificial Intelligence Lab could help with teaching, marketing, and memory improvement.
Robots, 3-D printers, and a surprise guest aim to get students excited about computer science.
Instrument scans images 2,000 times faster than commercial models.
Google experiments suggest that the D-Wave computer exploits quantum phenomena.
Looking back on the year that was: Highlights from the Computer Science and Artificial Intelligence Lab in 2015.
Algorithms exploiting light’s polarization boost resolution of commercial depth sensors 1,000-fold.
Team led by Professor Russ Tedrake of CSAIL to develop algorithms for 6-foot-tall “Valkyrie” robot to travel to Mars and beyond.