Laboratory for Information and Decision Systems (LIDS)
Laboratory for Information and Decision Systems (LIDS)

Laboratory for Information and Decision Systems (LIDS)

Aeronautical and astronautical engineering Artificial Intelligence Autonomous vehicles Data Faculty Interview Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Robotics School of Engineering

3 Questions: Honing robot perception and mapping

Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.

Aeronautical and astronautical engineering Artificial Intelligence Autonomous vehicles Computer science and technology Drones Laboratory for Information and Decision Systems (LIDS) Lincoln Laboratory machine learning MIT Schwarzman College of Computing Research Robotics Robots School of Engineering

A step toward safe and reliable autopilots for flying

A new AI-based approach for controlling autonomous robots satisfies the often-conflicting goals of safety and stability.

Algorithms Artificial Intelligence Computer modeling Computer science and technology Data Electrical Engineering & Computer Science (eecs) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Mathematics MIT Schwarzman College of Computing National Science Foundation (NSF) Ocean science Oceanography and ocean engineering Research School of Engineering

A better way to study ocean currents

A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.

Algorithms Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Data Electrical Engineering & Computer Science (eecs) IDSS Internet Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Networks Research School of Engineering

Researchers create a tool for accurately simulating complex systems

The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.

Artificial Intelligence Broad Institute Computer science and technology Data Electrical Engineering & Computer Science (eecs) IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

A method for designing neural networks optimally suited for certain tasks

With the right building blocks, machine-learning models can more accurately perform tasks like fraud detection or spam filtering.