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

Laboratory for Information and Decision Systems (LIDS)

Algorithms Artificial Intelligence Computer science and technology Electrical engineering and computer science (EECS) Faculty Game theory Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Profile School of Engineering

Games people — and machines — play: Untangling strategic reasoning to advance AI

Assistant Professor Gabriele Farina mines the foundations of decision-making in complex multi-agent scenarios.

Artificial Intelligence Computer science and technology computer-vision Jameel Clinic Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Technology and society

Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models

A new debiasing technique called WRING avoids creating or amplifying biases that can occur with existing debiasing approaches.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Defense Advanced Research Projects Agency (DARPA) Electrical engineering and computer science (EECS) Ethics Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Evaluating the ethics of autonomous systems

MIT researchers developed a testing framework that pinpoints situations where AI decision-support systems are not treating people and communities fairly.

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology Electrical engineering and computer science (EECS) IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research Robotics School of Engineering Supply chains

AI system learns to keep warehouse robot traffic running smoothly

This new approach adapts to decide which robots should get the right of way at every moment, avoiding congestion and increasing throughput.

Artificial Intelligence Computer science and technology Electrical engineering and computer science (EECS) Human-computer interaction Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research School of Engineering

A better method for identifying overconfident large language models

This new metric for measuring uncertainty could flag hallucinations and help users know whether to trust an AI model.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Careers Collaboration Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology Electrical engineering and computer science (EECS) Industry Laboratory for Information and Decision Systems (LIDS) machine learning Mechanical engineering MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Natural language processing Research Robotics School of Engineering

MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact

Academia-industry relationship is an early-stage accelerator, supporting professional progress and research.

Aeronautical and astronautical engineering Algorithms Artificial Intelligence Computer science and technology computer-vision Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing MIT-IBM Watson AI Lab Research Robotics School of Engineering

A better method for planning complex visual tasks

A new hybrid system could help robots navigate in changing environments or increase the efficiency of multirobot assembly teams.

Algorithms Artificial Intelligence Biological engineering Biology Broad Institute Cells Computer science and technology Diagnostics Electrical engineering and computer science (EECS) Genetics health IDSS Laboratory for Information and Decision Systems (LIDS) machine learning Medicine MIT Schwarzman College of Computing National Institutes of Health (NIH) Research School of Engineering

AI to help researchers see the bigger picture in cell biology

By providing holistic information on a cell, an AI-driven method could help scientists better understand disease mechanisms and plan experiments.

Artificial Intelligence Collaboration cybersecurity Graduate, postdoctoral IDSS Laboratory for Information and Decision Systems (LIDS) MIT Schwarzman College of Computing Oceanography and ocean engineering Profile Research School of Engineering School of Humanities Arts and Social Sciences Security and military studies Students Technology and policy

Enhancing maritime cybersecurity with technology and policy

Strahinja Janjusevic brings an international perspective and US Naval Academy education to his graduate research in the MIT Technology and Policy Program.

Algorithms Artificial Intelligence Cities Civil and environmental engineering Climate change Computer modeling Computer science and technology Electrical engineering and computer science (EECS) Emissions IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Energy Initiative MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering Sustainability Transportation

Parking-aware navigation system could prevent frustration and emissions

By minimizing the need to drive around looking for a parking spot, this technique can save drivers up to 35 minutes — and give them a realistic estimate of total travel time.