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

Inroads to personalized AI trip planning

A new framework from the MIT-IBM Watson AI Lab supercharges language models, so they can reason over, interactively develop, and verify valid, complex travel agendas.

Melding data, systems, and society

A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.

AI-enabled control system helps autonomous drones stay on target in uncertain environments

The system automatically learns to adapt to unknown disturbances such as gusting winds.

An anomaly detection framework anyone can use

PhD student Sarah Alnegheimish wants to make machine learning systems accessible.

The sweet taste of a new idea

Sendhil Mullainathan brings a lifetime of unique perspectives to research in behavioral economics and machine learning.

With AI, researchers predict the location of virtually any protein within a human cell

Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.

Study shows vision-language models can’t handle queries with negation words

Words like “no” and “not” can cause this popular class of AI models to fail unexpectedly in high-stakes settings, such as medical diagnosis.

New tool evaluates progress in reinforcement learning

“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

Designing a new way to optimize complex coordinated systems

Using diagrams to represent interactions in multipart systems can provide a faster way to design software improvements.

A faster way to solve complex planning problems

By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.