New control system teaches soft robots the art of staying safe
MIT CSAIL and LIDS researchers developed a mathematically grounded system that lets soft robots deform, adapt, and interact with people and objects, without violating safety limits.
New method improves the reliability of statistical estimations
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
Prognostic tool could help clinicians identify high-risk cancer patients
Using a versatile problem-solving framework, researchers show how early relapse in lymphoma patients influences their chance for survival.
MIT Schwarzman College of Computing welcomes 11 new faculty for 2025
The faculty members occupy core computing and shared positions, bringing varied backgrounds and expertise to the MIT community.
This new approach could lead to enhanced AI models for drug and materials discovery.
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Unpacking the bias of large language models
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
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.
A new method for detecting gene-expression patterns linked to lineage progression, providing a powerful tool for studying cell state memory across biological systems.
MIT researchers developed a new approach for assessing predictions with a spatial dimension, like forecasting weather or mapping air pollution.