AI model identifies certain breast tumor stages likely to progress to invasive cancer
The model could help clinicians assess breast cancer stage and ultimately help in reducing overtreatment.
Laboratory for Information and Decisions Systems (LIDS)
How to assess a general-purpose AI model’s reliability before it’s deployed
A new technique enables users to compare several large models and choose the one that works best for their task.
Machine learning and the microscope
PhD student Xinyi Zhang is developing computational tools for analyzing cells in the age of multimodal data.
When to trust an AI model
More accurate uncertainty estimates could help users decide about how and when to use machine-learning models in the real world.
The tenured engineers of 2024
Twelve faculty members have been granted tenure in six units across MIT’s School of Engineering.
Study reveals why AI models that analyze medical images can be biased
These models, which can predict a patient’s race, gender, and age, seem to use those traits as shortcuts when making medical diagnoses.
A data-driven approach to making better choices
In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.
School of Engineering welcomes new faculty
Fifteen new faculty members join six of the school’s academic departments.
Three from MIT awarded 2024 Guggenheim Fellowships
MIT professors Roger Levy, Tracy Slatyer, and Martin Wainwright appointed to the 2024 class of “trail-blazing fellows.”
A crossroads for computing at MIT
The MIT Schwarzman College of Computing building will form a new cluster of connectivity across a spectrum of disciplines in computing and artificial intelligence.
Using generative AI to improve software testing
MIT spinout DataCebo helps companies bolster their datasets by creating synthetic data that mimic the real thing.
Dealing with the limitations of our noisy world
Tamara Broderick uses statistical approaches to understand and quantify the uncertainty that can affect study results.
New AI model could streamline operations in a robotic warehouse
By breaking an intractable problem into smaller chunks, a deep-learning technique identifies the optimal areas for thinning out traffic in a warehouse.
Generative AI for smart grid modeling
MIT LIDS awarded funding from the Appalachian Regional Commission as part of a multi-state collaborative project to model and test new smart grid technologies for use in rural areas.