Institute for Medical Engineering and Science (IMES)
Institute for Medical Engineering and Science (IMES)

Justin Solomon appointed associate dean of engineering education

MIT faculty member in electrical engineering and computer science to focus on innovation in engineering education and new pedagogical approaches.

Beacon Biosignals is mapping the brain during sleep

Founded by Jake Donoghue PhD ’19 and former MIT researcher Jarrett Revels, the company is creating an AI-driven platform to help diagnose and treat disease.

How to create “humble” AI

An MIT-led team is designing artificial intelligence systems for medical diagnosis that are more collaborative and forthcoming about uncertainty.

3 Questions: Building predictive models to characterize tumor progression

Assistant Professor Matthew Jones is working to decode molecular processes on the genetic, epigenetic, and microenvironment levels to anticipate how and when tumors evolve to resist treatment.

Using synthetic biology and AI to address global antimicrobial resistance threat

Driven by overuse and misuse of antibiotics, drug-resistant infections are on the rise, while development of new antibacterial tools has slowed.

AI algorithm enables tracking of vital white matter pathways

Opening a new window on the brainstem, a new tool reliably and finely resolves distinct nerve bundles in live diffusion MRI scans, revealing signs of injury or disease.

3 Questions: Using AI to accelerate the discovery and design of therapeutic drugs

Professor James Collins discusses how collaboration has been central to his research into combining computational predictions with new experimental platforms.

Why it’s critical to move beyond overly aggregated machine-learning metrics

New research detects hidden evidence of mistaken correlations — and provides a method to improve accuracy.

MIT scientists investigate memorization risk in the age of clinical AI

New research demonstrates how AI models can be tested to ensure they don’t cause harm by revealing anonymized patient health data.

Researchers discover a shortcoming that makes LLMs less reliable

Large language models can learn to mistakenly link certain sentence patterns with specific topics — and may then repeat these patterns instead of reasoning.