Institute for Medical Engineering and Science (IMES)

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Department of EECS Announces 2024 Promotions

February 28, 2024

The Department of Electrical Engineering and Computer Science (EECS) is proud to announce multiple promotions.

Twelve with MIT ties elected to the National Academy of Medicine for 2023

October 11, 2023

Five MIT faculty, along with seven additional affiliates, are honored for outstanding contributions to medical research.

Five MIT faculty members named 2023 Simons Investigators

September 14, 2023

The Simons Investigator program supports “outstanding theoretical scientists who receive a stable base of research support from the foundation, enabling them to undertake the long-term study of fundamental questions.”

Using AI, scientists find a drug that could combat drug-resistant infections

May 26, 2023

The machine-learning algorithm identified a compound that kills Acinetobacter baumannii, a bacterium that lurks in many hospital settings.

School of Engineering welcomes new faculty

March 31, 2023

Eleven new faculty members join six of the school’s academic departments and institutes.

Louis Braida, hearing aid innovator and mentor, dies at 79

November 3, 2022

Louis Braida, the Henry Ellis Warren (1894) Professor (Emeritus) in the Department of Electrical Engineering and Computer Science (EECS), died Sept. 2nd. He was 79. Braida was a

Martha Gray named Whitaker Professor in Biomedical Engineering

July 15, 2022

Martha Gray, PhD, professor of Electrical Engineering and Computer Science (EECS), has been appointed as the Whitaker Professor in Biomedical Engineering, effective July 1. Martha is also a

Collin Stultz named co-director and MIT lead of the Harvard-MIT Program in Health Sciences and Technology

June 23, 2022

MIT professor will leverage his research into machine learning and computer science, as well as his role as a practicing cardiologist, toward educating clinician-scientists and engineers.

Artificial intelligence predicts patients’ race from their medical images

May 23, 2022

Study shows AI can identify self-reported race from medical images that contain no indications of race detectable by human experts.

Deep-learning technique predicts clinical treatment outcomes

March 1, 2022

A new methodology simulates counterfactual, time-varying, and dynamic treatment strategies, allowing doctors to choose the best course of action.