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- Electrical Engineering
  
  Electrical Engineers design systems that sense, process, and transmit energy and information. We leverage computational, theoretical, and experimental tools to develop groundbreaking sensors and energy transducers, new physical substrates for computation, and the systems that address the shared challenges facing humanity.
- Computer Science
  
  Computer science deals with the theory and practice of algorithms, from idealized mathematical procedures to the computer systems deployed by major tech companies to answer billions of user requests per day.
- Artificial Intelligence + Decision-making
  
  Artificial Intelligence and Decision-making combines intellectual traditions from across computer science and electrical engineering to develop techniques for the analysis and synthesis of systems that interact with an external world via perception, communication, and action; while also learning, making decisions and adapting to a changing environment.
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Caroline Uhler

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Andrew (1956) and Erna Viterbi Professor of Engineering; Professor of EECS and in IDSS, [AI+D]

(617) 253-4181

Office: 32-D634

Research Areas

AI for Healthcare and Life Sciences
Artificial Intelligence + Machine Learning

Latest News

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.

February 19, 2025

Tracking gene expression changes through cell lineage progression with PORCELAN

A new method for detecting gene-expression patterns linked to lineage progression, providing a powerful tool for studying cell state memory across biological systems.

November 12, 2024

A causal theory for studying the cause-and-effect relationships of genes

By sidestepping the need for costly interventions, a new method could potentially reveal gene regulatory programs, paving the way for targeted treatments.

Department of EECS names new chair recipients

The new chairs became effective July 1.

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.

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