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  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.
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  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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Peter Szolovits

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Professor of Computer Science and Engineering; [AI+D and CS]

(617) 253-3476

Office: 32-254

Research Areas

AI for Healthcare and Life Sciences
Artificial Intelligence + Machine Learning
Biological and Medical Devices and Systems

Latest News

December 2, 2021

2021 EECS Awards

It’s nearing the end of 2021, and we want to celebrate the accomplishments and contributions of our incredible EECS community by sharing some of the awards given by...

Want to know what software-driven health care looks like? This class offers some clues

An EECS-based course that combines machine learning and health care explores the promise of applying artificial intelligence to medicine.

Roundup: EECS faculty awards, prizes, fellowships, and other honors, 2018-2019

Constantinos Daskalakis and Vivienne Sze were among more than 40 EECS faculty members honored for excellence over the past academic year.

EECS Celebrates: Honoring the department’s outstanding contributors

The EECS community came together to celebrate faculty, student, and staff achievements over the past year.

February 18, 2019

Four EECS faculty members are named as world leaders in AI for health

Professors Barzilay, Jaakkola, Kellis, and Szolovits are among 100 leaders recognized by a top technology think tank.

MIT Electrical Engineering &
Computer Science Department

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