Electrical engineers design the most sophisticated systems ever built. From computers with billions of transistors to microgrids fed by renewable energy sources, from algorithms that predict disease to solar cells and electric vehicles, electrical engineering touches all parts of modern society. 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.
Our research is interdisciplinary by nature, and has far-reaching effects on almost every field of human activity, including energy and climate, human health, communications and computation, finance and music. We make the future.
Our research covers a wide range of topics of this fast-evolving field, advancing how machines learn, predict, and control, while also making them secure, robust and trustworthy. Research covers both the theory and applications of ML. This broad area studies ML theory (algorithms, optimization, …), statistical learning (inference, graphical models, causal analysis, …), deep learning, reinforcement learning, symbolic reasoning ML systems, as well as diverse hardware implementations of ML.
We develop the technology and systems that will transform the future of biology and healthcare. Specific areas include biomedical sensors and electronics, nano- and micro-technologies, imaging, and computational modeling of disease.
We develop the next generation of wired and wireless communications systems, from new physical principles (e.g., light, terahertz waves) to coding and information theory, and everything in between.
We design the next generation of computer systems. Working at the intersection of hardware and software, our research studies how to best implement computation in the physical world. We design processors that are faster, more efficient, easier to program, and secure. Our research covers systems of all scales, from tiny Internet-of-Things devices with ultra-low-power consumption to high-performance servers and datacenters that power planet-scale online services. We design both general-purpose processors and accelerators that are specialized to particular application domains, like machine learning and storage. We also design Electronic Design Automation (EDA) tools to facilitate the development of such systems.
We bring some of the most powerful tools in computation to bear on design problems, including modeling, simulation, processing and fabrication.
Educational technology combines both hardware and software to enact global change, making education accessible in unprecedented ways to new audiences. We develop the technology that makes better understanding possible.
Our research spans a wide range of materials that form the next generation of devices, and includes groundbreaking research on graphene & 2D materials, quantum computing, MEMS & NEMS, and new substrates for computation.
Our research focuses on solving challenges related to the transduction, transmission, and control of energy and energy systems. We develop new materials for energy storage, devices and power electronics for harvesting, generation and processing of energy, and control of large-scale energy systems.
Our field deals with the design and creation of sophisticated circuits and systems for applications ranging from computation to sensing.
Our research focuses on the creation of materials and devices at the nano scale to create novel systems across a wide variety of application areas.
Our research focuses on robotic hardware and algorithms, from sensing to control to perception to manipulation.
Signal processing focuses on algorithms and hardware for analyzing, modifying and synthesizing signals and data, across a wide variety of application domains. As a technology it plays a key role in virtually every aspect of modern life including for example entertainment, communications, travel, health, defense and finance.
From distributed systems and databases to wireless, the research conducted by the systems and networking group aims to improve the performance, robustness, and ease of management of networks and computing systems.
Our theoretical research includes quantification of fundamental capabilities and limitations of feedback systems, inference and control over networks, and development of practical methods and algorithms for decision making under uncertainty.
Gene Dresselhaus, influential research scientist in solid-state physics, dies at 91
Over 50 years at MIT, Dresselhaus made lasting contributions to materials science within the research group of longtime collaborator and wife, Mildred Dresselhaus.
Aziza Almanakly, Belinda Li Selected to Receive Clare Boothe Luce Graduate Fellowship for Women
The rigorous selection process for this prestigious fellowship took into account the two students’ outstanding track record of scientific achievement and inquiry, as well as their contributions to the STEM community.
Allen Liu ’20, Alex Miller ’21, and Isabelle Yan Phinney ’20. Photos courtesy of the Hertz Foundation. The Fannie and John Hertz Foundation has selected three MIT students as…
Assistant Professor Long Ju and colleagues have built a new, customized version of a laboratory tool known as near-field infrared nanoscopy and spectroscopy for MIT users. It and…
Left to right: Álvaro Fernández Galiana, Fatima Hussain, Sirma Orguc, and Rebecca Pinals have been named as Schmidt Science Fellows, an honor created in 2017 to encourage young…