Welcome to Cornell's School of Electrical and Computer Engineering
Master of Engineering (M.Eng.), in the field of Electrical and Computer Engineering
Our one-year Master of Engineering (M.Eng.) degree program from the School of Electrical and Computer Engineering is designed to put professional engineers on the fast track to success. Data show that it leads to a substantially higher starting salary. Even more important, it gives you a jump start on a more rewarding career, one in which you can apply your knowledge and skills to make a real difference in your workplace—and in the world. Find out how to apply online today!
Why choose Cornell for your M.Eng.?
While you are enrolled, you will benefit from:
- an unusually flexible curriculum
- a professional design project
- personal access to some of the world's finest teacher-researchers
- challenges that demand collaborative teamwork, critical thinking, and effective communication
- the knowledge and skills to tackle some of the world's most important problems
- and Cornell's worldwide reputation, attached to your name
ECE Fun Facts
Electricity itself was still a novelty when Cornell University introduced the nation's (and the world's) first course of study in electrical engineering in 1883.
Now, the reach of electrical and computer engineering extends from the nanoscale level of integrated electronics to terrestrial-scale power grids; from single-transistor devices to networks comprising a billion nodes.
With 40 faculty members, 300 graduate students, and more than 500 undergraduates, the School of Electrical and Computer Engineering (ECE) is the largest school in Cornell University's College of Engineering, and consistently ranks among the top ECE schools nationally*.
Our programs encompass digital and computer systems, embedded processors, digital signal processing, R. F. (wireless) systems, optical communications, atmospheric and space plasmas, solid-state electronics, integrated circuit design and fabrication, and biomedical applications such as image processing, sensors, and signal analysis.
ECE remains at the forefront of these fields, educating and training the next generation of engineers while driving the leading edge of technology.
* Cornell's Electrical Engineering and Computer Engineering each received the top ranking among research universities in the 2005 Faculty Scholarly Productivity Index. [read more]
- Source The Chronicle of Higher Education
News and Events [Faculty Awards, Student Awards, more news]
ECE Senior Skyler Schneider, wins the Douglas Whitney ’61 Award for excellence in writing in an Engineering Communications course [read more].
Cornell University's award winning Autonomous Underwater Vehicle (CUAUV) Team prepares their vessel for real world applications. [read more].
Professor Sheila Hemami has been elected an IEEE Signal Processing Society Distinguished Lecturer [read more].
ECE's Rajit Manohar appointed as Interim Associate Dean for Research and Graduate Studies in the College of Engineering [read more].
ECE Students play important role in Cornell's impressive 7th place finish in the U.S. Department of Energy's Solar Decathlon competition [read more].
David Albonesi's PhD student Mark Cianchetti has received a Ph.D. Fellowship award from the Intel Corporation [read more].
Sunil Bhave's PhD Student, Hengky Chandrahalim wins IEEE Ultrasonics, Ferroelectrics, and Frequency Control Society 2009 Student Paper Competition Award. [read more]
Clif Pollock receives the James M. and Marsha D. McCormick Award for
Excellence in Advising... [read more]
ECE faculty members (left to right) Dave Delchamps, Aaron Wagner, and Steve Wicker receive prestigious Engineering College Teaching Awards [read more]
ECE Professors José Martínez and Kevin Tang receive 2009 IBM Faculty Awards. [read more]
Approximating the capacity of wireless networks
Extending Shannon's theory for point-to-point communication systems to the network setting has been one of the greatest challenges in information theory over the past few decades. In this project we develop simple, deterministic channel models that capture the main features of the wireless medium, and utilized them to approximate the capacity of more complex networks. Using this approach, we have already made progress on several long-standing open problems in the field [read more].
-- Assistant Professor Salman Avestimehr