Master of Electrical Engineering (M.E.E.)

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Professional Master’s in Electrical Engineering (M.E.E.)

The Electrical and Computer Engineering Department at Rice University

The Master of Electrical Engineering (M.E.E.) degree is a course-based program designed to increase a student’s mastery of advanced subjects; no thesis is required. The Rice M.E.E. prepares a student to succeed and advance rapidly in today’s competitive technical marketplace.

A Professional Master’s in Electrical Engineering (M.E.E.) degree can enhance and strengthen a career in industry. The degree is designed for the recent graduate or business professional who wishes to expand his or her engineering knowledge, without completing a thesis. The degree emphasizes practical aspects of engineering, combined with management and communication coursework, allowing graduates to rapidly advance in their career.

An M.E.E. degree at Rice University provides in-depth instruction in a wide variety of specialization areas, shaping students into leaders in their respective fields, and increasing their know-how. This non-thesis degree can be completed in three or four semesters. The degree is a bridge to industry, designed to provide advanced learning and specialized training in the applied aspects of ECE technology.

Research Areas

Computer Engineering (CE)

Our research covers the full stack of systems, from integrated circuits, VLSI, architecture to operating systems. We are particularly interested in emerging platforms and application domains, such as Internet of Things (IoT), machine learning, and healthcare.




Data Science (DS)

Data Science is a growing field that integrates the tools and techniques involved in data acquisition, data analytics, and data storage to enable extraction of meaningful information from massive data sources.




DSP/Wireless Communications

Signal Processing is the analysis and transformation of signals in order to understand, simplify, or recast their structure. The understanding of how to analyze and restructure signals is applied to a wide range of areas, including: image and video analysis, statistical signal processing, and pattern recognition.




Engineering students help design ventilators

Employment Opportunities

Available as a Teaching Assistant or through the Data to Knowledge (D2K) Lab.

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Mailing: P.O. Box 1892 Houston, TX 77251-1892
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