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Master of Electrical and Computer Engineering (MECE) Degree

The Master of Electrical and Computer Engineering (MECE) degree is a non-thesis master's degree that requires students to complete a minimum of 10 courses (30-32 credit hours) to satisfy degree requirements.

Program Learning Outcomes

Upon completing the MECE degree, students will be able to:

1. Design and implement technical solutions to real-world problems that reflect an advanced command of principles in mathematics and science.
2. Communicate effectively expert analysis of technical problems and features of proposed solutions to stakeholders.
3. Practice as an expert specialist in at least one of the major sub-fields of electrical and computer engineering.

Requirements for the MECE Degree

• A minimum of 10 courses (30-32 credit hours) to satisfy degree requirements.
• A minimum of 30 credit hours of graduate-level study (graduate semester credit hours, coursework at the 500-level or above).
• A minimum of 27 graduate semester credit hours must be taken at Rice University.
• A minimum of 24 graduate semester credit hours must be taken in standard or traditional courses (with a course type of lecture, seminar, laboratory, lecture/laboratory).
• A minimum residency enrollment of one fall or spring semester of part-time graduate study at Rice University.
• A minimum of 3 courses (9 credit hours) from the Capstone Requirement.
  • 1 course (3 credit hours) to fulfill the Capstone: Foundations requirement.
  • A minimum of 2 semesters (6 credit hours) of ELEC 594 to fulfill the Capstone: Experience Project requirement.
• A minimum of 1 course (3 credit hours) from the Engineering Communications Requirement.
• A minimum of 2 courses (6 credit hours) from the Engineering Software Development Requirement.
• A minimum of 2 courses (6 credit hours) in one area of specialization.
• A minimum of 2 courses (6 credit hours) from the Elective Requirements.
• Required enrollment in ELEC 698 each semester in residence at Rice University.
• A maximum of 1 course (3 graduate semester credit hours) from transfer credit.
• A minimum overall GPA of 2.67 or higher in all Rice coursework.
• A minimum program GPA of 3.00 or higher in all Rice coursework that satisfies requirements for the non-thesis master's degree with a minimum grade of C (2.00 grade points) in each course.

Areas of Specialization

Students must complete a minimum of 2 courses (6 credit hours) from one Area of Specialization. The MECE degree program offers seven areas of specialization:

• AI & Systems
• Computer Engineering
• Computer Vision
• Digital Health
• Neuroengineering
• Quantum Engineering
• Wireless Systems

Area of Specialization: AI & Systems

Select 2 courses (6 credit hours) from the following:

• ELEC 502 / COMP 502 / STAT 502: NEURAL MACHINE LEARNING I
• ELEC 506: LINEAR ALGEBRA FOR DATA SCIENCE
• ELEC 515: MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
• ELEC 519: DATA SCIENCE AND DYNAMICAL SYSTEMS
• ELEC 531: STATISTICAL SIGNAL PROCESSING
• ELEC 533 / CMOR 553 / STAT 583: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
• ELEC 535: INFORMATION THEORY
• ELEC 546 / COMP 546: INTRODUCTION TO COMPUTER VISION
• ELEC 558: DIGITAL SIGNAL PROCESSING
• ELEC 575: LEARNING FROM SENSOR DATA
• ELEC 576 / COMP 576: A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
• ELEC 578: INTRODUCTION TO MACHINE LEARNING
• ELEC 631: ADVANCED MACHINE LEARNING

Area of Specialization: Computer Engineering

Select 2 courses (6 credit hours) from the following:

• ELEC 514: WIRELESS INTEGRATED CIRCUITS AND SYSTEMS
• ELEC 515: MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
• ELEC 517: MICROWAVE ENGINEERING
• ELEC 521: ADVANCED DIGITAL INTEGRATED CIRCUITS DESIGN
• ELEC 522: ADVANCED VLSI DESIGN
• ELEC 523: INTRODUCTION TO MICROFABRICATION
• ELEC 526 / COMP 526: HIGH PERFORMANCE COMPUTER ARCHITECTURE
• ELEC 527: VLSI SYSTEMS DESIGN
• ELEC 534: HARDWARE VERIFICATION
• ELEC 537: INTELLIGENT MOBILE SYSTEMS
• ELEC 543: ADVANCED HIGH-SPEED SYSTEM DESIGN
• ELEC 553: MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION
• ELEC 554 / COMP 554: COMPUTER SYSTEMS ARCHITECTURE
• ELEC 574: UBIQUITOUS AND WEARABLE COMPUTING

Area of Specialization: Computer Vision

Select 2 courses (6 credit hours) from the following:

• ELEC 502 / COMP 502 / STAT 502: NEURAL MACHINE LEARNING I
• ELEC 515: MACHINE LEARNING FOR RESOURCE-CONSTRAINED PLATFORMS
• ELEC 531: STATISTICAL SIGNAL PROCESSING
• ELEC 533 / CMOR 553 / STAT 583: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
• ELEC 537: INTELLIGENT MOBILE SYSTEMS
• ELEC 541: 3D VISION: FROM AUTONOMOUS CARS TO THE METAVERSE
• ELEC 542: GENERATIVE AI FOR IMAGE DATA
• ELEC 546 / COMP 546: INTRODUCTION TO COMPUTER VISION
• ELEC 549: COMPUTATIONAL PHOTOGRAPHY
• ELEC 553: MOBILE AND EMBEDDED SYSTEM DESIGN AND APPLICATION
• ELEC 555: IMAGING AND VISION FOR ROBOTICS
• ELEC 558: DIGITAL SIGNAL PROCESSING
• ELEC 575: LEARNING FROM SENSOR DATA
• ELEC 576 / COMP 576: A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
• ELEC 578: INTRODUCTION TO MACHINE LEARNING
• ELEC 631: ADVANCED MACHINE LEARNING

Area of Specialization: Digital Health

Select 2 courses (6 credit hours) from the following:

• ELEC 533 / CMOR 553 / STAT 583: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
• ELEC 541: 3D VISION: FROM AUTONOMOUS CARS TO THE METAVERSE
• ELEC 542: GENERATIVE AI FOR IMAGE DATA
• ELEC 545: INTRODUCTION TO DIGITAL IMAGE AND VIDEO PROCESSING
• ELEC 546 / COMP 546: INTRODUCTION TO COMPUTER VISION
• ELEC 547: ENGINEERING INCLUSIVE BIOSIGNAL HUMAN-MACHINE INTERFACES
• ELEC 558: DIGITAL SIGNAL PROCESSING
• ELEC 570: DISTRIBUTED METHODS FOR OPTIMIZATION AND MACHINE LEARNING
• ELEC 575: LEARNING FROM SENSOR DATA
• ELEC 576 / COMP 576: A PRACTICAL INTRODUCTION TO DEEP MACHINE LEARNING
• ELEC 578: INTRODUCTION TO MACHINE LEARNING
• ELEC 582: IMAGING OPTICS

Area of Specialization: Neuroengineering

Select 2 courses (6 credit hours) from the following:

• ELEC 502 / COMP 502 / STAT 502: NEURAL MACHINE LEARNING I
• ELEC 523: INTRODUCTION TO MICROFABRICATION
• ELEC 532: NEURAL INTERFACE ENGINEERING LABORATORY
• ELEC 533 / CMOR 553 / STAT 583: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
• ELEC 547: ENGINEERING INCLUSIVE BIOSIGNAL HUMAN-MACHINE INTERFACES
• ELEC 548 / BIOE 548: MACHINE LEARNING AND SIGNAL PROCESSING FOR NEURO ENGINEERING
• ELEC 582: IMAGING OPTICS
• ELEC 587: INTRODUCTION TO NEUROENGINEERING: MEASURING AND MANIPULATING NEURAL ACTIVITY
• ELEC 588 / CMOR 615 / NEUR 615: THEORETICAL NEUROSCIENCE I: BIOPHYSICAL MODELING OF CELLS AND CIRCUITS
• ELEC 589: NEURAL COMPUTATION
• ELEC 680 / BIOE 680: NANO-NEUROTECHNOLOGY
• ELEC 682: SPOTLIGHT ON LATEST NEUROTECHNOLOGY

Area of Specialization: Quantum Engineering

Select 2 courses (6 credit hours) from the following:

• ELEC 517: MICROWAVE ENGINEERING
• ELEC 523: INTRODUCTION TO MICROFABRICATION
• ELEC 560: PHYSICS OF SENSOR MATERIALS AND NANOSENSOR TECHNOLOGY
• ELEC 562: OPTOELECTRONIC DEVICES
• ELEC 563 / PHYS 563: INTRODUCTION TO SOLID STATE PHYSICS I
• ELEC 566: NANOPHOTONICS AND METAMATERIALS
• ELEC 568: INTRODUCTION TO QUANTUM COMPUTING WITH QISKIT
• ELEC 569 / PHYS 569: ULTRAFAST OPTICAL PHENOMENA
• ELEC 571: IMAGING AT THE NANOSCALE
• ELEC 572: FINITE ELEMENT METHOD FOR MULTIPHYSICS MODELING
• ELEC 580: QUANTUM MECHANICS AND REAL-WORLD APPLICATIONS
• ELEC 584: QUANTUM PHYSICS IN SEMICONDUCTOR DEVICES
• ELEC 603: FOUNDATIONAL AND CURRENT TOPICS IN NANOPHOTONICS RESEARCH
• ELEC 605 / PHYS 605: COMPUTATIONAL ELECTRODYNAMICS AND NANOPHOTONICS
• ELEC 660: QUANTUM INFORMATION SCIENCE AND TECHNOLOGY

Area of Specialization: Wireless Systems

Select 2 courses (6 credit hours) from the following:

• ELEC 514: WIRELESS INTEGRATED CIRCUITS AND SYSTEMS
• ELEC 517: MICROWAVE ENGINEERING
• ELEC 531: STATISTICAL SIGNAL PROCESSING
• ELEC 533 / CMOR 553 / STAT 583: INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS
• ELEC 535: INFORMATION THEORY
• ELEC 538: ADVANCED WIRELESS NETWORKING
• ELEC 539: INTRODUCTION TO COMMUNICATION NETWORKS
• ELEC 551: MODERN COMMUNICATION THEORY AND PRACTICE
• ELEC 558: DIGITAL SIGNAL PROCESSING
• ELEC 573: NETWORK SCIENCE AND ANALYTICS

Policies for the MECE Degree

Department of Electrical and Computer Engineering Graduate Program Handbook

The General Announcements (GA) is the official Rice curriculum. As an additional resource for students, the department of Electrical and Computer Engineering publishes a graduate program handbook.

Transfer Credit

For Rice University's policy regarding transfer credit, see the university's transfer credit policy. Some departments and programs have additional restrictions on transfer credit. Requests for transfer credit must be approved for Rice equivalency by the appropriate academic department offering the Rice equivalent course and by the Office of Graduate and Postdoctoral Studies (GPS).

Departmental Transfer Credit Guidelines

Students pursuing the MECE degree should be aware of the following departmental transfer credit guideline:

• No more than 1 course (3 credit hours) of transfer credit from U.S. or international universities of similar standing as Rice may apply towards the degree.

Teaching Assistant Requirement

Students must be enrolled in at least 5 credit hours to be able to serve as a teaching assistant (TA).

Opportunities for the MECE Degree

Fifth-Year Master's Degree Option for Rice Undergraduate Students

In certain situations and with some terminal master's degree programs, Rice students have an option to pursue a master's degree by adding an additional fifth year to their four years of undergraduate studies. Advanced Rice undergraduate students in good academic standing typically apply to the master's degree program during their junior or senior year. Upon acceptance, depending on course load, financial aid status, and other variables, they may then start taking some required courses of the master's degree program. A plan of study will need to be approved by the student's undergraduate major advisor and the master's degree program director.