Overview

The computer engineering masters focuses on the design and development of computer and computer-integrated systems, with consideration to such engineering factors as function, performance, security, and sustainability. Computer engineers design and build these systems to meet application and system requirements with attention to the hardware-software interaction. The program emphasizes the careful adoption of design methodology and the application of sophisticated engineering tools. The intensive programming and laboratory work requirements ensure significant, high level, specialized knowledge, and experience with modern facilities and state-of-the-art design tools.

The MS degree in computer engineering provides students with a high level of specialized knowledge in computer engineering, strengthening their ability to successfully formulate solutions to current technical problems, and offers a significant independent learning experience in preparation for further graduate study or for continuing professional development at the leading edge of the discipline. The program accommodates applicants with undergraduate degrees in computer engineering or related programs such as electrical engineering or computer science. (Some additional bridge courses may be required for applicants from undergraduate degrees outside of computer engineering).

Program goals

The MS in computer engineering prepares graduate students to:

  • demonstrate independent learning, which is necessary in order to update their skills in a changing workplace and economy, and
  • successfully formulate solutions to current technical problems in computer engineering or related disciplines.

Plan of study

The degree requires 30 semester credit hours and includes Analytical Topics in Computer Engineering (CMPE-610), two flexible core courses, four to six graduate electives, one semester of graduate seminar, and the option of completing either a thesis or a graduate project. The core courses and graduate electives provide breadth and depth of knowledge. The Computer Engineering Graduate Seminar (CMPE-795) exposes students to a variety of topics presented by researchers from within RIT, industry, and other universities, and guides students to choose either a thesis or project as their culminating experience.

Students who pursue the thesis option complete nine semester credit hours of thesis research (CMPE-790) with a faculty adviser in order to answer a fundamental science/engineering question that contributes to new knowledge in the field. Students formulate the problem under the faculty adviser's guidance and conduct extensive quantitative or qualitative analyses with sound methodology. Research findings should be repeatable and generalizable, with sufficient quality to make them publishable in technical conferences and/or journals.

Students who pursue the project option take six credits of graduate electives directly related to their project deliverables and three credits of Graduate Project (CMPE-792), which requires students to professionally execute a project under the supervision of a faculty adviser. The project generally addresses an immediate and practical problem, a scholarly undertaking that can have tangible outcomes, where students are expected to give a presentation or demonstration of the final deliverables of the project.

Research tracks/Flexible core/Graduate electives

Flexible core

Students must select one course from each of the following flexible core clusters.

Computer architecture and digital design

  • CMPE-630 Digital IC Design
  • CMPE-660 Reconfigurable Computing
  • CMPE-755 High-Performance Architecture

Computing, communications, and algorithms

  • CMPE-670 Data and Communication Networks
  • CMPE-655 Multiple Processor Systems
  • CMPE-677 Machine Intelligence

Graduate Electives

Students may select four to six graduate electives. At least two electives must be from the computer engineering department (courses that begin with the prefix CMPE). Students must consult with their adviser and obtain department approval for using other graduate-level courses as electives. Research tracks are available in the following areas:

Advanced computer architecture—Computer architecture deals with hardware resource management, instruction set architectures and their close connection with the underlying hardware, and the interconnection and communication of those hardware components. Some of the current computer architecture challenges that are being tackled in the computer engineering department include energy efficient architectures, high-performance architectures, graphic processing units (GPUs), reconfigurable hardware, chip multiprocessors, and Networks-on-Chips.

Computer vision and machine intelligence—Visual information is ubiquitous and ever more important for applications such as robotics, health care, human-computer interaction, biometrics, surveillance, games, entertainment, transportation, and commerce. Computer vision focuses on extracting information from image and video data for modeling, interpretation, detection, tracking, and recognition. Machine intelligence methods deal with human-machine interaction, artificial intelligence, agent reasoning, and robotics. Algorithm development for these areas spans image processing, pattern recognition, and machine learning, and is intimately related to system design and hardware implementations.

Digital systems—Next generation computing systems demand high computational density, intelligence on the device, small form factor, low energy dissipation, and high performance. This is enabled by the integration of CMOS and emerging technologies at the massive-scale. Digital systems research focuses on designing energy efficient architectures; neuromorphic computing systems; 3D architectures; power and thermal management; and studying the applicability of emerging technologies for new AI platforms.

Networks and security—The prevalence of interconnected computing, sensing, and actuating devices have transformed our way of life. Ubiquitous access to data using/from these devices with reliable performance as well as security assurance presents exciting challenges for engineers and scientists. Resilient to environmental uncertainty, system failures, and cyber attacks requires advances in hardware, software, and networking techniques. The research track in networks and security focuses on intelligent wireless and sensor networks, cryptographic engineering, and predictive cyber situation awareness.

Signal processing and controls —This research area is concerned with algorithms and devices used at the core of systems that interact with our physical world. As such, this area considers the sensing, analysis, and modeling of dynamic systems with the intent of measuring information about a system, communicating this information, and processing it to adapt its behavior. Application areas are robust feedback-based control where uncertainty in the dynamics and environment must be considered during the design process and signal processing algorithms and devices for system sensing and adaptation.

Additional graduate-level math courses

Additional math courses also may be used as electives. Students must consult with their adviser and obtain department approval for using these or other graduate-level math courses towards electives.

Industries

  • Aerospace
  • Insurance
  • Government (Local, State, Federal)
  • Internet and Software
  • Defense
  • Electronic and Computer Hardware
  • Manufacturing

Typical Job Titles

  • Software Engineer
  • Embedded Firmware Engineer
  • Junior Analyst Programmer
  • Software Applications Engineer
  • Software Developer
  • Systems Engineer
  • Test Engineer

Curriculum

Computer engineering (thesis option), MS degree, typical course sequence

First Year

  • CMPE-610 Analytical Topics in Computer Engineering
  • Flexible Core Course†
  • Choose two of the following flexible core courses:
    • CMPE-630 Digital Integrated Circuit Design
    • CMPE-655 Multiple Processor Systems
    • CMPE-660 Reconfigurable Computing
    • CMPE-670 Data and Communication Network
    • CMPE-685 Computer Vision
  • CMPE-790 Thesis and Project Initiation Seminar
  • CMPE-796 Thesis and Project Initiation Seminar
  • Graduate Electives*

Second Year

  • CMPE-790 Thesis
  • Graduate Elective

† Students may choose one of the following courses to fulfill this requirement: Digital IC Design (CMPE-630), Multiple Processor Systems (CMPE-655), Reconfigurable Computing (CMPE-660), Data and Communications Networks (CMPE-670), or Computer Vision (CMPE-685).

Computer engineering (project option), MS degree, typical course sequence

First Year

  • CMPE-610 Analytical Topics in Computer Engineering
  • Choose two of the following flexible core courses:
    • CMPE-630 Digital Integrated Circuit Design
    • CMPE-655 Multiple Processor Systems
    • CMPE-660 Reconfigurable Computing
    • CMPE-670 Data and Communication Network
    • CMPE-685 Computer Vision
  • CMPE-795Graduate Seminar
  • Graduate Electives*

Second Year

  • CMPE-792 Graduate Project
  • Project Focus Electives
  • Graduate Elective

† Students may choose one of the following courses to fulfill this requirement: Digital IC Design (CMPE-630), Multiple Processor Systems (CMPE-655), Reconfigurable Computing (CMPE-660), Data and Communications Networks (CMPE-670), or Computer Vision (CMPE-685).

Computer architecture

  • CMPE-655 Multiple Processor Systems
  • CMPE-660 Reconfigurable Computing
  • CMPE-655 Performance Engineering of Real-time and Embedded Systems
  • CMPE-731 Design and Testing of Multi-core Chips
  • CMPE-750 Advanced Computer Architecture
  • CMPE-755 High-Performance Architectures
  • CSCI-652 Distributed Systems
  • CSCI-654 Foundations of Parallel Computing
  • CSCI-742 Compiler Construction

Computer vision and machine intelligence

  • CMPE-680 Digital Image Processing Algorithms
  • CMPE-685 Computer Vision
  • CSCI-713 Applied Perception in Graphics and Visualization
  • CSCI-715 Applications in Virtual Reality
  • CSCI-719 Topics in Computer Graphics
  • CSCI-720 Big Data Analytics
  • CSCI-731 Advanced Computer Vision
  • EEEE-647 Artificial Intelligence Explorations
  • EEEE-670 Pattern Recognition
  • EEEE-685 Principles of Robotics
  • EEEE-780
  • Digital Video Processing
  • EEEE-781 Image and Video Compression
  • IMGS-756 Advanced Digital Image Processing

Integrated circuits and systems

  • CMPE-630 Digital Integrated Circuit Design
  • CMPE-655 Multiple Processor Systems
  • CMPE-730 Advanced Digital Integrated Circuit Design
  • CMPE-731 Design and Testing of Multi-core Chips
  • CMPE-750 Advanced Computer Architecture
  • EEEE-602 Random Signals and Noise
  • EEEE-610 Analog Electronics
  • EEEE-620 Design of Digital Systems
  • EEEE-712 Advanced Field Effect Devices
  • EEEE-713 Solid State Physics
  • EEEE-720 Advanced Topics in Digital Systems Design
  • EEEE-726 Mixed Signal IC Design
  • EEEE-730 Advanced Analog IC Design

Networks and security

  • CMPE-661 Hardware and Software Design for Cryptographic Applications
  • CMPE-670 Data and Communication Networks
  • CMPE-770 Wireless Networks
  • CSCI-642 Secure Coding
  • CSCI-662 Foundations of Cryptography
  • CSCI-720 Big Data Analytics
  • CSCI-734 Foundations of Security Measurement and Evaluation
  • CSCI-735 Foundations of Intelligent Security Systems
  • CSCI-736 Neural Networks and Machine Learning
  • CSCI-762 Advanced Cryptography
  • CSEC-743 Computer Viruses and Malicious Software
  • CSEC-744 Network Security
  • EEEE-602 Random Signals and Noise
  • EEEE-693 Digital Data Communication
  • EEEE-797 Wireless Communication
  • NSSA-612 Network Modeling and Analysis
  • NSSA-711 Advanced Routing Protocols
  • NSSA-715 Network Design and Performance

Signal processing, control, and embedded systems

  • CMPE-663 Real-time and Embedded Systems
  • CMPE-664 Modeling of Real-time Systems
  • CMPE-665 Performance Engineering of Real-Time and Embedded Systems
  • EEEE-602 Random Signals and Noise
  • EEEE-610 Analog Electronics
  • EEEE-661 Modern Control Theory
  • EEEE-733 Robust Control
  • EEEE-765 Optimal Control
  • EEEE-768 Adaptive Signal Processing
  • EEEE-793 Error Detection and Error Correction
  • EEEE-794 Information Theory
  • MATH-781
  • Wavelets and Applications

Additional graduate-level math courses

  • ISEE-601 Systems Modeling and Optimization
  • ISEE-701 Linear Programming
  • ISEE-702 Integer and Nonlinear Programming
  • MATH-603 Optimization Theory
  • MATH-605 Stochastic Processes
  • MATH-611
  • Numerical Analysis
  • MATH-651
  • Combinatorics and Graph Theory I

Admission Requirements

To be considered for admission to the MS program in computer engineering, candidates must fulfill the following requirements:

  • Complete a graduate application.
  • Hold a baccalaureate degree (or equivalent) from an accredited university or college in computer engineering or a related field.
  • Submit official transcripts (in English) from all previously completed undergraduate and graduate course work.
  • Have a minimum cumulative GPA of 3.0 (or equivalent).
  • Submit scores from the GRE.
  • Submit two letters of recommendation from individuals well qualified to judge the candidate’s ability for graduate study.
  • International applicants whose native language is not English must submit scores from the TOEFL, IELTS, or PTE. A minimum TOEFL score of 79 (internet-based) is required. A minimum IELTS score of 6.5 is required. The English language test score requirement is waived for native speakers of English or for those submitting transcripts from degrees earned at American institutions.
Program taught in:
  • English
Rochester Institute of Technology (RIT)

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Last updated July 8, 2019
This course is Campus based
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Duration
2 years
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47,522 USD
Annual tuition (12-18 credit hours). Additional fees may apply. Scholarships and aids are available.
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