Computer Engineering (CMPE)

Department of Computer Science and Electrical Engineering

JOEL M. MORRIS, Graduate Program Director

PINKSTON, JOHN T. Ph.D., Massachusetts Institute of Technology; Information Assurance, Superconducting Electronics, Digital Signal Processing.

Associate Professors
PHATAK, DHANANJAY, Ph.D., University of Massachusetts, Amherst; Mobile and high-performance computer networks; computer arithmetic algorithms and their VLSI implementations; signal processing; neural networks, their applications and efficient implementations; digital and analog VLSI design; and CAD.
YOUNIS, MOHAMED, Ph.D., New Jersey Institute of Technology; Fault-tolerant computing, operating systems, real-time systems, distributed systems, embedded computer systems, compile-time analysis, engineering of complex computer systems, programming languages, systems integration, reliability modeling, analysis and formal methods in software engineering.

Assistant Professors
MOHSENIN, TINOOSH, Ph.D., University of California, Davis; High performance and energy-efficient VLSI computation that support communication, signal processing, error correction, and biomedical applications; These include algorithm and architecture enhancements, application mapping/software development on many-core architectures, VLSI design of ASICs and reconfigurable architectures, single-chip solutions targeted for low-power embedded systems through a co-design of programmable cores and application-specific processors
PATEL, CHINTAN, Ph.D., University of Maryland, Baltimore County; VLSI design and test
ROBUCCI, RYAN, Ph.D., Georgia Institute of Technology analog and mixed-signal VLSI; CMOS image sensors; programmable and reconfigurable circuits; sensor interfacing and networking; image processing; real-time, mixed-mode signal processing; biologically-inspired systems; information theory; and computer-aided design and analysis of complex mixed-signal processing systems.
SLAUGHTER, GYMAMA, Ph.D., Virginia Commonwealth University; Sensor-processor integration, bioelectronics design and theory, optimization methods for physical circuit design, biologically inspired computing (neural networks), and sensor interfacing and wireless networking and communication. Other research areas include: bioengineering, biosensors, BioMEMS, and fluidic devices

Degrees Offered

M.S. (thesis and non-thesis project), Ph.D.

Program Description

The department offers a graduate program leading to the M.S. and Ph.D. degrees in Computer Engineering. The program provides advanced instruction and research opportunities in a broad range of computer engineering areas and is focused on both the theoretical and practical aspects of the state of the art in computer engineering. The doctoral program emphasizes research as a major element of its degree requirements. Fields of specialization in computer engineering supported within the department include:

  1. VLSI design and test, including mixed-signal analog and digital design
  2. Computing system architecture, design, implementation, and testing/verification
  3. VLSI design and test, including mixed-signal (analog and digital) design
  4. Sensor technology, systems, and networks
  5. Arithmetic and DSP algorithm implementations
  6. FPGA and Multi-technologies implementations

A departmental brochure that describes the department, its graduate programs, degree requirements and the research interests of the faculty can be obtained from the graduate program specialist or can be viewed at

Research Specialties

Ongoing research in the department provides a source of project, thesis and dissertation topics for students. The following illustrates some of the current research areas: VLSI design and test, low-power design, mixed-signal design, SoC design and test, computer arithmetic algorithms and implementations, MEMs, opto-electronic circuits and networks. The department encourages interdisciplinary research and invites students to take advantage of resources in related departments, including education, geography and environmental systems, information systems, mathematics and statistics, physics, visual arts and other departments within the College of Engineering and Information Technology or at the University of Maryland, Baltimore (UMB) Medical School. In addition, opportunities exist for joint research projects with local research laboratories, companies and government agencies.

Degree Requirements

Master of Science (M.S.) Degree

Within five (5) years of admission the student must earn a minimum of 30 credit hours with the thesis option or 33 credit hours with the non-thesis (project) option. All students MUST choose either the thesis or non-thesis (with project) option: there is no course-only option. Students must satisfy the grade and course requirements for their field of specialty and option. The course and grade requirements are as follows.

Course Requirements

Three core courses required for all students:
CMSC 611: Advanced Computer Architecture
CMPE 640: Advanced VLSI Design
CMPE 650: Digital Systems Design

Two focused electives, selected from any graduate course with a CMPE designation, or ENEE 610: Digital Signal Processing.

Three or five additional electives, depending on thesis or project option, selected from any graduate course with CMPE designation, or most graduate courses with CMSC (Computer Science), ENEE (Electrical Engineering) with approval from the graduate program director. Courses in related science and mathematics areas may also be taken for credit with approval from the graduate committee.

Grade Requirements: Students must receive a "B" or higher in each of the three core courses, and achieve a 3.0 or better grade point average across the fve core plus focused elective courses.

M.S. Thesis Option

Any student may undertake a master’s thesis, supervised by a faculty member. Master’s degree candidates undertake a thesis for six credits, which shows a tangible research component. Upon completion of the thesis research, the thesis must be defended in a public presentation.

Transfer Credits

No more than six credits may be transferred from another university or from UMBC as a non-degree student. Credit transfer must be approved by the graduate program director.

Grade Requirements:

Students must receive a 'B' or higher in each of the three (3) core courses, and achieve an average grade of 'B' or better (equivalently, a grade point average (GPA) of 3.0 or better) across the three (3) core plus two (2) focused elective courses. Grades with + and - are possible for graduate courses. A minimum grade of 'B' (3.0 GPA) is required for courses taken for the degree.

Graduate Seminar:

M.S. students are encouraged to attend graduate seminar presentations within the CMSC 608 and/or ENEE 608 courses during their first year. Check the CMPE Graduate Program website for any requirement changes.

M.S. Thesis Option (30 credits)

A student may undertake the M.S. thesis option that requires a minimum of eight (8) graduate-level courses and six (6) credit hours of thesis research (CMPE 799). The thesis is supervised by a faculty member as the research advisor (or co-advisor), and must show a tangible research component. Upon completion of the thesis research, the thesis must be defended with an oral public exam/presentation and accepted with the approval of the student's thesis committee. The committee must consist of at least three (3) graduate faculty members within the department. Copies of the approved thesis must be submitted both to the CSEE Department and the Graduate School.

M.S. Non-Thesis Option (33 credits)

A student may undertake the master�s non-thesis option, which would be supervised by a faculty member as the research advisor (or co-advisor). The non-thesis (project) option in the student�s field requires a minimum of ten (10) graduate-level courses and three (3) credit hours of graduate project research (CMPE 698) resulting in a scholarly paper, which must be approved by the advisor and an additional approved reader. A copy of the approved scholarly paper must be submitted to the CSEE Department.

Doctor of Philosophy (Ph.D.) Degree

Each field of specialty sets its course requirements for doctoral students in that field. The department�s minimum requirement is eleven (11) courses (beyond the bachelor�s degree). The doctoral student must spend the equivalent of at least three (3) years of full-time residency, with at least one (1) year on the UMBC campus. The doctoral dissertation must be an original and substantive contribution to knowledge in the student�s major field. It must demonstrate the student�s ability to carry out a program of research and to report the results in accordance with standards observed in the recognized scientific journals related to that field.

Doctoral students must: (a) submit their PhD Comprehensive Portfolio and receive a pass grade (P) within four (4) semesters of entrance to the program (six (6) semesters for part-time students); (b) develop and defend a doctoral dissertation proposal and be admitted to doctoral candidacy within four (4) years of entrance to the program; and (c) complete all Ph.D. requirements for their field of specialty within four (4) years of admission to doctoral candidacy.

Comprehensive Portfolio
Each student must pass a written examination based on the material covered in the four breadth courses. The comprehensive examinations are offered twice a year and may be retaken once if failed the first time, provided the time limit (four semesters for full-time students and five semesters for part-time students) is not exceeded. Any student who fails the exam twice will be dismissed from the graduate program. See the department's graduate program Web site at for detailed policies for comprehensive exams.

Course Requirements
Students must satisfy the minimum course requirements for their field of specialty (typically eleven (11) courses totaling 33 credits) excluding the department�s graduate seminar, graduate research credits prior to Ph.D. candidacy, and doctoral dissertation research credits. Five (5) of the eleven (11) courses must be the three (3) core and two (2) focused elective courses as specified in the M.S. degree requirements. The remaining elective courses must be CMPE courses and, with prior approval from their advisor and Graduate Program Director, a limited number of graduate science and engineering courses. Check the CMPE Graduate Program website for further requirement details. Students cannot take doctoral dissertation research (CMPE 899) credits before passing the preliminary examination, but can take pre-candidacy doctoral research (CMPE 898) credits during this period.

Graduate Seminar
CMPE Ph.D. students are expected to attend the regular Computer Science (CMSC 608) or Electrical Engineering (ENEE 608) seminars. Check the CMPE Graduate Program website for updates to the seminar requirement at or

PhD Comprehensive Portfolio
The CMPE PhD Comprehensive Portfolio consists of three (3) components: (a) GPA performance on the three (3) core plus two (2) focused elective courses, (b) the Research Activity Report (RAR), and (c) two (2) faculty support letters. See the CMPE Graduate Program website or for details on the CMPE PhD Comprehensive Portfolio policy.

Preliminary Examination (Prelim)
Each student must select a dissertation advisor and a dissertation committee. Students must pass a two-part preliminary examination, which is required for PhD candidacy. In the first part, the student presents and defends the dissertation proposal to the committee. In the second part, the committee examines the student orally on their research area(s) to assess the student's ability to complete the proposed research successfully. Each full-time student must pass the preliminary examination within one-and-a-half years after passing the PhD comprehensive portfolio to remain in the Ph.D. program. Part-time students will be given two-and-a-half years to pass the preliminary examination. Check the CMPE Graduate Program website for updates to this requirement.

Ph.D. Candidacy
After passing the preliminary examination (prelim) and completing the course requirements, the Graduate Program Committee recommends to the Graduate School that the student be admitted to Ph.D. candidacy.

Dissertation Research
The student conducts and reports (dissertation) on a significant original research topic under the guidance of their dissertation advisor. The doctoral dissertation must be an original and substantive contribution to knowledge in the student's major field. It must demonstrate the student's ability to: (a) conduct a program of research and (b) report the results in accordance with standards observed in the recognized scientific journals related to that field. This research must be completed and defended within four (4) years of admission to candidacy. Students must be admitted to candidacy at least two (2) full sequential semesters before the date on which the doctoral degree is to be conferred. Doctoral candidates take at least sixteen (16) dissertation credits (CMPE 899). The Ph.D. dissertation committee must include four (4) graduate faculty members from the CSEE department and one external member.

Residency Requirements
A minimum of three (3) years of full-time graduate study or its equivalent is required. At least one (1) year of full-time study must be completed at UMBC.

Program Admission Requirements

When seeking admission to the graduate program, applicants must satisfy all entrance requirements of the Graduate School at UMBC. All original application materials must be sent directly to the Graduate School, not to graduate program. Applications are not processed until all documents and fees are received. All applicants must submit official transcripts, three letters of recommendation, statement of purpose, Graduate Record Examination (GRE General Test) scores and, for inter-national students, scores for the TOEFL. Application deadlines are specified by the Graduate School. The application review process will begin by February 15 for admission in the fall semester and by October 1 for admission in the following spring semester. Early application is recommended.

An applicant to the graduate program in computer engineering is expected to have a strong background in computer engineering, computer science and mathematics courses. This includes the calculus course series, linear algebra, differential equations, and probability and statistics in mathematics. In addition, applicants are expected to have taken courses equivalent to the following computer engineering, computer science and electrical engineering courses at UMBC:

CMPE 212: Principles of Digital Design
CMPE 306: Basic Circuit Theory
CMPE 310: Systems Design and Programming
CMPE 314: Principles of Electronic Circuits
CMPE 315: Principles of VLSI Design
CMSC 341: Data Structures
CMSC 411: Computer Architecture
CMSC 421: Principles of Operating Systems

Students may apply for admission to either the M.S. or the Ph.D. program. However, admission to the Ph.D. program is highly selective, and only students with exceptional backgrounds will be accepted. Students who plan to pursue the Ph.D. degree but who do not already have a master’s in computer science are advised to apply for admission to the M.S. program. New students will be assigned an academic advisor who can provide advice on choosing courses, degree requirements and other important matters during the first year. By the end of the first year, students are expected to have located a faculty member to serve as the research advisor for master’s or doctoral. research. Consideration for continued financial assistance depends on locating a research advisor. Admission to the M.S. and Ph.D. degree programs are separate.

Facilities and Special Resources

The CMPE program facilities include dedicated computer engineering laboratories that provide computers and test and measurement equipment. The department also provides dedicated servers that allow students to use commercial design software, and the Office of Information Technology (OIT) has more than 400 workstations for general student use and several high-end computing systems.

Financial Assistance

Financial aid is available on a competitive basis to a limited number of qualified graduate students in the form of graduate teaching assistantships (TAs), graduate research assistantships (RAs), work-study positions and hourly employment as graders. Graduate RAs are often available to students actively engaged in their master’s thesis or doctoral dissertation research and are awarded and renewed subject to availability of funds and satisfactory research progress. Students are encouraged to apply directly to nationally awarded fellowship programs.


For CMPE (also CMSC and ENEE) course descriptions, and current year special topic course listings and descriptions, see the CSEE Graduate Program(s) website or CSEE Department website The set of CMPE 691 courses address specialized computer engineering topics representing the research focus of the faculty, and are scheduled according to student and faculty interests.

CMPE 611
Advanced Computer Architecture [3]

Memory-system design, advanced pipeline structures, instruction-level parallelism, compiler-assisted optimization, multi-processor architecture, interconnection network, advances storage systems. Within each topic, the emphasis is on quantitative evaluation and fundamental issues, e.g., data and control dependence, memory bandwidth, reliability, and coherence of distributed storage. Prerequisite: CMSC 411 or consent of instructor.

CMPE 640
Custom VLSI Design [3]

This course introduces the CMOS VLSI design process and focuses on design at the circuit and physical levels. Students design, implement, fabricate and test basic logic gates and other VLSI structures such as adders and multipliers using computeraided design tools and laboratory test and measurement equipment. Basic layout and simulation techniques are covered in addition to CMOS processing technology, MOS transistor theory, performance estimation, CMOS design styles, VLSI structures and timing issues. The Verilog hardware description language is used in the laboratories.

CMPE 641
Advanced VLSI Design II [3]

This course is focused on the design, implementation, fabrication and testing of a large VLSI chip. Advanced CMOS design topics are covered including BiCMOS and dynamic logic circuits. system level design entities such as ALUs, Register Files, Functional Units, Controllers, and clock and power distribution schemes. The Verilog high-level description language and high-level synthesis tools are also covered as well as Design-For-Testability design issues. Students work in groups of four to design, implement and test a CMOS implementation of a system level design entity such as a microprocessor. Prerequisite: CMPE 640

CMPE 642
Principles of Mixed Signal Design [3]

CMPE 645
Computer Arithmetic Algorithms and Implementations [3]

Introduction to arithmetic, unconventional fixed-radix number systems, sequential algorithms for multiplication and division, binary floating point numbers, fast addition and multiplication, fast division and square root, evaluation of elementary functions (polynomial/rational function methods as well as CORDIC), logarithmic and residue number representations. Other topics are covered in articles from current literature in the area.

CMPE 646
VLSI Design Verification and Test [3]

This course covers the design verification and testing processes applied to VLSI digital integrated circuits. Design and hardware level testing and failure analysis processes are examined in detail. Hardware testing concepts covered include fault modeling, fault simulation, automatic test pattern generation (ATPG), functional test, logic and parametric testing techniques. Built-in self test, design for testability, sequential test generation issues are also examined. Commercial computer aided verification and ATPG tools are used to generate tests on existing designs. Corequisite: CMPE 640

CMPE 650
Digital Systems Design [3]

This course covers practical and theoretical aspects necessary to design high-speeddigital systems. Topics include transmission line theory, cross-talk and non-ideal transmission line effects on signal quality and timing, impact of packages, vias andconnectors on signal integrity. Other issues covered include non-ideal return paths, simultaneous switching noise, power delivery, buffer modeling and digital timing analysis. Linux device driver design and implementation will also be covered.

CMPE 670
Biomedical Microsystems [3]

This course provides graduate electrical and computer engineering students an in-depth knowledge of the growing and highly multidisciplinary field of biomedical microsystems (BioMEMS) and biosensors. This course covers current microsystems and biosensors under development. Emphasis will be placed on how they operate and under what circumstanced they can be useful. Recurring themes will be the biological instrumentation design and techniques and the detection of blood glucose, because of their importance on current medical practice. Self-learning, gaining knowledge through team interactions and laboratory projects will be emphasized in this course. Prerequisities: Graduate Standing or CMPE 306 and 310.

CMPE 684
Wireless Sensor Networks [3]

This course provides a broad coverage of challenges and latest research results related to the design and management of wireless sensor networks. Covered topics include network architectures, node discovery and localization, deployment strategies, node coverage, routing protocols, medium access arbitration, fault-tolerance, and network security.

CMPE 691
Special Topics in Computer Engineering [1-3]

A set of CMPE 691 courses, on various Computer Engineering specialized topics, are typically offered each semester.

CMPE 698
Research Project in Computer Engineering [1-3]

Individual projects on a topic in Computer Engineering. The project will result in a scholarly paper, which must be approved by the student's research advisor and read by another graduate faculty member. Required for non-thesis M.S. students. Note: May be taken for repeated credit up to a maximum of three credits. Prerequisite: Completion of the core and breath courses or consent of advisor.

CMPE 699
Independent Study in Computer Engineering [1-3]

Independent study work will consist of individualized research work with a faculty member.

CMPE 791
Advanced Topics in Computer Engineering [3]

CMPE 791 will allow the computer engineering faculty to teach advanced level [700 level] courses in their areas of expertise.

CMPE 799
Master's Thesis Research [2-9]

This course is for students in the CMPE master's program who are engaged in master's thesis research. Note: May be taken for repeated credits, but a maximum of six credit hours may be applied toward master's thesis-option requirements. Prerequisite: Open only to CMPE thesis-option students.

CMPE 898
Pre-Candidacy Doctoral Research [3-9]

Research on doctoral dissertation conducted under the direction of a faculty advisor before candidacy.

CMPE 899
Doctoral Dissertation Research [9]

This dissertation research course is for doctoral students who have passed the Ph.D. preliminary examination or will be taking the preliminary examination in the semester they are enrolled in this course. Note: May be taken for repeated credits (two semesters required), up to 16 credit hours.

CYBR 691
Special Topics in Cybersecurity [3]

Courses on specialized or emerging cybersecurity topics offered on a timely or as-needed basis.

ENMG 664
Quality Engineering and Management [3]

This course provides an overview of the basic principles and tools of quality and their applications from an engineering perspective. The primary quality schools of thought or methodologies, including Total Quality Management, Six Sigma and Lean Six Sigma, and quality approaches from key figures in the development and application of quality as a business practice, including W. Edwards Deming and Joseph M. Juran will be analyzed. Some of the key mathematical tools used in quality systems will be discussed, including Pareto charts, measurement systems analysis, design of experiments, response surface methodology, and statistical process control. Students will apply these techniques to solve engineering problems using the R software. Reading assignments, homework, exams, and the project will emphasize quality approaches, techniques, and problem solving.