Computer Engineering
About the Program
Master of Science in Computer Engineering (MSCPE): 45.0 - 48.0 quarter credits
PhD: 90.0 quarter credits
The computer engineering curriculum is designed to: (1) address the needs of students with a variety of different backgrounds; (2) ensure that graduates will have adequate knowledge and skills in at least one area of specialization; (3) meet the immediate needs of working students as well as to adequately prepare full-time students for a real-world technological environment; and (4) equip students with tools to grasp and develop new technologies and trends.
The Master of Science in Computer Engineering degree requires a minimum of 45.0 approved credits chosen in accordance with a plan of study arranged in consultation with the student's advisor and the departmental graduate advisor. Up to but not exceeding 9 research/thesis credits may be taken by students who choose to write a Master's thesis. Students who elect a non-thesis option are also encouraged to engage in research, by registering for supervised research credits (not to exceed 9 credits).
For more information, visit the Department of Electrical and Computer Engineering web site.
Admission Requirements
Applicants should preferably have an undergraduate degree equivalent to a U.S. bachelor's degree in computer engineering, computer science, or electrical engineering. Students holding degrees in other engineering and science disciplines with appropriate coursework or training will also be considered.
Appropriate coursework includes experience with all of the following: Software (advanced programming and operating systems); Computer Architecture (digital systems design, computer organization and architecture); Algorithms and Data Structures; Computer Networks. Students must have a minimum 3.0 GPA (on a 4.0 scale) for the last two years of undergraduate studies, as well as for any subsequent graduate-level work.
The GRE General Test is required of applicants to full-time MS and PhD programs. Students whose native language is not English and who do not hold a degree from a U.S. institution must take the Test of English as a Foreign Language (TOEFL).
Master of Science in Computer Engineering
The Master of Science in Computer Engineering curriculum encompasses 45.0 or 48.0 (with the Graduate Co-op option) approved credit hours, chosen in accordance with the following requirements and a plan of study arranged with the departmental graduate advisor in consultation with the student’s research advisor, if applicable. Before the end of the first quarter in the Department of Electrical and Computer Engineering, for a full-time student, or by the end of the first year for a part-time student, said plan of study must be filed and approved with the departmental graduate advisor.
A total of at least 30.0 credit hours must be taken from among the graduate course offerings of the Department of Electrical and Computer Engineering. These credits must be taken at Drexel University. No transfer credit may be used to fulfill these requirements, regardless of content equivalency.
These departmental credit hours are as follows:
- 18.0 credits of Computer Engineering Courses (ECEC)
- 6.0 credits if Electrical Engineering Courses (ECEE, ECEP, ECES, ECET)
- 6.0 credits of General Electrical and Computer Engineering Courses (ECEC, ECEE, ECEP, ECES, ECET)
Computer Engineering Course Requirements
Core Courses
The Computer Engineering core courses consist of two courses:
Sequence Courses
Besides the two core courses, students must also complete a three course Computer Engineering (ECEC) sequence. This requirement may be fulfilled by taking the remaining two courses of one of the two sequences started as part of the core course requirement or by completing an entirely separate three course sequence in Computer Engineering.
| Computer Engineering Courses (ECEC) | 18.0 | |
| Electrical Engineering Courses (ECEE, ECEP, ECES, ECET) | 6.0 | |
| General Electrical and Computer Engineering (ECEC, ECEE, ECEP, ECES, ECET) Courses | 6.0 | |
| Additional Requirements * | 15.0 | |
| Total Credits | 45.0 | |
| * | With the remaining required 15.0 credit hours, students may take graduate coursework, subject to the approval of the departmental graduate advisor, in electrical and computer engineering, mathematics, physics or other engineering disciplines. |
Although not required, students are encouraged to complete a Master’s Thesis as part of the MS studies. Those students who choose the thesis option may count up to 9.0 research/thesis credits as part of their required credit hour requirements.
Graduate Co-Op Program
Students may choose to participate in the Graduate Co-Op Program, where 6.0 credit hours can be earned for a six month co-operative education experience in industry, working on curriculum related projects. The total number of required credit hours is increased to 48 for those students who choose to pursue the Graduate Co-Op option. This change represents an increase in non-departmental required credit hours to a total of 18.0 credit hours, 6.0 of which are earned from the co-operative education experience.
Please note that (Fundamentals of Computer Hardware) and (Fundamentals of Computer Networks) do not count toward the credit requirements to complete the MS in Electrical Engineering degree program.
For more information on curricular requirements, visit the Department of Electrical and Computer Engineering’s web site.
PhD in Electrical Engineering
General Requirements
The following general requirements must be satisfied in order to complete the PhD in Electrical Engineering:
- 90.0 credit hours total
- candidacy examination
- research proposal
- dissertation defense
Students entering with a master’s degree in electrical or computer engineering or a related field will be considered a post-masters PhD student and will only be required to complete a total of 45.0 credit hours, in accordance with University policy.
Curriculum
Appropriate coursework is chosen in consultation with the student’s research advisor. A plan of study must be developed by the student to encompass the total number of required credit hours. Both the departmental graduate advisor and the student’s research advisor must approve this plan.
Candidacy Examination
The candidacy examination explores the depth of understanding of the student in his/her specialty area. The student is expected to be familiar with, and be able to use, the contemporary tools and techniques of the field and to demonstrate familiarity with the principal results and key findings.
The student, in consultation with his/her research advisor, will declare a principal technical area for the examination. The examination includes the following three parts:
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A self-study of three papers from the archival literature in the student’s stated technical area, chosen by the committee in consultation with the student.
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A written report (15 pages or less) on the papers, describing their objectives, key questions and hypotheses, methodology, main results and conclusions. Moreover, the student must show in an appendix independent work he/she has done on at least one of the papers – such as providing a full derivation of a result or showing meaningful examples, simulations or applications.
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An oral examination which takes the following format:
- A short description of the student’s principal area of interest (5 minutes, by student).
- A review of the self-study papers and report appendix (25-30 minutes, by students).
- Questions and answers on the report, the appendix and directly related background (40-100 minutes, student and committee).
In most cases, the work produced during the candidacy examination will be a principal reference for the student’s PhD dissertation; however, this is not a requirement.
Research Proposal
Each student, after having attained the status of PhD Candidate, must present a research proposal to a committee of faculty and industry members, chosen with his/her research advisor, who are knowledgeable in the specific area of research. This proposal should outline the specific intended subject of study, i.e. , it should present a problem statement, pertinent background, methods of study to be employed, expected difficulties and uncertainties and the anticipated form, substance and significance of the results.
The purpose of this presentation is to verify suitability of the dissertation topic and the candidate's approach, and to obtain the advice and guidance of oversight of mature, experienced investigators. It is not to be construed as an examination, though approval by the committee is required before extensive work is undertaken. The thesis proposal presentation must be open to all; announcements regarding the proposal presentation must be made in advance.
The thesis advisory committee will have the sole responsibility of making any recommendations regarding the research proposal. It is strongly recommended that the proposal presentation be given as soon as possible after the successful completion of the candidacy examination. The student must be a PhD candidate for at least one year before he/she can defend his/her doctoral thesis.
Dissertation Defense
Dissertation Defense procedures are described in the Office of Graduate Studies policies regarding Doctor of Philosophy Program Requirements. The student must be a PhD candidate for at least one year before he/she can defend his/her doctoral thesis.
Dual Degree
The ECE Department offers outstanding students the opportunity to receive two diplomas (BS and MS) at the same time. The program requires five (5) years to complete. Participants, who are chosen from the best undergraduates students, work with a faculty member on a research project and follow a study plan that includes selected graduate classes. This program prepares individuals for careers in research and development; many of its past graduates continued their studies toward a PhD.
For more information on eligibility, academic requirements, and tuition policy visit the Engineering Combined BS/MS page.
Facilities
Drexel University and the Electrical and Computer Engineering Department are nationally recognized for a strong history of developing innovative research. Research programs in the ECE Department prepare students for careers in research and development, and aim to endow graduates with the ability to identify, analyze, and address new technical and scientific challenges. The ECE Department is well equipped with state-of-the-art facilities in each of the following ECE Research laboratories:
Research Laboratories at the ECE Department
- Adaptive Signal Processing and Information Theory Research Group
- Applied Communications and Information Networking Center
- Applied Networking Research Laboratory
- Biochemical Signal Processing Laboratory
- Cleanroom Microfabrication Facility
- Data Fusion Laboratory
- Drexel Network Modeling Laboratory
- Drexel Wireless Systems Laboratory
- Electric Power Engineering Center
- Electronic Design Automation (EDA) Facility
- Microwave Photonics Center
- Microwave-Photonics Device Laboratories
- Music and Entertainment Technology Laboratory
- NanoPhotonics Laboratory
- Opto-Electro-Mechanical Laboratory
- Plasma and Magnetics Laboratory
- Power Electronics Research Laboratory
- Supervisory Control Laboratory
- Testbed for Power/Performance Management of Enterprise Computing Systems
Courses
ECEC 500 Fundamentals Of Computer Hardware 3.0 Credits
Covers computer organization and architecture; elements of computer hardware, processors, control units, and memories; hardware for basic mathematical operations; tradeoffs between speed and complexity; examples of embedded systems; microcontrollers; systems modeling.
Repeat Status: Not repeatable for credit
ECEC 501 Computational Principles of Representation and Reasoning 3.0 Credits
This course presents fundamentals of discrete mathematics as applied within the computer engineering and manufacturing environment. Students are given the theoretical background in representation and reasoning for a broad variety of engineering problems solving situations. Entity-relational techniques of representation are demonstrated to evolve into the object-oriented approach. Various search techniques are applied in the cases of representing engineering systems by using theory of automata techniques.
Repeat Status: Not repeatable for credit
ECEC 502 Principles of Data Analysis 3.0 Credits
This course presents theoretical methods and techniques of model development applicable within the computer engineering design and manufacturing environment. Students are given the theoretical background in data analysis (including "data mining"). Emphasis is on hybrid systems and discrete events systems. Various methods of recognizing regularities in data will be presented. Elements of the theory of clustering and classification will be dealt with for the paradigm of software and hardware problems.
Repeat Status: Not repeatable for credit
ECEC 503 Principles of Decision Making 3.0 Credits
This course presents theoretical fundamentals and engineering techniques of decision making and problem solving applicable within the computer engineering design and manufacturing environment. Students are given the theoretical background in optimization methods for a broad variety of situation. Elements of the theory of planning and on-line control of systems are presented within the scope of software and hardware computer design and control.
Repeat Status: Not repeatable for credit
ECEC 511 Combinational Circuit Design 3.0 Credits
Representing arithmetic. Logic and syntax data for machine processing. Switching algebra: Boolean and multiple values. Identification and classification of functions. Realizing completely specified and incompletely specified Boolean functions. Issues in designing large communication/control Boolean functions. Fault and testing of Boolean function.
Repeat Status: Not repeatable for credit
ECEC 512 Sequential Circuit Design 3.0 Credits
Finite automata and their realization by sequential machines, capabilities, transformation, and minimization of finite automata, linear finite automata. Clocked pulsed and level mode sequential circuits. Malfunctions in sequential circuits: hazards, races, lockouts, metastability. Issues of state assignment. Evolution of memory elements design: ROM vs. RAM vs. associative memory.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 511 [Min Grade: C]
ECEC 513 Design for Testability 3.0 Credits
Economics vs. Complexity vs. Strategy of Testing; Fault Models; Test Generation; Testability Analysis & Designing Testable Circuits; Testing Microprocessors, Memories and Computer Components; Test Data Compression; Fault Tolerant Hardware; Reliably vs. Availability; Redundancy and Error Correcting Codes.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 511 [Min Grade: C] and ECEC 512 [Min Grade: C]
ECEC 520 Dependable Computing 3.0 Credits
Fundamental design issues involved in building reliable, safety-critical, and highly available systems. Topics include testing and fault-tolerant design of VLSI circuits, hardware and software fault tolerance, information redundancy, and fault-tolerant distributed systems.
Repeat Status: Not repeatable for credit
ECEC 541 Robotic Computer Interface Controls I 3.0 Credits
Covers sensors, actuators, mechanical components of robots, kinematics, inverse kinematics, dynamics, and equations of motion.
Repeat Status: Not repeatable for credit
ECEC 542 Robotic Computer Interface Controls II 3.0 Credits
Covers the robot control problem, including PD, PID, position, force and hybrid controllers, resolved rate and acceleration control, and multiprocessor architecture.
Repeat Status: Not repeatable for credit
Prerequisites: ECES 641 [Min Grade: C] and ECES 643 [Min Grade: C] and ECEC 541 [Min Grade: C]
ECEC 543 Robotic Computer Interface Controls III 3.0 Credits
Covers non-linear control techniques, FLDT, and advanced topics.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 542 [Min Grade: C]
ECEC 600 Fundamentals of Computer Networks 3.0 Credits
Fundamentals design principles of ATM, Internet and local area networks; protocol layers and the Internet Architecture; medium access protocols; application protocols and TCP/IP utilities; basic principles and virtual circuit switching; naming and addressing; flow and congestion control protocols; routing algorithms; Quality-of-Service in computer networks; security issues in networks.
Repeat Status: Not repeatable for credit
ECEC 621 High Performance Computer Architecture 3.0 Credits
Maximizing single processor performance. Concepts and techniques for design of computer systems. Processor design, instruction set architecture design and implementation, memory hierarchy, pipelines processors, bus bandwidth, processor/memory interconnections, cache memory, virtual memory, advanced I/O systems, performance evaluation.
Repeat Status: Not repeatable for credit
ECEC 622 Parallel Computer Architecture 3.0 Credits
Advanced techniques of computer design. Use of parallel processing to achieve high performance levels. Fine and coarse grained parallelism. Multiple CPU parallelism, through multiprocessors, array and vector processors. Dataflow architectures and special purpose processors. Design implications of memory latency and bandwidth limitations. Speedup problems.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 621 [Min Grade: C]
ECEC 623 Advanced Parallel Computer Architecture 3.0 Credits
Modern research topics and methods in parallel computer architectures. Parallel algorithms, interconnection networks, SIMD/MIMD machines, processor synchronization, data coherence, dataflow machines, special purpose processors. Select topics in parallel computing.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 622 [Min Grade: C]
ECEC 631 Principles of Computer Networking 3.0 Credits
Principles of circuit switching, packet switching and virtual circuits; protocol layering; application layer protocols for e-mail and web applications; naming and addressing; flow control and congestion avoidance with TCP; Internet Protocol (IP); routing algorithms; router architectures; multicast protocols; local area network technologies and protocols; issues in multimedia transmissions; scheduling and policing; Quality-of-Service and emerging Internet service architectures; principles of cryptography.
Repeat Status: Not repeatable for credit
ECEC 632 Performance Analysis of Computer Networks 3.0 Credits
Covers probability theory and its applications to networks, random variable and random processes; Markov chains, multi-dimensional Markov chains; M/M/1, M/M/m, M/M/m/m, M/G/1 and G/G/1 queueing systems and their applications in computer networks; analysis of networks of queues: Kleinrock Independence Approximation; Time-reversibility and Burke's theorem; Jackson's theorem; the phenomenon of long-range dependence and its implications in network design and traffic engineering.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 631 [Min Grade: C]
ECEC 633 Advanced Topics in Computer Networking 3.0 Credits
perspectives in the areas of switch/router architectures, scheduling for best-effort and guaranteed services, QoS mechanisms and architectures, web protocols and applications, network interface design, optical networking, and network economics. The course also includes a research project in computer networking involving literature survey, critical analysis, and finally, an original and novel research contribution.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 631 [Min Grade: C] and ECEC 632 [Min Grade: C]
ECEC 654 Knowledge Engineering I 3.0 Credits
Covers conceptual modeling, including an overview of knowledge representation. Includes semantic networks, reduced semantic networks, logic of incomplete knowledge bases, extensional semantic networks, and applications of conceptual models.
Repeat Status: Not repeatable for credit
ECEC 655 Knowledge Engineering II 3.0 Credits
Covers expert systems, including language and tools of knowledge engineering. Includes reasoning about reasoning, design and evaluation, heuristics in expert systems, expert systems for decision support, and expert systems in conceptual design.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 654 [Min Grade: C]
ECEC 656 Knowledge Engineering III 3.0 Credits
Covers information-intensive systems, including information representation in autonomous systems. Includes clauses and their validation; clustering in linguistic structures; linguistic and pictorial knowledge bases; discovery in mathematics, including am; and methods of new knowledge generation.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 655 [Min Grade: C]
ECEC 661 VLSI Design 3.0 Credits
Covers CMOS design styles, techniques, and performance; VLSI computer hardware, arithmetic units, and signal processing systems; and cat tools for layout design and simulation.
Repeat Status: Not repeatable for credit
ECEC 662 VLSI Array Processors I 3.0 Credits
Covers VLSI testing, including design for testability and parallel computer architectures; signal and image processing algorithms and mapping algorithms onto array structures; and systolic array processors.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 661 [Min Grade: C]
ECEC 663 VLSI Array Processors II 3.0 Credits
Covers wavefront array processors; matching hardware to arrays; hardware design, systems design, and fault-tolerant design; and implementations and VLSI design projects.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 662 [Min Grade: C]
ECEC 671 Electronic Design Automation for VLSI Circuits I 3.0 Credits
This course focuses on the electronic design automation problems in the design process of VLSI integrated circuits. In this first quarter of the course, algorithms, techniques and heuristics structuring the foundations of contemporary VLSI CAD tools are presented. Boolean algebra, graph theory, logic minimization and satisfiability topics are presented.
Repeat Status: Not repeatable for credit
ECEC 672 Electronic Design Automation for VLSI Circuits II 3.0 Credits
This course focuses on the electronic design automation problems in the design process of VLSI integrated circuits. In this second quarter of the course, physical VLSI design steps of technology mapping, floor planning, placement, routing and timing and presented individual and team-based small-to-medium scale programming projects are assigned.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 671 [Min Grade: C]
ECEC 673 Deep Sub-Micron Integrated Circuit Design 3.0 Credits
This course focuses on the design challenges of digital VLSI integrated circuits in deep sub-micron manufacturing technologies. Automation challenges and high-performance circuit design techniques such as low-power and variation-aware design are presented. The course material is delivered in a lecture format structured on recent presentations, articles, and tutorials.
Repeat Status: Not repeatable for credit
Prerequisites: ECEC 671 [Min Grade: C]
ECEC 690 Special Topics Computer Engineering 9.0 Credits
Covers special topics of interest to students and faculty.
Repeat Status: Can be repeated multiple times for credit
ECEC 697 Research in Computer Engineering 9.0 Credits
Research in computer engineering.
Repeat Status: Can be repeated multiple times for credit
ECEC 699 Supervised Study in Computer Engineering 9.0 Credits
Supervised study in computer engineering.
Repeat Status: Can be repeated multiple times for credit
ECEC 890 Advanced Special Topics in Computer Engineering 1.0-9.0 Credit
Covers advanced special topics of interest to students and faculty.
Repeat Status: Can be repeated multiple times for credit
ECEC 891 Advanced Topics in Computer Engineering 0.5-9.0 Credits
Advanced topics in computer engineering.
Repeat Status: Can be repeated multiple times for credit
ECEC 898 Master's Thesis in Computer Engineering 9.0 Credits
Master's thesis in computer engineering.
Repeat Status: Can be repeated multiple times for credit
ECEC 997 Dissertation Research in Computer Engineering 1.0-12.0 Credit
Graded Ph.D. dissertation in computer engineering.
Repeat Status: Can be repeated multiple times for credit
ECEC 998 PhD Dissertation in Computer Engineering 1.0-12.0 Credit
Ph.D. dissertation in computer engineering.
Repeat Status: Can be repeated multiple times for credit
