Computer Engineering MS
Major: Computer Engineering
Degree Awarded: Master of Science (MS)
Calendar Type: Quarter
Minimum Required Credits: 45.0
Co-op Option: Available for full-time, on-campus master's-level students
Classification of Instructional Programs (CIP) code: 14.0901
Standard Occupational Classification (SOC) code: 15-1132; 15-1133; 15-1143; 17-2031
About the Program
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 9.0 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 9.0 credits).
Full-time students within the Master of Science in Computer Engineering are eligible to take part in the Graduate Coop Program, which combines classroom coursework with a six-month, full-time work experience.
Additional Information
For more information, visit the MS in Computer Engineering program and Department of Electrical and Computer Engineering website.
Admission Requirements
Applicants should have an undergraduate degree equivalent to a US 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 US institution must take the Test of English as a Foreign Language (TOEFL).
Degree Requirements
The Master of Science in Computer Engineering curriculum encompasses 45.0 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.
The remaining courses needed to reach the minimum credit hour requirement for the degree program are considered elective courses. Elective courses can be chosen from among the graduate course offerings of the Department of Electrical and Computer Engineering; other departments within the College of Engineering; the School of Biomedical Science, Engineering and Health Systems; the Department of Mathematics; the Department of Physics; the Department of Chemistry, the Department of Biology, and the Department of Computer Science. In order to have courses outside of these departments and schools count towards degree completion, they must be approved by the departmental graduate advisors prior to registration for said courses.
Please note that ECEC 500 Fundamentals of Computer Hardware and ECEC 600 Fundamentals of Computer Networks do not count toward the credit requirements to complete the MS in Electrical Engineering degree program.
Computer Engineering (ECEC) 500+ level Courses | 21.0 | |
General Electrical and Computer Engineering (ECE) Courses * | 9.0 | |
Mathematical Foundations Requirement | ||
6.0 credits from one of the following courses must be included within (not in addition to) the 45.0 total required MS credits: | ||
Theory of Computation | ||
Applied Symbolic Computation | ||
Introduction to Computer Vision | ||
Machine Learning | ||
Approximation Algorithms | ||
Computational Geometry | ||
Analytical Methods in Systems | ||
Fundamentals of Systems I | ||
Fundamentals of Systems II | ||
Fundamentals of Systems III | ||
Probability & Random Variables | ||
Random Process & Spectral Analysis | ||
Detection & Estimation Theory | ||
Fundamentals of Deterministic Digital Signal Processing | ||
Fundamentals of Computer Vision | ||
Optimization Methods for Engineering Design | ||
Information Theory and Coding | ||
Advanced Mathematical Program | ||
Applied Math Programming | ||
MATH 500-900 level | ||
Elective Courses ** | 15.0 | |
Optional Co-op Experience *** | 0-1 | |
Career Management and Professional Development for Master's Degree Students | ||
Total Credits | 45.0-46.0 |
- *
500+ level courses from subject codes ECEC, ECEE, ECEP, ECES, ECET, ECE.
- **
500+ level courses in the following areas: ECEC, ECEE, ECEP, ECES, ECET, ECE, AE, CHE, CIVE, CMGT, EGMT, ENGR, ENVE, ET, MATE, MEM, PROJ, SYSE, BMES, MATH, PHYS, CHEM, BIO, OPR, CS.
- ***
Co-op is an option for this degree for full-time on-campus students. To prepare for the 6-month co-op experience, students will complete: COOP 500. The total credits required for this degree with the co-op experience is 46.0
Students not participating in the co-op experience will need 45.0 credits to graduate.
Options for Degree Fulfillment
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.
Students may choose to participate in the Graduate Co-Op Program working on curriculum related projects. Graduate Co-op enables graduate students to alternate class terms with a six-month period of hands-on experience, gaining access to employers in their chosen industries. Whether co-op takes students throughout the United States or abroad, they are expanding their professional networks, enhancing their resumes, and bring that experience back to the classroom and their peers.
For more information on curricular requirements, visit the Department of Electrical and Computer Engineering’s website.
Sample Plan of Study
Full Time, No CO-OP
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
ECEC Courses | 6.0 | ECEC Courses | 6.0 | ECEC Course | 3.0 | Vacation | |
Elective | 3.0 | Elective | 3.0 | Electives | 6.0 | ||
9 | 9 | 9 | 0 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | ||||
ECEC Course | 3.0 | ECEC Course | 3.0 | ||||
General ECE Course | 3.0 | General ECE Courses | 6.0 | ||||
Elective | 3.0 | ||||||
9 | 9 | ||||||
Total Credits 45 |
Full Time With CO-OP
First Year | |||||||
---|---|---|---|---|---|---|---|
Fall | Credits | Winter | Credits | Spring | Credits | Summer | Credits |
COOP 500 | 1.0 | ECEC Courses | 6.0 | ECEC Course | 3.0 | ECEC Course | 3.0 |
ECEC Courses | 6.0 | Elective | 3.0 | Electives | 6.0 | General ECE Course | 3.0 |
Elective | 3.0 | Elective | 3.0 | ||||
10 | 9 | 9 | 9 | ||||
Second Year | |||||||
Fall | Credits | Winter | Credits | Spring | Credits | ||
COOP EXPERIENCE | COOP EXPERIENCE | ECEC Course | 3.0 | ||||
General ECE Courses | 6.0 | ||||||
0 | 0 | 9 | |||||
Total Credits 46 |
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
The Adaptive Signal Processing and Information Theory Research Group conducts research in the area of signal processing and information theory. Our main interests are belief/expectation propagation, turbo decoding and composite adaptive system theory. We are currently doing projects on the following topics:
- Delay mitigating codes for network coded systems
- Distributed estimation in sensor networks via expectation propagation
- Turbo speaker identification
- Performance and convergence of expectation propagation
- Investigating bounds for SINR performance of autocorrelation based channel shorteners
Applied Networking Research Lab
Applied Networking Research Lab (ANRL) projects focus on modeling and simulation as well as experimentation in wired, wireless and sensor networks. ANRL is the home of MuTANT, a Multi-Protocol Label Switched Traffic Engineering and Analysis Testbed composed of 10 high-end Cisco routers and several PC-routers, also used to study other protocols in data networks as well as automated network configuration and management. The lab also houses a sensor network testbed.
Bioimage Laboratory
Uses computer gaming hardware for enhanced and affordable 3-D visualization, along with techniques from information theory and machine learning to combine the exquisite capabilities of the human visual system with computational sensing techniques for analyzing vast quantities of image sequence data.
Data Fusion Laboratory
The Data Fusion Laboratory investigates problems in multisensory detection and estimation, with applications in robotics, digital communications, radar, and target tracking. Among the projects in progress: computationally efficient parallel distributed detection architectures, data fusion for robot navigation, modulation recognition and RF scene analysis in time-varying environments, pattern recognition in biological data sequences and large arrays, and hardware realizations of data fusion architectures for target detection and target tracking.
Drexel Network Modeling Laboratory
The Drexel Network Modeling Laboratory investigates problems in the mathematical modeling of communication networks, with specific focus on wireless ad hoc networks, wireless sensor networks, and supporting guaranteed delivery service models on best effort and multipath routed networks. Typical methodologies employed in our research include mathematical modeling, computer simulation, and performance optimization, often with the end goal of obtaining meaningful insights into network design principles and fundamental performance tradeoffs.
Drexel University Nuclear Engineering Education Laboratory
The field of nuclear engineering encompasses a wide spectrum of occupations, including nuclear reactor design, medical imaging, homeland security, and oil exploration.The Drexel University Nuclear Engineering Education Laboratory (DUNEEL) provides fundamental hands on understanding for power plant design and radiation detection and analysis.Software based study for power plant design, as well as physical laboratory equipment for radiation detection, strengthen the underlying concepts used in nuclear engineering such that the student will comprehend and appreciate the basic concepts and terminology used in various nuclear engineering professions. Additionally, students use the laboratory to develop methods for delivering remote, live time radiation detection and analysis. The goal of DUNEEL is to prepare students for potential employment in the nuclear engineering arena.
Drexel VLSI Laboratory
The Drexel VLSI Laboratory investigates problems in the design, analysis, optimization and manufacturing of high performance (low power, high throughput) integrated circuits in contemporary CMOS and emerging technologies. Suited with industrial design tools for integrated circuits, simulation tools and measurement beds, the VLSI group is involved with digital and mixed-signal circuit design to verify the functionality of the discovered novel circuit and physical design principles. The Drexel VLSI laboratory develops design methodologies and automation tools in these areas, particularly in novel clocking techniques, featuring resonant clocking, and interconnects, featuring wireless interconnects.
Drexel Wireless Systems Laboratory
The Drexel Wireless Systems Laboratory (DWSL) contains an extensive suite of equipment for constructing, debugging, and testing prototype wireless communications systems. Major equipment within DWSL includes:
- software defined radio network testbeds for rapidly prototyping new communications and network systems,
- electromagnetic anechoic chamber and reverberation chambers for testing new wireless technologies,
- experimental cell tower for field testing new wireless technologies.
The lab is also equipped with network analyzers, high speed signal generators, oscilloscopes, and spectrum analyzers as well as several Zigbee development platforms for rapidly prototyping sensor networks. The lab offers laboratory coursework in wireless network security, collaborative intelligent radio networks, and fundamental analog and digital communication systems.
Ecological and Evolutionary Signal-processing and Informatics Laboratory
The Ecological and Evolutionary Signal-processing and Informatics Laboratory (EESI) seeks to solve problems in high-throughput genomics and engineer better solutions for biochemical applications. The lab's primary thrust is to enhance the use of high-throughput DNA sequencing technologies with pattern recognition and signal processing techniques. Applications include assessing the organism content of an environmental sample, recognizing/classifying potential and functional genes, inferring environmental factors and inter-species relationships, and inferring microbial evolutionary relationships from short-read DNA/RNA fragments. The lab also investigates higher-level biological systems such as modeling and controlling chemotaxis, the movement of cells.
Electric Power Engineering Center
This newly established facility makes possible state-of-the-art research in a wide variety of areas, ranging from detailed theoretical model study to experimental investigation in its high voltage laboratories. The mission is to advance and apply scientific and engineering knowledge associated with the generation, transmission, distribution, use, and conservation of electric power. In pursuing these goals, this center works with electric utilities, state and federal agencies, private industries, nonprofit organizations and other universities on a wide spectrum of projects. Research efforts, both theoretical and experimental, focus on the solution of those problems currently faced by the electric power industry. Advanced concepts for electric power generation are also under investigation to ensure that electric power needs will be met at the present and in the future.
Electronic Design Automation Facility
Industrial-grade electronic design automation software suite and intergrated design environment for digital, analog and mixed-signal systems development. Field Programmable Gate Array (FPGA) development hardware. Most up-to-date FPGA/embedded system development hardware kits. Printed circuit board production facility. Also see Drexel VLSI Laboratory.
Microwave-Photonics Device Laboratories
The laboratory is equipped with test and measurement equipment for high-speed analog and digital electronics and fiber optic systems. The test equipment includes network analyzers from Agilent (100kHz- 1.3 GHz and 45 Mhz-40 GHz), and Anritsu (45 MHz-6 GHz); spectrum analyzers from Tektronix, HP, and Agilent with measurement capability of DC to 40 GHz and up to 90 GHz using external mixers; signal generators and communication channel modulators from HP, Rhode-Schwartz, Systron Donner, and Agilent; microwave power meter and sensor heads, assortment of passive and active microwave components up to 40 GHz ; data pattern generator and BER tester up to 3Gb/s; optical spectrum analyzer from Anritsu and power meters from HP; single and multimode fiber optic based optical transmitter and receiver boards covering ITU channels at data rates up to 10Gb/s; passive optical components such as isolator, filter, couplers, optical connectors and fusion splicer; LPKF milling machine for fabrication of printed circuit boards; wire-bonding and Cascade probe stations; Intercontinental test fixtures for testing of MMIC circuits and solid-state transistors; state-of-the-art microwave and electromagnetic CAD packages such as Agilent ADS, ANSYS HFSS, and COMSOL multi-physics module.
Multimedia & Information Security Lab [MISL]
The Multimedia and Information Security Lab (MISL) develops algorithms to detect fake images and videos, along with algorithms to determine the true source an image or video. This research is particularly important because widely available editing software enables multimedia forgers to create perceptually realistic forgeries. Our goal at MISL, is to conduct research that provides information verification and security in scenarios when an information source cannot be trusted.
The research conducted at MISL is part of a new area, known as multimedia forensics, which lies at the intersection of many areas in machine learning and artificial intelligence, signal processing, image and video processing, game theory, etc. Our algorithms work by identifying or learning visually imperceptible traces left in images and videos by processing operations. We use these traces to detect editing or forgery as well as to link an image or video back to the camera that captured it. We also perform research on anti-forensic operations designed to fool forensic techniques. By studying anti-forensics, researchers can identify and address weaknesses in existing forensic techniques as well as develop techniques capable of identifying the use of anti-forensics.
Music and Entertainment Technology Laboratory
The Music and Entertainment Technology Laboratory (MET-lab) is devoted to research in digital media technologies that will shape the future of entertainment, especially in the areas of sound and music. We employ digital signal processing and machine learning to pursue novel applications in music information retrieval, music production and processing technology, and new music interfaces. The MET-lab is also heavily involved in outreach programs for K-12 students and hosts the Summer Music Technology program, a one-week learning experience for high school students. Lab facilities include a sound isolation booth for audio and music recording, a digital audio workstation running ProTools, two large multi-touch display interfaces of our own design, and a small computing cluster for distributed processing.
NanoPhotonics+ Lab
Our research is primarily in the area of nanophotonics with a focus on the nanoscale interaction of light with matter. Interests include: liquid crystal/polymer composites for gratings, lenses and HOEs; liquid crystal interactions with surfaces and in confined nanospaces; alternative energy generation through novel photon interactions; ink-jet printed conducting materials for RF and photonic applications; and the creation and development of smart textiles technologies including soft interconnects, sensors, and wireless implementations.
Opto-Electro-Mechanical Laboratory
This lab concentrates on the system integration on optics, electronics, and mechanical components and systems, for applications in imaging, communication, and biomedical research. Research areas include: Programmable Imaging with Optical Micro-electrical-mechanical systems (MEMS), in which microscopic mirrors are used to image light into a single photodetector; Pre-Cancerous Detection using White Light Spectroscopy, which performs a cellular size analysis of nuclei in tissue; Free-space Optical Communication using Space Time Coding, which consists of diffused light for computer-to-computer communications, and also tiny lasers and detectors for chip-to-chip communication; Magnetic Particle Locomotion, which showed that particles could swim in a uniform field; and Transparent Antennas using Polymer, which enables antennas to be printed through an ink-jet printer.
Plasma and Magnetics Laboratory
Research is focused on applications of electrical and magnetic technologies to biology and medicine. This includes the subjects of non-thermal atmospheric pressure plasma for medicine, magnetic manipulation of particles for drug delivery and bio-separation, development of miniature NMR sensors for cellular imaging and carbon nanotube cellular probes.
Power Electronics Research Laboratory
The Power Electronics Research Laboratory (PERL) is involved in circuit and design simulation, device modeling and simulation, and experimental testing and fabrication of power electronic circuits. The research and development activities include electrical terminations, power quality, solar photovoltaic systems, GTO modeling, protection and relay coordination, and solid-state circuit breakers. The analysis tools include EMPT, SPICE, and others, which have been modified to incorporate models of such controllable solid-state switches as SCRs, GTOs, and MOSFETs. These programs have a wide variety and range of modeling capabilities used to model electromagnetics and electromechanical transients ranging from microseconds to seconds in duration. The PERL is a fully equipped laboratory with 42 kVA AC and 70 kVA DC power sources and data acquisition systems, which have the ability to display and store data for detailed analysis. Some of the equipment available is a distribution and HV transformer and three phase rectifiers for power sources and digital oscilloscopes for data measuring and experimental analysis. Some of the recent studies performed by the PERL include static VAR compensators, power quality of motor controllers, solid-state circuit breakers, and power device modeling which have been supported by PECO, GE, Gould, and EPRI.
Program Level Outcomes
Upon completion of the program, graduates will be prepared to:
- Apply knowledge of mathematics, science, and engineering
- Design and conduct experiments, as well as to analyze and interpret data
- Design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
- Function on multidisciplinary teams
- Identify, formulate, and solve engineering problems
- Understand professional and ethical responsibility
- Communicate effectively
- Understand the impact of engineering solutions in a global, economic, environmental, and societal context
- Recognize the need for, and an ability to engage in life-long learning
- Attain knowledge of contemporary issues
- Use the techniques, skills, and modern engineering tools necessary for engineering practice