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School of Engineering Science
9801 Applied Science Building, 778.782.4371, 778.782.4951 Fax, www.ensc.sfu.ca
Director
- M. Saif BSEE, MSEE, PhD (Cleveland), PEng
Graduate Program Chair
- K.K. Gupta BTech (IIT, Dehli), MEng, PhD (McG), PEng
Faculty and Areas of Research
For a complete list of faculty, see “School of Engineering Science” on page 82.
- S. Arzanpour – vibration control, nonlinear systems, smart materials and structures, vibration based energy harvesting, Haptic devices and interfaces, flexible fixtures, robotic assembly
- M. Bahrami – heat transfer and fluid flow in microchannels, transport phenomena in new materials, porous media and metalfoams, microelectronics cooling, energy management thermal contact resistance
- B. Bahreyni – micro-electomechanical systems (MEMS), micro-sensors, resonant devices, microfabrication, interface circuit design for MEMS
- I.V. Bajic – signal processing and applications in image and video coding, multimedia communications, and computational biology
- M.F. Beg – computational anatomy: algorithms for segmentation, registration and shape analysis from medical images. Applications to structure and function in the brain, heart and peripheral muscles and nerves
- J.S. Bird – signal processing, sonar, underwater acoustics, underwater acoustic transducers, bottom mapping and target detection applications
- T.W. Calvert* – information processing in man and machines, biomedical applications, graphics
- J.K. Cavers* – wireless communication: modulation, single- and multi-user detection, adaptive antenna arrays, iterative processing, sensor networks
- G.H. Chapman – microelectronics, EMS, IC defect avoidance designs, imaging sensors, microsensors, biomedical optics, microfabrication, laser applications
- V. Cuperman* – signal processing, speech coding and recognition, multimedia information compression, digital communications, digital signal processing structures and hardware
- J.C. Dill* – information visualization, visual analytics, human-computer interaction
- D.A. George* – adaptive signal processing for communications and remote sensing systems
- M.F. Golnaraghi – intelligent sensor systems: developing sensors for various industrial and biomedical applications for response and motion characterization and control; smart actuation systems: applications of magnetorheological fluids and elastomers, mangetostrictive material, piezoelectric ceramics, shaped memory allorys; nonlinear vibration analysis and control
- B.L. Gray – microfluidics, interconnect and microassembly, biomedical microdevices and instruments, high-aspect-ratio microfabrication techniques
- W.A. Gruver* – distributed intelligence, multi-agent and holonic systems, wireless peer-to-peer networks. Applications to manufacturing, robotics, and automation systems
- K.K. Gupta – algorithmic robotics, robot motion and path planning algorithms, obstacle avoidance, sensor-based motion planning, range sensing for robotics
- R.H.S. Hardy – wireless communication networks, protocols and performance, access control and management of multimedia networks, wide area wireless and ad hoc networks
- P.K.M. Ho – wireless communications, with emphasis on space-time coding and processing modulation, coding, detection, and channel estimation
- R.F. Hobson – system-on-chip, low power embedded memory, embedded processor design
- J.D. Jones – finite element analysis, heat transfer, thermodynamics and their application to micromachining; history and philosophy of engineering
- B. Kaminska – wireless sensor networks, micro-medical devices, biosensors, wearable electronics; physiological, behavioral, and environmental monitoring; microelectronic design, test, and fault-tolerance; design and test automation algorithm
- E. Kjeang – micro and nanofluidic energy conversion devices, innovative fuel cell architectures and materials, modelling and simulation of transport phenomena in porous media
- D.C. Lee – computer and communications networks, wireless communications, multimedia transport
- A.M. Leung – microelectronics, integrated circuit technology, integrated micromachined physical sensors, optical lithography
- J. Liang – image/video compression, image/video processing, filter bank, wavelets, multimedia communications, wireless communications
- C. Menon – control and design of mechatronic systems such as medical robotics, novel sensors/actuators, flexure/vibration control
- M. Moallem – mechatronics, real-time systems, embedded computer control systems, smart sensors and actuators, robotics, control applications, linear and nonlinear systems
- S. Muhaidat – multi-input multi-output (MIMO) communications, space-time coding, co-operative communications, performance analysis over fading channels, channel estimation and equalization, modulation and detection techniques, orthogonal frequency division multiplexing (OFDM)
- M. Parameswaran – silicon and plastic MEMS technology development; microelectronic sensors and actuators; microelectronic device and processing simulation; biomedical diagnostic chips and systems
- E.J. Park – biomechatronics and mechatronics, biomedical technologies, wearable technologies, biorobotics, smart sensors and actuators, control applications
- S. Payandeh – robotics, distributed robotics, mechanics-based modeling and rendering, deformable objects, multi-modal interface, haptic devices, haptic rendering, medical robotics
- A.B. Rad – autonomous mobile robots, SLAM, advanced vehicle control systems, intelligent control, time delay systems, system identification, process control
- N. Rajapakse – adaptive (smart) materials and structures, nanomechanics and multi-scale modelling, fracture mechanics, geomechanics
- A.H. Rawicz – biomedical transducers (sensors and actuators), optical engineering and biophotonics, brain-computer interfaces, vision sensors, reliability of biomedical devices
- S.N. Robinovitch – dynamics and control of human movement, postural stability and balance, osteoporosis and hip fracture prevention, orthopedic biomechanics, rehabilitation engineering
- P. Saeedi – computer vision, machine learning in computer vision, motion/trajectory tracking, object recognition using vision, structure from motion, and automatic 3D map generation
- M. Saif – estimation and control theory, model based fault diagnosis, large scale systems, optimization, and application of the above to engineering systems
- S.P. Stapleton – passive RF/microwave circuits, GaAs monolithic microwave integrated circuits, nonlinear RF/microwave devices, active RF/microwave circuits
- M.V. Sarunic – biomedical optical imaging, optical coherence tomography (OCT), low-coherence interferometry, optical microscopy
- L. Shannon – computing system design; system-on-chip and network-on-chip; architectures; reconfigurable computing and FPGAs; embedded system design; on-chip CAD tools
- S.P. Stapleton – power amplifier linearization, high efficiency power amplifier design techniques, high speed digital signal processing, monolithic microwave integrated circuits, integrated RF/DSP systems, high power device characterization
- M. Syrzycki – microelectronics, semiconductor devices, analog and mixed signal CMOS ICs, integrated circuit technology, integrated sensor microsystems, vision sensors, design for manufacturability of analog and digital CMOS ICs
- L. Trajkovic – communication networks (traffic characterization and modeling, protocols and network control algorithms); nonlinear systems (circuit simulation tools, theory of nonlinear circuits, analysis of complex networks)
- R.G. Vaughan – personal and mobile communications, compact antennas, diversity antennas, propagation, signal processing, DSP techniques wireless systems, microwave techniques, multiport and MIMO systems
- G. Wang – product design optimization, design theories and methodologies, process improvement for health care, alternative energy for transportation, advanced manufacturing
Associate Members
For areas of research, refer to the department listed.
- M. Donelan, Department of Biomedical Physiology and Kinesiology
- J.A. Hoffer, Department of Biomedical Physiology and Kinesiology
*emeritus
The School of Engineering Science offers two distinct master’s degrees, master of engineering (MEng), or master of applied science (MASc) and a doctor of philosophy (PhD) degree.
If the subject matter of a listed course has been previously completed with graduate credit, the course may not be completed again for credit.
The MEng program, for part-time study by practising engineers, is based on a course set normally offered in the evenings, plus a project performed in industry. The principal areas of study are electronics, communications and signal processing, intelligent systems, and control theory.
The MASc is a full-time program with primary emphasis on the thesis rather than course work, is more exploratory than the MEng, and covers a greater range of study.
Admission Requirements
The normal admission requirement to the MEng and MASc programs is a bachelor’s degree in electrical engineering, computer engineering, engineering science or a related area, with a 3.0 CGPA (B grade) from a recognized university, or equivalent. The number of faculty members limits the number of MASc students accepted into the programs.
Transfer from MEng to MASc Program
Normally transfer from the MEng to the MASc will be considered under the following conditions.
Undergraduate Grade Point Average
Minimum undergraduate CGPA of 3.3 is required.
MEng Grade Point Average
On at least two courses, a minimum CGPA of 3.5 is required.
Degree Requirements – MEng Program
Course Work
MEng candidates complete at least 21 graduate course units. All students complete ENSC 820, specialize in an area of study, and complete required courses as follows. Students specializing in communications complete ENSC 805 and 810; electronics specialization students complete one of ENSC 851, 852 or 853; and intelligent systems or control theory specialists complete ENSC 801. Elective courses (see below) comprise the remainder of the 21 required units. Additional courses may be required to correct background deficiencies.
In addition, a student completes a project which is expected to take a minimum of two full-time equivalent months. If the project is performed in the student’s workplace, the student receives academic supervision from the senior supervisor, and day-to-day supervision from the manager, or designated associate. Industrial supervisors, who are on the supervisory committee, will be appointed by the graduate chair in consultation with the senior supervisor. In very small companies, alternate arrangements will be made for industrial supervision.
In addition to submission of a technical report at project completion, the student makes an oral presentation to the supervisory committee and the graduate chair. A grade will be assigned based on the report’s quality, the presentation, and the student’s understanding of the subject. A grade of ‘complete’ or ‘in progress’ will reflect the majority decision. In the case of an ‘in progress’ grade, the student re-submits the project report and presents it again.
MEng Fees
Students may complete their program before paying the minimum total fee. An additional payment is required prior to graduation to satisfy the minimum fee requirement of six full-time fee units. See “Graduate Fees” on page 227.
Degree Requirements – MASc Program
MASc candidates complete 30 units consisting of a minimum of 12 units, plus a thesis equal to 18 units. In consultation with the senior supervisor, the courses will normally be selected from the list below, except that ENSC 820 may not be used towards the MASc course requirements. At least six units must be ENSC graduate courses. At most, three units may be directed studies.
Additional courses may be required to correct deficiencies in the student’s background.
The thesis is based on an independent project with a significant research component. The student defends the thesis at an exam, in accordance with regulations.
Graduate Research Internship
With the supervisory committee’s approval, students accepted to the MASc or PhD programs may do research internship in industry. The responsibility for finding a suitable internship rests with the student, though the senior supervisor will provide guidance. In addition to satisfying degree requirements, students must satisfy the following conditions.
Proposal
The proposal must be approved by the supervisory committee and by the graduate committee. The proposal must include the following.
• justification for undertaking the work in industry
• agreement regarding intellectual property and publications
• funding arrangement
On-campus Presence
During the internship, the student must spend at least one day per week (or equivalent as approved by the graduate committee) on campus to meet with his/her supervisor and attend regular seminars. This is in addition to time spent on campus for course work.
Oral Presentations
At least two supervisory committee oral presentations (not including thesis defence) on the progress of the student’s work will be given during the internship.
Duration
The duration of the internship will not exceed two terms for an MASc student, or four terms in the case of a PhD student.
Failure to Comply
See “1.8 Progress, Withdrawal and Leave” on page 223 in the Graduate General Regulations.
Admission Requirements
For admission, a student must have a master’s degree in electrical engineering, mechanical engineering, physics, computer science or a related field, have submitted evidence od capability to undertake substantial original research, and have identified a faculty member as senior supervisor.
See “1.3 Admission” on page 219 for other PhD program admission requirements.
Residence Requirement
Students will conform to the residence requirement (see “1.7 Residence and Course Requirements” on page 222).
Transfer from the Master’s Program to the PhD Program
Proceeding to a PhD program without completing a master’s degree is discouraged. However, a student may be admitted after at least 12 months in the MASc program if all requirements have been completed with a 3.67 or better CGPA, outstanding potential for research has been shown, and approval of the student’s supervisory committee, graduate program committee and senate graduate studies committee has been given.
Degree Requirements
Course Work
The minimum requirement is 18 units beyond that of the MASc degree. Six of these units will be for prescribed courses in the option in which the student is enrolled. Alternatives can be substituted with the approval of the student’s supervisory committee. At most, six units may be senior undergraduate courses. At most, six units may be directed studies. At least six units must be within engineering science, except that ENSC 820-3 may not be used toward the course requirement of the PhD degree. Additional courses may be required to correct deficiencies in the student’s background.
Qualifying Examination
To qualify the student will submit a brief written research proposal and defend it orally to his/her supervisory committee within the first 24 months of admission. The proposal defence will be judged according to the feasibility and scientific merits of the proposed research, and demonstration of a sophisticated understanding of general material in the student’s major area of research. This level of understanding is associated with senior undergraduate and first year graduate course material. The possible outcomes of the qualifying examination are ‘pass,’ ‘marginal’ and ‘fail’ (a student with ‘marginal’ will be required to re-submit the research proposal and defend it for the second and final time within six months and/or to complete more courses; a ‘failing’ grade requires withdrawal).
Thesis
Students define and undertake original research, the results of which are reported in a thesis. An examining committee is formed as defined in “1.9.3 Examining Committee for Doctoral Thesis” on page 224. Students conform to residence requirements (see “1.7.3 Residence Requirement for the Doctoral Degree” on page 223). The senior supervisor will be an engineering science faculty approved by the graduate program committee.
The student’s progress will be reviewed every 12 months by a supervisory committee of three or more faculty members. At each annual review, the student presents a summary of his/her work to date, with the first review being the research proposal defence described in the section for Qualifying Examination (see above). Students not making satisfactory progress in their research topics, or failing to demonstrate satisfactory knowledge and understanding of recent publications in their general area of research, or failing to have their revised research proposal approved by the supervisory committee within 20 months of admission, may be required to withdraw as per section “1.8.2 Review of Unsatisfactory Progress” on page 223.
Directed Studies and Special Topics Courses
Directed studies (ENSC 891, 892) and special topics (ENSC 893, 894, 895) courses may be offered by the following research groups, subject to student interest and demand.
Communications Group
- estimation theory
- network performance evaluation
- optical telecommunications networks
- advanced modulation techniques
- spread spectrum communications
- information flow and decision theory
- adaptive arrays
- active and passive sonar systems
- synthetic aperture radar
- multimedia signal processing
- multimedia communications
- active and passive sonar systems
- synthetic aperture radar
- multimedia signal processing
- multimedia communications
- ad hoc and sensor networks
- small antennas
Microelectronic group
- analog VLSI signal and information processing
- applied solid state electronics
- CMOS compatible micromachining
- embedded VLSI systems
- low power, low noise, high frequency circuits
- optoelectronic devices
- photonics and laser applications in engineering
- reliability engineering
- sensor – principles and applications
- VLSI circuits for telecommunications
Intelligent Systems and Control Group
- design optimization
- algorithms for robotics
- intelligent design
- intelligent control of robotic systems
- intelligent manufacturing systems
- model-based fault diagnostics in control systems
- multivariable control systems
- nonlinear control systems
- numerical modelling of heat transfer
- robotic synthesis
Courses Offered by Other Departments
These courses are of particular interest to engineering science students. Descriptions can be found in the “Course Catalogue” on page 311.
BUEC 820-4 Analysis of Dynamic Processes
CMPT 720-3 Artificial Intelligence
CMPT 750-3 Computer Architecture
CMPT 815-3 Algorithms of Optimization
CMPT 821-3 Robot Vision
CMPT 822-3 Computational Vision
CMPT 827-3 Expert Systems
CMPT 851-3 Fault-Tolerant Computing and Testing
CMPT 852-3 VLSI Systems Design
CMPT 853-3 Computer-Aided Design/Design Automation for Digital Systems
KIN 885-3 Seminar on Man-Machine Systems
MATH 851-4 Numerical Solutions of Ordinary Differential Equations
PHYS 425/821-3 Electromagnetic Theory
PHYS 810-3 Fundamental Quantum Mechanics
PHYS 861-3 Introduction to Solid State Physics
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