Dr. Rabab Kreidieh Ward
Professor, Electrical and Computer Engineering
FRSC , FIEEE , FCAE , FEIC
Dr. Rabab K.
Ward is a Professor in the Electrical and Computer Engineering
Department at the University of British Columbia ( UBC), Canada. She is
presently appointed in the Office of the Vice-President Research Office
as the natural sciences and engineering research coordinator for UBC.
She ensures that initiatives are developed to support research and
scholarship in engineering and the natural sciences and that the
relevant information is disseminated .
She is Fellow of the Royal Society of Canada, the Institute of
Electrical and Electronics Engineers, the Canadian Academy of Engineers
and the Engineering Institute of Canada. She has received the Career
Achievement Award of CUFA, BC, the organization representing all
professors and academic staff at BC's doctoral universities (2011), UBC
Engineering Co-op Faculty Member of the Year Award (2010), the IEEE
Signal Processing Society top award "The Society Award" (2008), the YWCA
Woman of Distinction Award (2008), British
Columbia's top engineering award "The RA McLachlan Memorial Award"
(2006) and UBC Killam Research Prize (1998).
Dr Ward's research interests are
mainly in the areas of signal, image and video processing. She has made
contributions in the areas of signal detection, image encoding,
compression, recognition, restoration and enhancement, and their
applications to cable TV, HDTV, medical images, infant cry signals and
brain computer interfaces . She has published around 130 refereed
journal papers, 260 refereed conference articles and holds six patents
related to cable television picture monitoring, measurement and noise
reduction. Applications of her work have been transferred to U.S. and
Canadian industries. She is the inventor of the non-intrusive
measurement methods for cable TV video impairments (licensed to
Hewlett-Packard) and co-inventor of a non-interfering video system for
measuring size and biomass of fish in cages and Tanks (licensed to J. B.
Thompson and Associates).
She was the Vice President of the IEEE
Signal Processing Society (2003 - 2005) and a member of the Society's
Board of Governors( 2003-2995 and 2008-1010). She was the General Chair
of the IEEE International Conference on Image Processing 2000, the Vice
Chair of the IEEE International Symposium on Circuits & Systems 2004,
chair of the IEEE Symposium on Signal Processing and Information
Technology and is the co-chair of ICASSP 2013.
She was the Principal Investigator of the $22.2 million CFI/BCKDF award
which resulted in a new building at UBC that houses the most modern
equipment in all areas related to human centered technologies .
You can download my CV
Current Research Projects
Developing asynchronous Brain Computer Interface systems:
The ultimate aim is to use the EEG as a direct communication channel from
the brain of a person with severe motor disabilities to the real world.
This is achieved by analyzing a person's EEG signal to detect whether or
not it contains an activity relating to the person's intention to control
his/her environment or a device.
Magnetic Resonance Imaging: Magnetic Resonance
Imaging (MRI) is a versatile medical imaging modality. It can produce very
high quality images without any biological side-effects. However it is a
slow imaging modality. There has been physics (hardware) based and signal
processing (software) based acceleration techniques to speed-up MR
acquisition times. Our research is driven by recent advances in Compressed
Sensing. We intend to speed-up data acquisition times, by collecting less
data (than required by traditional MRI techniques) and reconstructing the
image by using smart Compressed Sensing algorithms. In particular we focus
on the following areas on MR Imaging:
o Single slice MR imaging from single and multiple K-space scans.
o Quantitative MR imaging.
o Combining signal processing and physics based techniques for parallel
o Dynamic MRI.
Content based multimedia fingerprinting: This
project addresses copy detection and copyright protection in multimedia
sharing websites. The aim is to develop algorithms that can identify
whether a query video (or part of it) has been copied form an existing
video in a large database of videos . The approach used is called
fingerprinting . Fingerprinting extracts from a video, compact signatures
that should uniquely identify this video or any distorted versions
of it. The main two challenges in video fingerprinting are the design of
the fingerprinting algorithm and the search algorithm that can identify a
certain fingerprint in a huge database of fingerprints in a correct and
fast fashion .
Information hiding and quality monitoring using
watermarking: Data hiding is usually used in
secret communication between two parties. Towards this aim, a binary
secret message is imperceptibly inserted into the content. For example,
this message could be the identification number of the content owner. At
the receiver side, the hidden information should be extracted as
accurately as possible. Watermarking has also been adopted as a technique
to provide a blind measure of the quality of service (QoS) in multimedia
communications. In such applications, the watermark is embedded into the
original image at the transmitter side. The image quality is estimated at
the receiver side by extracting the watermark from the received image and
comparing it with the original watermark.
Human activity recognition
in real videos: This project aims at recognizing human
action under occlusion, scale and viewpoint changes. The task is highly
challenging as we work on real world videos collected from Youtube,
movies, TV broadcasts etc.
Digital image interpolation is also known as image enlargement /reduction
has many application in the advertising industry, digital cameras, video
compression etc. Content-adaptive and Wavelet-based image interpolation
techniques are developed. Efforts are also directed to finding efficient
methods for edge enhancement, removing edge zigzagging and solving the
loss of contrast after image enlargement.
recognition invariant to pose, illumination, and facial expression
approaches are based on wavelet transform and principal component analysis
to normalize illumination variation and to extract more salient features
to facilitate the face recognition task.
Reversible integer-to-integer wavelet/subband transforms
in the context of JPEG-2000 standardization effort.
Selected Recent Publications|
For the complete
list of publications, please refer to my
Kharma, N., Ebne-Alian, M., Medina, O., Charbonneau, L., Dhot, T., Ward, R.,
and Rouleau, G., "Evolution of Image Secgementation Programs for Automated Processing of
Microscopic Images of Cells in Culture", IEEE Trans. Evolutionary Compuation, (submitted September
Fu, H., Xu, D., Zhang, B., Lin, S., and Ward, R. K. "Object-based
Multiple Foreground Video Co-segmentation via Multi-state Selection Graph," IEEE Trans on Image
Processing, (under revision).
Guha, T., Nezhadarya, E., and Ward, R. K., "Sparse
Representation-based Image Quality Assessment", Signal Processing: Image Communication, (Accepted
for publication, October 2014).
Majumdar, A., and Ward, R. K., " Exploiting Sparsity and Rank Deficiency for
MR Image Reconstruction from Multiple Partial K-Space Scans", Canadian Journal of Electrical and
Computer Engineering, Vol. 37(4), pp. 228-235, 2014.
Nezhadarya, E. and Ward, R. K., "Multiscale Derivative Transform
and Its Application to Image Watermarking", Elsevier Digital Signal Processing, Vol. 33,
pp. 148-155, 2014.
Guha, T., and Ward, R.K., "Image Similarity Using Sparse
Representation and Compression Distance", IEEE Transactions on Multimedia, Vol. 16 (4),
pp. 980-987, 2014.
Chen, X., Liu, A., Peng, H., and Ward, R., "A Preliminary Study
of Muscular Artifact Cancellation in Single-Channel EEG", Sensors, 14(10), pp. 18370-18389,
Majumdar, A., Anupriya, G., and Ward, R. K., "A Low-Rank Matrix
Recovery Approach for Energy Efficient EEG Acquisition for a Wireless Body Area Network", Sensors,
Vol. 14(9), pp. 15729-15748, 2014.
Majumdar, A., and Ward, R. K., "Non-convex row-sparse multiple
measurement vector analysis prior formulation for EEG signal reconstruction", Biomedical Signal
Processing and Control, Vol. 13, pp. 142-147, 2014.
Vahedi, E., Ward R. K., and Blake, I. F., "Performance analysis
of RFID protocols: CDMA vs. the standard EPC Gen2," IEEE Transactions on Automation Sciences and
Engineering, Vol. PP(9), pp. 1-12, January 2014.
Sheikhzadeh, F., MacAulay, C., Guillaud, M., Lane, P., Carraro, A., Ward, R., and
McKenna, J., "Fluorescence confocal microscopy for detection of cervical preneoplastic lesions", 2015
SPIE Medical Imaging Symposium, 21 - 26 February 2015, Orlando, Florida United States.
Majumdar, A., Shukla, A. and Ward, R., "Combining Sparsity with Rank-Deficiency for
Energy Efficient EEG Sensing and Transmission over Wireless Body Area Network", IEEE Int. Conf. on
Acoustics, Speech, and Signal Processing (ICASSP), Brisbane, Australia, April 2015 (submitted).
Majumdar, A., and Ward, R., "Learning the Sparsity Basis in Low-rank
plus Sparse Model for Dynamic MRI Reconstruction", IEEE Int. Conf. on Acoustics, Speech, and Signal
Processing (ICASSP), Brisbane, Australia, April 2015 (submitted).
Majumdar, A., and Ward, R., "Improved Blind Compressed Sensing for
Dynamic MRI Reconstruction", Magnetic Resonance Imaging, Abstracts pp. 4381, 22( 2014).
Ward, R. and Majumdar, A., "Exploiting Sparsity and Rank-deficiency
in Dynamic CT Reconstruction", IEEE Medcom 2014, 7th to 8th November, Greater Nodia, India.
Majumdar, A., and Ward, R., "Fast SVD Free Low-rank Matrix Recovery:
Application to Dynamic MRI Reconstruction", IEEE Medcom 2014, 7th to 8th November, Greater Nodia, India.
Palangi, H., Deng, L., and Ward, R. K., "Recurrent deep-stacking
networks for sequence classification", 2nd IEEE China Summit & International Conference on Signal and
Information Processing, pp. 510 – 514, Xi’an, China 9-13 July 2014.
Majumdar, A., and Ward, R. K., "Improved MRI Reconstruction via
Non-Convex Elastic Net", IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), Florence,
Italy, May 2014 (accepted).
Guha, T., and Ward, R. K., "Learning Sparse Models for Image Quality
Assessment", IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP), pp. 151- 154, Florence,
Italy, May 2014.