Dr. Rabab Kreidieh
Professor Emeritus, Electrical and Computer Engineering
FRSC , FIEEE , FCAE , FEIC
Dr. Rabab K. Ward is a Professor Emeritus in
the Electrical and Computer Engineering Department at the University of
British Columbia (UBC), Canada. 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 UBC Applied Science Dean’s Medal of Distinction
(2016), Killam Award for Excellence in Mentoring (2013), 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).
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 180
refereed journal papers, 330 refereed conference articles and holds eight
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 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 is the President of the IEEE Signal
Processing Society. She was the Vice President of this Society (2003 -
2005) and a member of the Society's Board of Governors (2003-2995 and
2008-1010). She was the co-chair of the IEEE International Conference on
Acoustic Speech & Signal Processing (2013) and the IEEE International
Conference on Image Processing (2000), the vice chair of the IEEE
International Symposium on Circuits & Systems (2004) and is the chair
of the IEEE Symposium on Signal Processing and Information Technology
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 here.
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 MRI.
o Dynamic MRI.
Content based multimedia
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 .
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.
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: 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.
integer-to-integer wavelet/subband transforms
in the context of JPEG-2000 standardization effort.
complete list of publications, please refer to my publication
Majumdar, A., and R. K. Ward, MRI: Physics,
Analysis. CRC Press, 2015
Ward, R. K., Carraro, A., Chen, Z., van Niekerk, D., Miller, D., Ehlen,
T., MacAulay, C., Follen, M., Lane, P., and Guillaud, M. “Quantification of confocal fluorescence
microscopy for the detection of cervical interaepithelial
neoplasia.” BioMed Eng
OnLine (2015) 14:96.
Palangi, H., R. Ward, and L. Deng,
“Distributed Compressive Sensing: A Deep Learning Approach", in IEEE
Transactions on Signal Processing (submitted, 2015).
Palangi, H., L. Deng, Y. Shen, J. Gao, X. He, J. Chen, X. Song, and R. Ward, “Deep
Sentence Embedding Using the Long Short-Term Memory Networks", in IEEE/ACM
Transactions on Audio, Speech, and Language Processing (under review,
Mahrous, H., and
R. Ward, R., “Block Sparse Compressed Sensing of EEG Signals by
exploiting Linear and Non-linear Dependencies”, IEEE Journal of Selected
Topics in Signal Processing, (submitted 2015).
Liu, A., X. Chen, J. Chiang, J. Wang, M.J.
McKeown, and R.K. Ward, “Removing Muscle Artifacts from EEG Data:
Multichannel or Single-Channel Techniques?”, IEEE Sensors Journal,
(accepted November 2015).
Bashashati, H., and R. Ward, R.,
“User-Customized Brain Computer Interfaces Using Bayesian
Optimization”, Journal of Neural Engineering, (accepted, November 2015).
Karimi, D., and R. Ward, R., “Sinogram
Denoising via Simultaneous Sparse Representation in Learned
Dictionaries”, IEEE Transactions on Medical Imaging, (submitted August
Karimi, D., and R. Ward, R., “A Sinogram
Denoising Algorithm for Low-Dose Computed Tomography”, BMC Medical
Imaging, (submitted July 2015).
Karimi, D., and R. Ward, R., “Reducing
streak artifacts in computed tomography via sparse representation in
coupled dictionaries”, Medical Physics, (submitted September 2015).
Bashashati, H., Ward, R.K., Birch, G.E.,
and Bashashati A., “Comparing Different Classifiers in Sensory Motor
Brain Computer Interfaces," Plos
One, (accepted 2015).
Rouf, M., D.
Reddy, K. Pulli and R. Ward, “Fast
edge-directed single-image super-resolution”, IS&T International
Symposium on Electronic Imaging 2016.
Sheikhzadeh, F., Carraro,
A., Korbelic, J., MacAulay, C., Guillaud,
M., and Ward, R. K. Automatic labeling of molecular biomarkers on a
cell-by-cell basis in immunohistochemistry images using convolutional
neural networks. Accepted in SPIE- Medical Imaging 2016, San Diego, US
(February 27- March 3, 2016).
Karimi, D., and R. Ward, “Sinogram
smoothing and interpolation via alternating projections onto the slope
and curvature constraints”, SPIE Medical Imaging Symposium, February 27-
March 3 2016, San Diego CA.
Karimi, D., and R. Ward, “A novel
structured dictionary for fast processing of 3D medical images, with
application to computed tomography restoration and denoising”, SPIE
Medical Imaging Symposium, February 27- March 3 2016, San Diego CA.
Palangi, H., R. Ward, and L. Deng,
“Exploiting Correlations Among Channels in Distributed Compressive
Sensing with Convolutional Deep Stacking Networks", in IEEE
International Conference on Acoustics, Speech and Signal Processing
(ICASSP), (submitted, 2016).
Bashashati, H., and R. K.Ward
and A. Bashashati,
"Customizing Brain Computer Interfaces Using Bayesian
Optimization", submitted to IEEE ICASSP 2015.
Bashashati, H., R. K.Ward
and A. Bashashati, “Hidden Markov Support Vector Machines for Self-Paced
Brain Computer Interfaces”, International Conference on Machine Learning
Applications (IEEE ICMLA), 2015.
P. Nasiopoulos, and R. Ward, " Optimal
Lagrange Multiplier in Perceptually-Friendly High Efficiency Video Coding
for Mobile Applications” , The International
Conference on Computing, Networking and Communications (ICNC16), CNC
Workshop, Hawaii, USA, Feb. 2016.
P. Nasiopoulos, and R. Ward, “Perceptual
Distortion Measurement in the Coding Unit Mode Selection for 3D-HEVC”,
IEEE International Conference on Consumer Electronics ICCE 2016, Las
Vegas, NV, USA, January 8-11, 2016.