My research interests lie broadly in the following aspects: (1) SAR, PolSAR data processing and the associated applications, particularly in ocean environment monitoring; (2) Hyperspectral and multispectral unmixing, classification, segmentation, feature extraction, and the associated applications; (3) Quantitative and computational methods in remote sensing and other geospatial application, spatial-multivariate data modeling and mining, quantitative remote sensing, image processing & com.
My research areas include image processing (statistical), machine learning, and computer vision. I am working under the supervision of Professor Fieguth.
I am very interested in spectropolarimetric optical imaging techniques and utilizing them for medical purposes. I have extended interests as well in medical image processing and analysis, in particular with prostate MRI.
My research applies computers to analysis and optimization problems in healthcare, with a focus on cancer. This involves pattern recognition, statistical machine learning, health informatics, signal & image processing and other disciplines. I am supervised by Prof. Paul Fieguth and Prof. Helen Chen.
My research interests lie in the area of Machine Learning, Computer Vision and Cognitive Science. I am especially interested in developing new Machine Learning algorithms for analyzing structures in massive data sources as well as learning predictive models based on those structures. Besides this, I am researching about the functionality of human visual system and learning how to model impressive properties of this mysterious system.
My research interests include Computer Vision, Machine Learning and Biomedical Image Processing while my main focus is on Graphical Models specially Conditional Random Fields and Markov Random Fields
My research focuses on non-linear multiscale data assimilation for sea ice forecasting. I also work at The Waterloo Institute for Social Innovation and Resilience at the University of Waterloo developing models to support decision makers. I am is interested in the common patterns that drive systems ranging from cells to societies and in what makes long-term prosperity possible.
My research interests mainly lie in the fields of image processing and computer vision and problems related to pattern recognition, machine learning, biomedical signal and image analysis.
My research passions lie broadly in the realm of computer vision with a HCI/human factors twist. I am focusing my PhD thesis work on extracting hemodynamic information from videos. For my Master's, I designed intuitive image features to help doctors make more accurate diagnoses of melanoma. Apart from medical image processing, I have also dappled with remote sensing (hyper- & multi-spectral) and photogrammetry (3D stereo vision).
In the VIP Lab, I am a part-time Ph.D. student conducting research for my full-time employer, Christie Digital Systems. Although I work in Software Engineering at Christie, my research purpose here is to investigate and develop robust methods of extracting geometry from sparse measurements.
My research interest is in the field of image and signal processing, pattern recognition and computer vision while mainly focusing on the optical imaging. My current research is concerned with enhancing the existence image processing methods for the Optical Coherence Tomography (OCT) images.
My active reserach includes hyperspectral imaging techniques, spectroscopy, microscopy, and ultrasound imaging for arterial wall degradation.
My research interests include image processing and computer vision, with specific emphasis on biomedical imaging. My current research primarily focuses on computer-aided prostate cancer detection and grading via multi-parametric MRI. Other projects include lung nodule segmentation, video photoplethysmography, and illumination-robust feature detection.
I am passionate about working collaboratively to solve applied research problems. I have a biomedical science background with a Master’s in nutrition and physiology. I am focusing my PhD thesis work on pushing the boundaries in nutrition research methods for application in our aging population and beyond. Specifically, I am developing a non-contact multispectral imaging system geared for nutrient sensing on a smartphone. My dream is to marry lab quality results with the ease of on-site, real-time measurements for a reliable and less burdensome alternative to pen and paper methods of food-intake and nutrient intake analysis.
My passion lies in space technologies and satellite-based for remote sensing; specifically GNSS Reflectometry. I am the current Project Manager of WatSat - the University of Waterloo Micro-Satellite team (www.watsat.ca) .
Sara graduated in 2014 from the University of Waterloo with a BASc in Systems Design Engineering. After spending a year in the world of web development, she returned to UW and is currently working on a Master's degree studying markerless tracking of the human body. In her spare time, Sara is involved in the circus arts community, and enjoys combining her academic research with acrobatic performance to create multimedia artwork.