She is currently a lecturer and researcher at the Amirkabir University of Technology, Department of Computer Engineering and Information Technology, and University of Economic Science.

Her research is primarily in image and video processing, statistical modeling and machine learning. She has published and reviewed several papers for key journals and conferences in the related areas of image processing, image analysis and pattern recognition.

Before her PhD, Ying worked for four years on the research and development of signal processing for underwater systems. In 2010, she collaborated with the compression research group in Research In Motion Ltd. on video processing research for the coming standard HEVC. Recently, she is collaborating with Center of Pattern Analysis and Machine Intelligence, University of Waterloo and working on data analysis and machine learning.

Email: 30liu@engmail.uwaterloo.ca

Our approach to this class of problems has been to treat the problem as an inverse or estimation problem. Because the fine-scale porous field is discrete (pore / not pore), discrete-state solvers such as Simulated Annealing are quite effective, such as the following example from the work of Mohebi:

The above work left us with two challenges:

1. How to address very large fields with structure on a wide variety of scales.
2. How to address nonstationary fields, those with multiple distinct behaviours.

The work of Liu considered hierarchical models (challenge 1) having hidden fields containing a label describing some attribute of behaviour (challenge 2):

 This work led to promising results on fairly complex fields:

The performance of the method proposed by Liu is quite strikingly better than that produced by other wavelet resolution-enhancement methods.

Related people

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Alumni

Related research areas

Multiresolution Techniques

Stochastic Models

Scientific Imaging

Related publications

Theses

Campaigne, W., “Frozen-State Hierarchical Annealing”, Department of Systems Design Engineering, 2012. Get it here.

Liu, Y., “Hidden Hierarchical Markov Fields for Image Modeling”, Department of Systems Design Engineering, Waterloo, Ontario, Canada, University of Waterloo, 2011. Get it here.

Students

Supervision – Current

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ph.D.

M.A.Sc.

Supervision – Completed

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ph.D.

M.A.Sc.