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Liu, Ying

Biography

Dr. Ying Liu is an Assistant Professor in the Department of Computer Engineering at Santa Clara University. She graduated from the Department of Electrical Engineering at The State University of New York, University at Buffalo (SUNY at Buffalo). Her general areas of expertise are computer vision, machine learning, and signal processing. Her research is focused on video analysis, high-dimensional data, and compressed sensing. She is a member of the Institute of Electrical and Electronics Engineers (IEEE) and a member of the Society of Photo-Optical Instrumentation Engineers (SPIE). Her research articles are published in IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE Transactions on Multimedia (TMM), SPIE Journal of Electronic Imaging (JEI), and many prestigious conferences. She serves as a reviewer of many top-ranked journals and also serves as the technical program committee member of multiple international conferences.

 

Education

Ph.D., Electrical Engineering, SUNY at Buffalo, 2012

M.S., Electrical Engineering, SUNY at Buffalo, 2008

B.S., Telecommunications Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China, 2006

 

Teaching

COEN 166 Artificial Intelligence (Fall 2018)

COEN 266 Artificial Intelligence (Winter 2019)

 

Website

http://www.cse.scu.edu/~yliu1/

Selected Publications

  1. Y. Liu, D. A. Pados, J. Kim, and C. Zhang, “Reconstruction of compressed-sensed multiview video with disparity and motion compensated total-variation minimization,” IEEE Trans. Circuits and Systems for Video Technology, vol. 28, pp. 1288-1302, June 2018.

  2. Y. Liu and D. A. Pados, “Compressed-sensed-domain L1-PCA video surveillance,” IEEE Trans. Multimedia, vol. 18, pp. 351-363, Mar. 2016.

  3. Y. Liu, M. Li, and D. A. Pados, “Motion-aware decoding of compressed-sensed video,” IEEE Trans. Circuits and Systems for Video Technology, vol. 23, pp. 438-444, Mar. 2013.

  4. Y. Liu and D. A. Pados, “Decoding of framewise compressed-sensed video via interframe total variation minimization,” SPIE Journal of Electronic Imaging, Special Issue on Compressive Sensing for Imaging, Apr.-June 2013.

  5. Y. Liu, D. A. Pados, S. N. Batalama, and M. J. Medley, “Iterative re-weighted L1-norm principal-component analysis,” in Proc. Asilomar Conf. Signals, Systems, and Computers, Pacific Grove, CA, Oct. - Nov. 2017.

  6. Y. Liu, S. Chamadia, and D. A. Pados, “Joint-view Kalman-filter recovery of compressed- sensed multiview videos,” in Proc. IEEE Int. Conf. Acoust. Speech, and Signal Process. (ICASSP), Shanghai, China, Mar. 2016.

  7. K. R. Vijayanagar, Y. Liu, and J. Kim, “Adaptive measurement rate allocation for block- based compressed sensing of depth maps,” in Proc. IEEE Int. Conf. Image Process. (ICIP), Paris, France, Oct. 2014.

     
     
     
     
     

Ying Liu