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Yanxi Liu
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Yanxi Liu

  • Co-Director: Laboratory for Perception, Action, and Cognition (LPAC)
  • Associate Professor
338B IST Building
University Park, PA 16802
Phone: (814) 865-7495

Education:

  1. University of Massachusetts, Amherst

Biography:

Yanxi Liu received her B.S. degree in physics/electrical engineering in Beijing, China, and her Ph.D. degree in computer science for group theory applications in robotics from the University of Massachusetts. Her postdoctoral training was performed in LIFIA/IMAG, Grenoble, France. She has also spent one year at DIMACS (NSF center for Discrete Mathematics and Theoretical Computer Science) with an NSF research-education fellowship award.

Before joining the Departments of Computer Science and Engineering and Electrical Engineering at Penn State in Fall 2006 as a tenured faculty member, Dr. Liu had been with the faculty of the Robotics Institute of Carnegie Mellon University, and affiliated with the Machine Learning Department of CMU. She is also an adjunct associate professor in the Radiology Department of University of Pittsburgh and a guest professor of Huazhong University of Science and Technology in China.

Dr. Liu is the co-director (with Dr. Collins) of the Laboratory for Perception, Action, and Cognition (LPAC) at Penn State. Dr. Liu's research interests span a wide range of applications in computer vision and pattern recognition, computer graphics, medical image analysis and robotics, with two main themes: computational (a)symmetry and discriminative subspace learning. Computational symmetry addresses issues of robust representation, detection, analysis and synthesis of real world (a)symmetries and near-regularities. Discriminative subspace learning focuses on discovering low-dimensional discriminative subspaces from very large (multi-million), multi-modality feature spaces for biomedical image database and computer aided diagnosis applications in particular. With her colleagues, Dr. Liu won first place in the clinical science category and the best paper overall at the Annual Conference of Plastic and Reconstructive Surgeons for the paper "Measurement of Asymmetry in Persons with Facial Paralysis."

Dr. Liu chaired the First International Workshop on Computer Vision for Biomedical Image Applications (CVBIA) in conjunction with ICCV 2005 in Beijing, and co-edited the book: "CVBIA: Current Techniques and Future Trends," Springer-Verlag LNCS 3765. Dr. Liu serves as a reviewer/committee member/panelist for all major journals, conferences, and NIH/NSF panels of computer vision, pattern recognition, biomedical image analysis, and machine learning. She served as a chartered study section member (3-year term) for Biomedical Computing and Health Informatics at NIH. She is a senior member of IEEE and the IEEE Computer Society.

Research Interests:

Computational regularity, group theory and applications, machine learning (particularly discriminative subspace learning from multimedia data),  computer-aided diagnosis, computer vision and computer graphics (textures, urban scenes, dance, taiji), biomedical image analysis/indexing/retrieval, robotics

Selected Publications:

  1. Lee, S., Y. Liu.  2011.  Curved Glide-Reflection Symmetry Detection.  To appear in Pattern Analysis and Machine Intelligence (PAMI). (In press)
  2. Liu, Y., H. Hel-Or, C. S. Kaplan, L. Van Gool.  2010.  Computational Symmetry in Computer Vision and Computer Graphics:  A Survey.  Foundations and Trends in Computer Graphics and Vision 5(2):1-195.
  3. Park, M., K. Brocklehurts, R. Collins, Y. Liu.  November 2010.  Translational Symmetry-based Perceptual Grouping with Applications to Urban Scenes.  Proceedings of the Tenth Asian Conference on Computer Vision (ACCV 2010).  pp. 329-342.  Queenstown, New Zealand.
  4. Lee, S., Y. Liu.  September 2010.  Skewed Rotation Symmetry Group Detection.  IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) 32(9):1659-1672.
  5. Liu, Y., W-C. Lin, J. Hays. August 2004. Near-Regular Texture Analysis and Manipulation. ACM Transactions on Graphics (SIGGRAPH) 23(3):368-376.