Difference between revisions of "Yenting Lin"

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Yenting (Greg) Lin
 
 
PHD student in University of Southern California
 
 
 
== Yenting (Greg) Lin  
 
== Yenting (Greg) Lin  
  

Revision as of 15:26, 1 February 2013

== Yenting (Greg) Lin


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Yenting Lin
  • Ph.D. Candidate (expect graduation: May 2013)
Advisor: Antonio Ortega
Signal and Image Processing Institute
Ming Hsieh Electrical Engineering Department
University of Southern California
  • Address: 3740 McClintock Ave., EEB 441, Los Angeles, CA 90089-2564 Google Map
  • Telephone: (213)-740-4655

Research Interests

My research interest is to recover the low-dimensional structure from sparse (incomplete, corrupted) observations, and apply them to solve problems in signal processing (reservoir modeling and 3D object reconstruction)

  • Transmission tomography for high contrast structures
  • Compressive sensing and sparse structure exploitation in tight, unconventional reservoir
  • Sparse reconstruction for X-Ray discrete tomography
  • Group testing for well production measuring
  • Signal processing for plenoptic camera

Education

  • Sep. 2006-present: University of Southern California, Los Angeles, CA

Ph.D. student, Department of Electrical Engineering-Systems

  • Sep. 2004-May. 2006: University of Southern California, Los Angeles, CA

Master of Science, May 2006, Department of Electrical Engineering-Systems

  • Sep. 1997-May. 2001: National Taiwan University, Taiwan

Bachelor of Science in Engineering, June. 2001, School of Electrical Engineering and Computer Science

Academic Experience

  • Research Assistant, Sep. 2007 - Present
    • Travel time tomography for high contrast media with sparse data
      • Develop algorithms to detect the high contrast structure with sparse water injection and oil production data.
    • Group testing for automatic well-testing system
      • Develop a novel algorithm to increase the production well-testing frequency up to 70% without changing any hardware.
    • Discrete X-ray tomography
      • Reconstruction of high contrast X-ray image (e.g., Angiography) with reduced radiation up to 90%.
    • Underwater acoustic tomography
      • Reduce the variance of estimate travel time in an noisy underwater environment up to 50%.
  • Teaching Assistant, Aug. 2006- May 2007
    • Communication theory
      • Lectured Communication theory discussion session for groups of 30 students, 1 hours/week (2 semesters)

Professional Experience



  • Jun. 2002 to Feb. 2004 Military Service in Taiwan Army as Second Lieutenant
    • Contribution:
      • Manage and maintain the military combat communication network.
      • Lead the development team for C4ISR

Skills / Tools

  • Proficient in C/C++, Matlab.
  • Good knowledge of Mathematical optimization.


Conference Publications

  • Y. Lin and A. Ortega, "Group Testing: A Novel Approach To Increase The Effective Frequency Or Accuracy Of Well-tests Without Increasing Infrastructure Costs", to appear in SPE Western Regional Meeting, Monterey, April 2013.
  • Y. Lin, A. Ortega, T. Tafti, and I. Ershaghi, "Detecting shale discontinuity between different layers using water-flood tomography", in SPE Western Regional Meeting, Bakersfield, March 2012.
  • Lin, Y and Ortega, Antonio and Dimakis, Alexandros G. "Level estimation for sparse reconstruction in discrete tomography". In Proceedings of 2011 Asilomar Conference on Signals, Systems and Computers (ASILOMAR), , 6-9 Nov. 2011
  • Lin, Y. and Ortega, A. "Reconstruction algorithm for high contrast velocity travel time tomography". In Proceedings of the 2010 IEEE International Acoustics Speech and Signal Processing Conference(ICASSP 2010),, Dallas, March 2010.
  • Lin, Y. and Ortega, A. and Nejad, A. and Ershaghi, I. "Waterflood Tomography: Mapping High Contrast Permeability Structures Using Injection/Production Data". In Proceedings of the 2010 SPE Western Regional Meeting(SPE WRM 2010), , Anaheim, May 2010.
  • Lin, Y. and Ortega, A. and Dimakis, A.G. "Sparse recovery for discrete tomography". In Proceedings of the 2010 IEEE International Conference on Image Processing (ICIP), 2010, , Hong Kong, October 2010.