Juan Shan
Assistant Professor

E-mail: jshan@pace.edu

School/College: Seidenberg School of Computer Science and Information Systems
Department(s): Computer Science NY
Primary Location:

Office Hours: (Fall 2014)
Tuesday
2:30PM-5:00PM
Thursday
2:30PM-5:00PM

Office Phone:
+1-212-346-1014

CV: DOWNLOAD

Education

PhD, Utah State University, Logan, UT, 2011

Computer Science

BS, Harbin Institute of Technology, Harbin, China, 2004

Computer Science

Scheduled Courses

Fall 2014:
  • CS 121: Computer Programming I
  • CS 121: Computer Programming I
  • DCS 990: Dissertation for DPS in Cmptng
  • CS 502: Fund Comp Sci I using Java

View All Courses Taught
  • CIS 101: Introduction to Computing
  • CIT 314: Introduction to Programming II
  • CS 113: Mathematical Structures for CS
  • CS 121: Computer Programming I
  • CS 122: Computer Programming II
  • CS 502: Fund Comp Sci I using Java
  • DCS 891: Research Seminar VI
  • DCS 990: Dissertation for DPS in Cmptng
  • Research Interests

    Automatic Diagnosis for Breast Cancer; Medical Image Processing; Machine Learning; Pattern Recognition

    Awards and Honors

    • Pace University, April 2014 - Research Day 2014 Awardee

    PROFESSIONAL MEMBERSHIPS

    • IEEE membership 2010
    • IEEE Women in Engineering 2011

    Publications

    • Shan, J. (2014, May). A new scheme to evaluate the accuracy of knowledge representation in automated breast cancer diagnosis. http://cts2014.cisedu.info/
    • Shan, J. A novel multiplayer tracking system for short track speed skating. IET Computer Vision. , pages 16. http://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2014.0001
    • Shan, J. (2012). Breast ultrasound image segmentation based on neutrosophic l-means clustering.
    • Shan, J. (2012, September). “effective and automatic breast ultrasound image segmentation using l-means clustering. Medical Physics. Vol 39 (Issue 9) , pages 5669-5682.
    • Shan, J. & , . (2012, February). Completely automated segmentation approach for breast ultrasound images using multiple-domain features. Ultrasound Med Biol.. Vol 38 (Issue 2)
    • Shan, J. (2010). Automated breast cancer detection and classification using ultrasound images: a survey. Pattern Recognition.
    • Shan, J. (2010). Completely automatic segmentation for breast ultrasound using multiple-domain features.

    PRESENTATIONS

    • Shan, J. (2014, May 21). The 2014 International Conference on Collaboration Technologies and Systems (CTS 2014). A similarity measurement of clinical trials using snomed - a preliminary study. IEEE, ACM, IFIP, Minneapolis, MN
    • Shan, J. (2014, May 20). The 2014 International Conference on Collaboration Technologies and Systems (CTS 2014). A new scheme to evaluate the accuracy of knowledge representation in automated breast cancer diagnosis. IEEE, ACM, IFIP, Minneapolis, MN
    • Shan, J. (2013, October 05). Pace DPS seminar. Telehealth and computer-aided diagnosis for breast cancer. Seidenberg School of CSIS, Graduate Center

    Department Service

    • Computer Science Curriculum Committee [Committee Member]
    • CIS101 Review Committee [Committee Member]

    College Service

    • DPS Dissertation Committee [Committee Member]
      Desc: Reading the dissertation, making suggestions for changes and improvements, and sitting in on the defense.
      Committee's Key Accomplishments: Have served in the committee for following DPS students: Steve Kim (09/2013), Ned Bakelman(05/2014), Dmitry Nikelshpur(05/2014), and Jonathan Leet(12/2014).
    • Faculty Search Committee [Committee Member]
      Desc: Search new faculty members for Seidenberg School of Computer Science and Information Systems.

    PROFESSIONAL Service

    • The 2014 International Conference on Collaboration Technologies and Systems [Session Chair]
      Desc: As the co-chair of workshop on Knowledge Management and Collaboration (KMC 2014), my responsibilities include finalizing the panel committee, helping disseminate call-for-paper, organizing reviews, making acceptance decisions, arranging the final workshop program, etc.