Our Faculty

Juan Shan

Assistant Professor

Seidenberg School of CSIS

Computer Science NY

Location
  • @New York City
Office Hours
New York City

Tue 1:30pm-5:00pm

Thu 3:30pm-5:00pm

Biography


Dr. Shan joined Pace University in August 2013. She is currently an assistant professor in the Department of Computer Science. Prior to joining Pace, she was an assistant professor in Department of Mathematics and Computer Science at Benedictine College from 2011 to 2013. Her primary research interest is medical image processing and computer-aided diagnosis.

Education


PhD , Utah State University , Logan, UT , 2011
Computer Science

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

Awards and Honors

  • Pace University, June 2016 - Kenan Award
  • Pace University, April 2014 - Research Day 2014 Awardee
  • Intermountain Graduate Research Symposium, April 2011 - First Place Research Paper
  • Graduate Student Senate, Utah State University, June 2010 - Enhancement Awards
  • Utah State University, January 2006 - Honor Roll of Graduate School

Publications


Li, L. & Shan, J. Automated Microaneurysm Detection in Fundus Images through Region Growing.

Du, Y. & Shan, J. Knee Osteoarthritis Prediction on MR Images Using Cartilage Damage Index and Machine Learning Methods. http://muii.missouri.edu/bibm2017/

Cao, W. & Czarnek, N. Microaneurysm Detection in Fundus Images by Small Image Patches and Machine Learning Methods. http://muii.missouri.edu/bibm2017/

Li, L. & Shan, J. (2017, February). Automated Microaneurysm Detection in Fundus Images by Region Growing.

Mukaddim, R. A., Shan, J., Kabir, I., Ashik, A., Abid, R., Yan, Z., Metaxas, D., Garra, B., Islam, K. & Alam, S. (2016, December). A Novel and Robust Automatic Seed Point Selection Method for Breast Ultrasound Images.

Shan, J. & Li, L. (2016, June). A Deep Learning Method for Microaneurysm Detection in Fundus Images.

Butt, N. & Shan, J. (2016, June). CyberCare: A Novel Electronic Health Record Management System.

Shan, J., Alam, K., Garra, B., Zhang, Y. & Ahmed, T. (2016, January (1st Quarter/Winter)). Computer-aided Diagnosis for Breast Ultrasound Using Computerized BI-RADS Features and Machine Learning Methods. Ultrasound in Medicine and Biology (UMB). Vol 42 (Issue 4) , pages 980-988.

Shan, J. (2014, December). 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. (2014, May). A New Scheme to Evaluate the Accuracy of Knowledge Representation in Automated Breast Cancer Diagnosis. http://cts2014.cisedu.info/

PRESENTATIONS


Shan, J. (2016, June 28). The First IEEE Conference on Connected health: Applications, Systems and Engineering Technologies. A Deep Learning Method for Microaneurysm Detection in Fundus Images. IEEE, Washington D.C.

Butt, N. (2016, June 28). The First IEEE Conference on Connected health: Applications, Systems and Engineering Technologies. CyberCare: A Novel Electronic Health Record Management System.

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

RESEARCH INTEREST


Dr. Shan's research interests include machine learning, medical image processing, and computer-aided diagnosis (CAD) systems. Her primary focus is developing robust and efficient CAD algorithms to help doctors analyzing medical images, discovering distinguishing features, and classifying data utilizing machine learning methods. Her on-going research projects include CAD systems for breast cancer, diabetic retinopathy, and knee osteoarthritis.

Grants, Sponsored Research and Contracts

Shan, J. (2017, September 15). PI. A Novel 3D Image Predictive Model for Knee Osteoarthritis Disease.
National Science Foundation , Federal , $208,107.00 . Funded,

Shan, J. (2017, September). Co-PI, DAISEC: Data Analytics in Cybersecurity.
National Security Agency , Federal , $188,564.98 . Funded,

Chen, L., Genc, Y. & Shan, J. (2017, September). DAISEC: Data Analytics in Cybersecuirty.
National Security Agency , Federal , $188,564.98 . Funded,

Shan, J. (2017, January). Innovation Grant.
2017 , Pace University . Funded,

Shan, J. (2016, November). Scholarly Research Committee Grant.
Pace University , Pace University . Funded,

Shan, J. (2017, April). CRA-W Distinguished Lecture Series at Pace University -- Workshop on Deep Learning.
Computing Research Association -Women (CRA-W) , Other . Funded,

PROFESSIONAL MEMBERSHIPS

  • IEEE membership 2010
  • IEEE Women in Engineering 2011

COLLEGE SERVICE

  • Editorial Board Member of Seidenberg School Technical Report Series [Committee Member]
  • Computer Science Curriculum Committee [Committee Member]
  • DPS Dissertation Committee [Committee Member]
  • Computer Science Curriculum Committee [Committee Chair]
  • Faculty Search Committee [Committee Member]

UNIVERSITY SERVICE

  • CIS101 Review Committee [Committee Member]
    Desc: Work with colleagues from other schools to modify and redesign the course CIS101.
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