Sharon Huang

Email: suh972@psu.edu

Phone: (814) 863-7235

Office Address:
E317 Westgate Building

Title: Associate Professor

Website:

Research Areas:
Computer Science
Materials Science & Engineering
Petroleum & Natural Gas Engineering

Education Background:
• Tsinghua University, Beijing, China, Computer Science, BE, 1999
• Rutgers University, New Brunswick, NJ, Computer Science, MS, 2001
• Rutgers University, New Brunswick, NJ, Computer Science, PhD, 2006

About:

Huang is an associate professor in information sciences and technology. She began at Penn State in 2018. Huang received her B.Eng. in computer science from Tsinghua University in China, and her M.S. and Ph.D. in computer science from Rutgers University. Her research interests are in the areas of image data analysis, computer vision, and machine learning, focusing on methods for object recognition, image segmentation, image synthesis, registration/ matching, tracking, skeletonization, computer-assisted diagnosis and intervention. Her broader interests include computer graphics, artificial intelligence, data visualization, data mining, biomedical informatics, and human-computer interaction.

Research Interests:

• Biomedical image data analysis
• Computer vision
• Machine learning
• Computer graphics and visualization
• Data mining

Memberships & Committees:

• Member of IEEE

Honors & Awards:

• Outstanding Reviewer Award, by Computers in Biology and Medicine (CBM) journal, 2015
• P.C. Rossin Assistant Professorship, Lehigh University, 2009
• Minority Junior Faculty Award for Career Enhancement, Christian R. and Mary F. Lindback Foundation, 2007

Teaching:

• IST 210: Organization of Data, Fall 2018
• IST 597: Machine Learning Methods in Biomedical Image Informatics, Spring 2019

Publications:

Elsevier: https://pennstate.pure.elsevier.com/en/persons/sharon-xiaolei-huang/publications/

Sharon Huang's Publications
Record 1 - 10 of 11 View All
Ma, Y., T. Xu, X. Huang, X. Wang, C. Li, J. Jerwick, Y. Ning, X. Zeng, B. Wang, Y. Wang, Z. Zhang, X. Zhang, and C. Zhou, (2019). Computer-Aided Diagnosis of Label-Free 3D Optical Coherence Microscopy Images of Human Cervical Tissue, IEEE Trans. on Biomedical Engineering.
Shen, Z. H., J. Wang, J. Y. Jiang, S. X. Huang, Y. H. Lin, C. W. Nan, L. Chen, and Y. Shen, (2019). Phase-field modeling and machine learning of electric-thermal-mechanical breakdown of polymer-based dielectrics, In Nature Communications, Vol. 10, No. 1, p. 1843.
Xu, T., C. Langouras, M. A. Koudehi, B. E. Vos, N. Wang, G. H. Koenderink, X. Huang, and D. Vavylonis, (2019). Automated Tracking of Biopolymer Growth and Network Deformation with TSOAX, In Scientific Reports, 9(1), p. 1717.
Xue, Y., and X. Huang, (2019). Improved Disease Classication in Chest X-rays with Transferred Features from Report Generation, Proc. of International Conf. on Information Processing in Medical Imaging (IPMI).
Zhang, Q., Y. Xue, and X. Huang, (2019). Online Training Strategies for Body Part Segmentation in Infant Movement Videos, Proc. of the IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro (ISBI).
Xu, T., P. Zhang, Q. Huang, H. Zhang, Z. Gan, X. Huang, and X. He, (2018). AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks, Proc. Of IEEE Conf. on Computer Vision and Pattern Recognition (CVPR).
Xue, Y., T. Xu, and X. Huang, (2018). Adversarial Learning with Multi-Scale Loss for Skin Lesion Segmentation, Proc. of the IEEE Int'l Symposium on Biomedical Imaging: From Nano to Macro (ISBI).
Xue, Y., T. Xu, H. Zhang, L. R. Long, and X. Huang, (2018). SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation, Neuroinformatics, 16(3-4):383-392.
Xue, Y., T. Xu, L. R. Long, Z. Xue, S. Antani, G. R. Thoma, and X. Huang, (2018). Multimodal Recurrent Model with Attention for Automated Radiology Report Generation, Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 457-466.
Yao, J., Z. Xu, X. Huang, and J. Huang, (2018). An ecient algorithm for dynamic MRI using low-rank and total variation regularizations, Medical Image Analysis, Vol. 44, pp. 14-27.
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