Curriculum Vitae (PDF)

Sharon X. Huang

Professor
College of Information Sciences and Technology
Huck Institutes of the Life Sciences
Penn State University
University Park, PA 16802

413G Eric J. Barron Innovation Hub
suh972 AT psu.edu
(814) 863-7235 (Phone)

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Brief Bio:


Sharon Xiaolei Huang received her B.E. degree in Computer Science from Tsinghua University, China, and her M.S. and Ph.D. degrees in Computer Science from Rutgers University. She is currently a Professor in the College of Information Sciences and Technology and a member of the Huck Institutes of the Life Sciences at the Penn State University, University Park, PA. Her research interests are in the areas of biomedical image analysis, computer vision, and machine learning, focusing on methods for object recognition, image and video segmentation, image and video synthesis, computer-assisted diagnosis and intervention, registration/matching, and motion tracking. Her broader interests include AI for medicine, data science for healthcare, biomedical informatics, computer graphics, visualization, and human-computer interaction. She regularly serves on the program committees of major conferences in medical image computing and computer vision and is an associate editor for several journals including Medical Image Analysis, Computer Vision and Image Understanding, Computerized Medical Imaging and Graphics. In the College of IST, she currently serves as the program coordinator of Applied Data Sciences.

Courses:

Fall 2022: Introduction to Data Sciences (DS 200)
Spring 2022: Algorithmic Methods and Tools (DS 305)
Fall 2021: Visual Analytics for Data Sciences (DS 330)
Spring 2021: Machine Learning in Healthcare (IST 597)
Fall 2020: Data Management for Data Sciences (DS 220)
Spring 2019: Machine Learning Methods in Biomedical Image Informatics (IST 597)
Fall 2018: Organization of Data (IST 210)


Research:

I am a computer scientist who is curious about how human brain, eye, body, and cell, function. Hence I am always excited about developing robust image analysis methods and building autonomous and intelligent systems that integrate algorithms with efficient, application-specific designs to solve computational problems in biomedicine, perception, and cognition. In particular, I work toward robust medical imaging software based on computer vision and machine learning algorithms that aid medical doctors in accurate and reproducible diagnosis, and help them better understand the anatomical and physiological relationships in normal and diseased states. I develop image processing and analysis software for analyzing biological images to help biologists and biophysicists in understanding and modeling complex biological pathways and systems. I also create intelligent vision systems that are capable of learning effectively and reasoning about multiple sources of information in order to achieve functions typical of human vision.

Selected Recent Publications: (See Google Scholar Profile for all publications)

H. Ni, Y. Xue, L. Ma, Q. Zhang, X. Li, S.X. Huang, ``Semi-supervised Body Parsing and Pose Estimation for Enhancing Infant General Movement Assessment," In Medical Image Analysis, Vol. 83, 2023.

H. Ni, Y. Xue, K. Wong, J. Volpi, S. TC Wong, J.Z. Wang, X. Huang, ``Asymmetry Disentanglement Network for Interpretable Acute Ischemic Stroke Infarct Segmentation in Non-Contrast CT Scans," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. [code]

Y. Ou, Y. Yuan, X. Huang, S. TC Wong, J. Volpi, J.Z. Wang, K. Wong, ``Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2022. [code]

J. Liu, Y. Xue, J. Duarte, K. Shekhawat, Z. Zhou, X. Huang, ``End-to-end Graph-constrained Vectorized Floorplan Generation with Panoptic Refinement," In Proc. of the European Conference on Computer Vision (ECCV), 2022.

J. Ye, Y.-T. Yeh, Y. Xue, Z. Wang, N. Zhang, L. He, K. Zhang, R. Ricker, Z. Yu, A. Roder, N.P. Lopez, L. Organtini, W. Greene, S. Hafenstein, H. Lu, E. Ghedin, M. Terrones, S. Huang, S.X. Huang, ``Accurate virus identification with interpretable Raman signatures by machine learning," In The Proceedings of the National Academy of Sciences (PNAS), 2022. [code]

T. Cai, H. Ni, M. Yu, X. Huang, K. Wong, J. Volpi, J. Z. Wang, S. TC Wong, ``DeepStroke: An Efficient Stroke Screening Framework for Emergency Rooms with Multimodal Adversarial Deep Learning," In Medical Image Analysis, Vol. 80, 2022.

F. Yang, X. Huang, Z. Zhou, ``Deep Depth from Focus with Differential Focus Volume," In Proc. Of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. [code]

J. Liu, P. Ji, N. Bansal, C. Cai, Q. Yan, X. Huang, Y. Xu, ``PlaneMVS: 3D Plane Reconstruction from Multi-View Stereo," In Proc. Of IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022.

P. Jin, X. Zhang, Y. Chen, S.X. Huang, Z. Liu, Y. Lin, ``Unsupervised learning of full-waveform inversion: Connecting CNN and partial differential equation in a loop," In Proc. Of International Conference on Learning Representations (ICLR), 2022.

J. Ye, Y. Xue, P. Liu, K.C. Cheng, R. Zaino, X. Huang, ``A Multi-attribute Controllable Generative Model for Histopathology Image Synthesis," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [code]

Y. Ou, Y. Yuan, X. Huang, K. Wong, J. Volpi, J. Z. Wang, S. T.C. Wong, ``LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-weighted MR Images," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021. [code]

Y. Xue, J. Ye, Q. Zhou, L.R. Long, S. Antani, Z. Xue, C. Cornwell, R. Zaino, K.C. Cheng, X. Huang, ``Selective Synthetic Augmentation with HistoGAN for Improved Histopathology Image Classification," In Medical Image Analysis, 2021.

Y. Xue, Y.C. Guo, H. Zhang, T. Xu, S.H. Zhang, X. Huang, ``Deep Image Synthesis from Intuitive User Input: A Review and Perspectives," In Computational Visual Media, 8(1):3-31, 2022.

J. Ye, Y. Xue, L.R. Long, S. Antani, Z. Xue, K. Cheng, X. Huang, ``Synthetic Sample Selection via Reinforcement Learning," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.

H. Ni, Y. Xue, Q. Zhang, X. Huang, ``SiamParseNet: Joint Body Parsing and Label Propagation in Infant Movement Videos," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.

M. Yu, T. Cai, X. Huang, K. Wong, J. Volpi, J.Z. Wang, S. TC Wong, ``Toward Rapid Stroke Diagnosis with Multimodal Deep Learning," In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2020.

Y. Xue, Z. Zhou, X. Huang, ``Neural Wireframe Renderer: Learning Wireframe to Image Translations," In Proc. of the European Conference on Computer Vision (ECCV), 2020. [code]

S. Wang, Y. Zhou, X. Qin, S. Nair, X. Huang, Y. Liu, ``Label-free detection of rare circulating tumor cells by image analysis and machine learning," In Scientific Reports, 10(1), 2020.

Y. Xue, H. Tang, Z. Qiao, G. Gong, Y. Yin, Z. Qian, C. Huang, W. Fan, X. Huang, ``Shape-Aware Organ Segmentation by Predicting Signed Distance Maps," In Proc. of 34th AAAI Conference on Artificial Intelligence (AAAI), 2020.

Y. Xue, Q. Zhou, J. Ye, L.R. Long, S. Antani, C. Cornwell, Z. Xue, X. Huang, ``Synthetic Augmentation and Feature-based Filtering for Improved Cervical Histopathology Image Classification, In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 387-396, 2019.

Y. Xue, X. Huang, ``Improved Disease Classification in Chest X-rays with Transferred Features from Report Generation, In Proc. of International Conf. on Information Processing in Medical Imaging (IPMI), pp. 125-138, 2019.

T. Xu, C. Langouras, M.A. Koudehi, B.E. Vos, N. Wang, G.H. Koenderink, X. Huang, D. Vavylonis, ``Automated Tracking of Biopolymer Growth and Network Deformation with TSOAX, In Scientific Reports, 9(1), p. 1717, 2019. [code]

H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang, D. Metaxas, ``StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks, In IEEE Trans. On Pattern Analysis and Machine Intelligence, 41(8), pp. 1947-1962, 2019. [code]

Z. Shen, J. Wang, J. Jiang, S.X. Huang, Y. Lin, C. Nan, L. Chen, Y. Shen, ``Phase-field Modeling and Machine Learning of Electric-Thermal-Mechanical Breakdown of Polymer-based Dielectrics, In Nature Communications, 2019.

Y. Ma, T. Xu, X. Huang, X. Wang, C. Li, J. Jerwick, Y. Ning, X. Zeng, B. Wang, Y. Wang, Z. Zhang, X. Zhang, C. Zhou, ``Computer-Aided Diagnosis of Label-Free 3D Optical Coherence Microscopy Images of Human Cervical Tissue, In IEEE Trans. on Biomedical Engineering, 2019.

Y. Xue, T. Xu, L.R. Long, Z. Xue, S. Antani, G.R. Thoma, X. Huang, ``Multimodal Recurrent Model with Attention for Automated Radiology Report Generation, In Proc. Of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 457-466, 2018.

T. Xu, P. Zhang, Q. Huang, H. Zhang, Z. Gan, X. Huang, X. He, ``AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks, In Proc. Of IEEE Conf. on Computer Vision and Pattern Recognition, 2018. [code]

Y. Xue, T. Xu, H. Zhang, L. R. Long, and X. Huang, `` SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation, In Neuroinformatics, 16(3-4):383-392, 2018. [code]

J. Yao, Z. Xu, X. Huang, J. Huang, ``An Efficient Algorithm for Dynamic MRI using Low-rank and Total Variation Regularizations," In Medical Image Analysis, Vol. 44, pp. 14-27, 2018.

H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang, D. Metaxas, ``StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networks," In Proc. of International Conf. on Computer Vision, 2017. [code]

S. Wan, H.C. Lee, X. Huang, T. Xu, T. Xu, X. Zeng, Z. Zhang, Y. Sheikine, J.L. Connolly, J.G. Fujimoto, C. Zhou, ``Integrated local binary pattern texture features for classification of breast tissue imaged by Optical Coherence Microscopy,'' In Medical Image Analysis, Vol. 38, pp. 104-116, 2017.

T. Xu, H. Zhang, C. Xin, E. Kim, L.R. Long, Z. Xue, S. Antani, X. Huang, ``Multi-feature based benchmark for cervical dysplasia classification evaluation,'' In Pattern Recognition, Vol. 63, pp. 468-475, 2017.

T. Xu, H. Zhang, X. Huang , S. Zhang, D. Metaxas, ``Multimodal Deep Learning for Cervical Dysplasia Diagnosis,'' In Proc. of International Conf. on Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS Vol. 9901, pp. 115-123, 2016.

H. Zhang, T. Xu, M. Elhoseiny, X. Huang, S. Zhang, A. Elgammal, D. Metaxas, ``SPDA-CNN: Unifying Semantic Part Detection and Abstraction for Fine-Grained Recognition,'' In Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 1143-1152, 2016.

Z. Zhu, D. Liang, S. Zhang, X. Huang, B. Li, S. Hu, ``Traffic-Sign Detection and Classification in the Wild,'' In Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 2110-2118, 2016.

T. Xu, D. Vavylonis, F.C. Tsai, G.H. Koenderink, W. Nie, E. Yusuf, I.J. Lee, J.Q. Wu, X. Huang, ``SOAX: A software for quantification of 3D biopolymer networks," In Scientific Reports, 13;5:9081, 2015. [code]

M. Cheng, N.J. Mitra, X. Huang, P.H.S. Torr, S.M. Hu, ``Global Contrast Based Salient Region Detection," In IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 37(3):569-82, 2015.

D. Song, E. Kim, X. Huang, J. Patruno, H. Munoz-Avila, J. Heflin, L.R. Long, S. Antani, ``Multi-modal Entity Coreference for Cervical Dysplasia Diagnosis," In IEEE Trans. on Medical Imaging (TMI), 34(1):229-45, 2015.

H. Li, X. Huang, J. Huang, S. Zhang, ``Feature Matching with Affine-Function Transformation Models," In IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 36(12):2407-22, 2014.

T. Xu, D. Vavylonis, X. Huang, ``3D Actin Network Centerline Extraction with Multiple Active Contours,'' In Medical Image Analysis, 18(2):272-84, 2014.

M. Cheng, N. J. Mitra, X. Huang, S. M. Hu, ``SalientShape: Group Saliency in Image Collections,'' In Visual Computer, August 2013.

H. Li, X. Huang, L. He, ``Object Matching Using a Locally Affine Invariant and Linear Programming Techniques,'' In IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 35(2):411-24, 2013.

E. Kim, H. Li, X. Huang, ``A Hierarchical Image Clustering Cosegmentation Framework,'' In Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 686-693, 2012.

E. Kim, X. Huang, G. Tan, ``Markup SVG - An Online Content Aware Image Abstraction and Annotation Tool,'' In IEEE Trans. on Multimedia (TMM), 13(5):993-1006, 2011.

T. Shen, H. Li, X. Huang, ``Active Volume Models for Medical Image Segmentation,'' In IEEE Trans. on Medical Imaging (TMI), 30(3):774-791, 2011.

H. Li, T. Shen, X. Huang, ``Approximately Global Optimization for Robust Alignment of Generalized Shapes,'' In IEEE Trans. on Pattern Analysis and Machine Intelligence(TPAMI), 33(6):1116-1131, 2011.

E. Kim, X. Huang, J. Heflin, ``Finding VIPS - A Visual Image Persons Search Using a Content Property Reasoner and Web Ontology,'' In Proc. of IEEE International Conf. on Multimedia & Expo (ICME), 2011.

M. Cheng, G. X. Zhang, N. J. Mitra, X. Huang, S. M. Hu, ``Global Contrast based Salient Region Detection,'' In Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 409-416, 2011.

M. B. Smith, H. Li, T. Shen, X. Huang, E. Yusuf, D. Vavylonis, ``Segmentation and Tracking of Cytoskeletal Filaments using Open Active Contours,'' In Cytoskeleton, 67(11): 693-705, 2010.

M. Cheng, F. L. Zhang, N. J. Mitra, X. Huang, S. M. Hu, ``RepFinder: Finding Approximately Repeated Scene Elements for Image Editing,'' In ACM Trans. on Graphics, Vol. 29, No. 4, 2010. (Presented at SIGGRAPH 2010)

H. Li, E. Kim, X. Huang, L. He, ``Object Matching with a Locally Affine-Invariant Constraint,'' In Proc. of IEEE Computer Society Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 1641-1648, 2010.

J. Huang, X. Huang, D. Metaxas, ``Learning with Dynamic Group Sparsity,'' In Proc. of IEEE International Conf. on Computer Vision (ICCV), pp. 64-71, 2009.


Current Ph.D. Students:

 

Yanglan Ou

Haomiao Ni

Amogh Adishesha

Jiarong (Karen) Ye

Matthew Poska

Peng Jin

Rui Yu

Jiachen Liu



Former Ph.D. students:

 

Fengting Yang -- Now Applied Research Scientist at Meta Reality Lab; co-advised with Z. Zhou

Yuan Xue -- Now Postdoctoral Fellow at Johns Hopkins University

Tao Xu -- Now Research Scientist at Meta (Facebook)

Ting Xu -- Now Research Scientist at Konica Minolta Laboratory
Edward Kim -- Now Associate Professor at Drexel University
Hongsheng Li -- Now Associate Professor at the Chinese University of Hong Kong
Yaoyao Zhu -- Now Senior Software Engineer at Checkpoint Systems
Tian Shen -- Now Principal Research Scientist at Tencent AI Lab