Sharon Xiaolei Huang

Professor

Sharon Xiaolei Huang

Most Recent Publications

Zebrafish Histotomography Noise Removal in Projection and Reconstruction Domains

Amogh Subbakrishna Adishesha, Daniel Vanselow, Patrick La Riviere, Sharon Xiaolei Huang, Keith Cheng, on p. 140-144

Guo Ye Yang, George Kiyohiro Nakayama, Zi Kai Xiao, Tai Jiang Mu, Xiaolei Huang, Shi Min Hu, 2024, Proceedings of the AAAI Conference on Artificial Intelligence on p. 6486-6493

Haomiao Ni, Jiachen Liu, Yuan Xue, Sharon X. Huang, 2024, on p. 4942-4952

Amogh Subbakrishna Adishesha, Daniel J. Vanselow, Patrick La Riviere, Keith C. Cheng, Sharon X. Huang, 2023, Computer Methods and Programs in Biomedicine

AI Chatbots in Clinical Laboratory Medicine: Foundations and Trends

He S. Yang, Fei Wang, Matthew B. Greenblatt, Sharon X. Huang, Yi Zhang, 2023, Clinical Chemistry on p. 1238-1246

ABSLearn: a GNN-based framework for aliasing and buffer-size information retrieval

Ke Liang, Jim Tan, Dongrui Zeng, Yongzhe Huang, Xiaolei Huang, Gang Tan, 2023, Pattern Analysis and Applications on p. 1171-1189

Yanglan Ou, Sharon X. Huang, Kelvin K. Wong, Jonathon Cummock, John Volpi, James Z. Wang, Stephen T.C. Wong, 2023, Computerized Medical Imaging and Graphics

Amogh Subbakrishna Adishesha, Lily Jakielaszek, Fariha Azhar, Peixuan Zhang, Vasant Honavar, Fenglong Ma, Chandra Belani, Prasenjit Mitra, Sharon Xiaolei Huang, 2023, IEEE Journal of Biomedical and Health Informatics on p. 3645-3656

Editorial for special issue on explainable and generalizable deep learning methods for medical image computing

Guotai Wang, Shaoting Zhang, Xiaolei Huang, Tom Vercauteren, Dimitris Metaxas, 2023, Medical Image Analysis

Haomiao Ni, Yihao Liu, Sharon X. Huang, Yuan Xue, 2023, on p. 412-422

Most-Cited Papers

Ming Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Philip H.S. Torr, Shi Min Hu, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence on p. 569-582

Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris Metaxas, 2017, on p. 5908-5916

Tao Xu, Pengchuan Zhang, Qiuyuan Huang, Han Zhang, Zhe Gan, Xiaolei Huang, Xiaodong He, 2018, on p. 1316-1324

Traffic-Sign Detection and Classification in the Wild

Zhe Zhu, Dun Liang, Songhai Zhang, Xiaolei Huang, Baoli Li, Shimin Hu, 2016, on p. 2110-2118

Han Zhang, Tao Xu, Hongsheng Li, Shaoting Zhang, Xiaogang Wang, Xiaolei Huang, Dimitris N. Metaxas, 2019, IEEE Transactions on Pattern Analysis and Machine Intelligence on p. 1947-1962

Yuan Xue, Tao Xu, Han Zhang, L. Rodney Long, Xiaolei Huang, 2018, Neuroinformatics on p. 383-392

SPDA-CNN: Unifying semantic part detection and abstraction for fine-grained recognition

Han Zhang, Tao Xu, Mohamed Elhoseiny, Xiaolei Huang, Shaoting Zhang, Ahmed Elgammal, Dimitris Metaxas, 2016, on p. 1143-1152

Ming Ming Cheng, Niloy J. Mitra, Xiaolei Huang, Shi Min Hu, 2014, Visual Computer on p. 443-453

Zhong Hui Shen, Jian Jun Wang, Jian Yong Jiang, Sharon X. Huang, Yuan Hua Lin, Ce Wen Nan, Long Qing Chen, Yang Shen, 2019, Nature Communications

Multimodal deep learning for cervical dysplasia diagnosis

Tao Xu, Han Zhang, Xiaolei Huang, Shaoting Zhang, Dimitris N. Metaxas, 2016, on p. 115-123

News Articles Featuring Sharon Xiaolei Huang

College of IST awards seed grants to 8 projects

The Penn State College of Information Sciences and Technology recently announced eight projects that will receive funding from the college’s seed grant program.

Researchers to use $1.2 million grant to study early Alzheimer’s detection

A team of Penn State-led researchers received a $1.2 million grant from the National Institutes of Health to help fund a project to develop a machine learning system for early Alzheimer’s disease detection. Alzheimer’s disease, a neurological condition and the most common form of dementia, affects nearly 6 million Americans, according to the Centers for Disease Control and Prevention.

Podcast unpacks interdisciplinary team’s rapid new virus diagnostics

The latest episode of The Symbiotic Podcast welcomes its largest-ever crew of guests, collaborators from a multi-disciplinary, multi-institution team that came together via video conference to talk about their work on a newly developed rapid diagnostic tool for COVID-19 and other viruses.

Penn State receives five-year $3.7 million grant to study virus evolution

The evolution of viruses will be the focus of a five-year $3.7 million dollar grant from the National Science Foundation’s new program on convergence research, to an interdisciplinary team led by Penn State. The grant is in two phases, depending on successful completion of phase one milestones.