Hao Zheng 郑昊

I am currently an Assistant Professor at the School of Computing and Informatics of University of Louisiana at Lafayette. Previously, I was a postdoctoral researcher at the Center for Biomedical Image Computing and Analytics (CBICA) of University of Pennsylvania. I obtained my Ph.D. from University of Notre Dame, and my B.Sc. from University of Science and Technology of China.

My primary research lies in artificial intelligence for biomedical data analysis and scientific visualization, including both methodology development and real-world biomedical applications. Specifically, my current research interests are: (1) Computer Vision (e.g., registration, segmentation, classification, detection, synthesis, imaging); (2) Machine Learning for Multi-Modal Data Analysis (e.g., image, text, omics); (3) Trustworthy and Robust AI for Healthcare (e.g., explainability, generalizability); (4) Data-Efficient Machine Learning (e.g., efficient annotation, semi-supervised learning, transfer learning, foundation models).

I am constantly looking for highly motivated students and interns to join my lab! Please read this note for prospective students and review my research page first. Due to the limited openings and high volume of inquiries I receive, I may not be able to reply to every email. Please understand that this limitation does not reflect your qualifications or potential.
✨ Prospective Ph.D. Students (Spring/Fall 2025): Fully funded RA/TA positions. Please send me an email with the title [PhD Application-25Spring/Fall] and attach your 1) CV, 2) transcripts for both undergrad and master's (if applicable), 3) TOFEL/GRE scores (if applicable), and 4) representative publications (optional). More information for formal application can be found on the Graduate School Application Page.
✨ Prospective Interns/Visiting Students (all year): Please send me an email with the title [Intern/Visiting PrefferedTime] and your CV and transcripts.
✨ Current ULL Students: For Undergraduate Students looking for research projects, please send me your resume or take my courses. For Graduate Students looking for mentors, please contact me by email with your CV and a brief note on how our interests might overlap.

Teaching

• Fall 2024: CMPS 320, Introduction to Artificial Intelligence and Machine Learning

Recent and selected publications

Enhancing Whole Slide Image Classification with Discriminative and Contrastive Learning. PDF
Peixian Liang, Hao Zheng, Hongming Li, Yuxin Gong, Yong Fan.
International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024

Versatile Medical Image Segmentation Learned from Multi-Source Datasets via Model Self-Disambiguation. PDF
Xiaoyang Chen, Hao Zheng, Yuemeng Li, Yuncong Ma, Liang Ma, Hongming Li, Yong Fan.
IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2024

KD-INR: Time-Varying Volumetric Data Compression via Knowledge Distillation-based Implicit Neural Representation. PDF
Jun Han, Hao Zheng, Chongke Bi.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2024

Coupled Reconstruction of Cortical Surfaces by Diffeomorphic Mesh Deformation. PDF
Hao Zheng, Hongming Li, Yong Fan.
Neural Information Processing Systems (NeurIPS), 2023

SurfNN: Joint Multiple Cortical Surfaces Reconstruction from 3D Brain MRIs. PDF
Hao Zheng, Hongming Li, Yong Fan.
IEEE International Symposium on Biomedical Imaging (ISBI), 2023

KCB-Net: A 3D Knee Cartilage and Bone Segmentation Network via Sparse Annotation. PDF
Yaopeng Peng, Hao Zheng, Peixian Liang, Lichun Zhang, Fahim Zaman, Xiaodong Wu, Milan Sonka, Danny Z. Chen.
Medical Image Analysis (MIA), 2022

A Dysmorphic Mouse Model Reveals Developmental Interactions of Chondrocranium and Dermatocranium. PDF
Susan M. Motch Perrine, M. Kathleen Pitirri, Emily L. Durham, Mizuho Kawasaki, Hao Zheng, Danny Z. Chen, Kazuhiko Kawasaki, Joan T. Richtsmeier.
eLife, 2022

Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models. PDF
Yizhe Zhang, Suraj Mishra, Peixian Liang, Hao Zheng, Danny Z. Chen.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2022

CMC-Net: 3D Calf Muscle Compartment Segmentation with Sparse Annotation. PDF
Yaopeng Peng, Hao Zheng, Lichun Zhang, Milan Sonka, Danny Z. Chen.
Medical Image Analysis (MIA), 2022

TANGO: A GO-term Embedding Based Method for Protein Semantic Similarity Prediction. PDF
Hongxiao Wang, Hao Zheng, Danny Z. Chen.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), 2022

STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes. PDF
Jun Han, Hao Zheng, Danny Z. Chen, Chaoli Wang.
IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2021), 2022

Selected publications before 2022

Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation. PDF
Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2021

[Student Travel Award]

kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation. PDF
Pengfei Gu, Hao Zheng, Yizhe Zhang, Chaoli Wang, Danny Z. Chen.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2021

V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data. PDF
Jun Han, Hao Zheng, Yunhao Xing, Danny Z. Chen, Chaoli Wang.
IEEE Transactions on Visualization and Computer Graphics (IEEE SciVis 2020), 2021

Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation. PDF
Hongxiao Wang, Hao Zheng, Jianxu Chen, Lin Yang, Danny Z. Chen.
IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2020

Cartilage Segmentation in High-Resolution 3D Micro-CT Images via Uncertainty-Guided Self-Training with Very Sparse Annotation. PDF
Hao Zheng, Susan M. Motch Perrine, M. Kathleen Pitirri, Kazuhiko Kawasaki, Chaoli Wang, Joan T. Richtsmeier, Danny Z. Chen.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2020

An Annotation Sparsification Strategy for 3D Medical Image Segmentation via Representative Selection and Self-Training. PDF
Hao Zheng, Yizhe Zhang, Lin Yang, Chaoli Wang, Danny Z. Chen.
AAAI Conference on Artificial Intelligence (AAAI), 2020

[Spotlight]

HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion. PDF
Hao Zheng, Lin Yang, Jun Han, Yizhe Zhang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen.
Medical Image Computing and Computer Assisted Interventions (MICCAI), 2019

SPDA: Superpixel-based Data Augmentation forBiomedical Image Segmentation. PDF
Yizhe Zhang, Lin Yang, Hao Zheng, Peixian Liang, Colleen Mangold, Raquel G. Loreto, David P. Hughes, Danny Z. Chen.
Medical Imaging with Deep Learning (MIDL), 2019

[Oral]

Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation. PDF
Peixian Liang, Jianxu Chen, Hao Zheng, Lin Yang, Yizhe Zhang, Danny Z. Chen.
IEEE International Symposium on Biomedical Imaging (ISBI), 2019

[Oral]

A New Ensemble Learning Framework for 3D Biomedical Image Segmentation. PDF
Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen.
AAAI Conference on Artificial Intelligence (AAAI), 2019

[Oral]

Biomedical Image Segmentation via Representative Annotation. PDF
Hao Zheng, Yizhe Zhang, Lin Yang, Chaoli Wang, Danny Z. Chen.
AAAI Conference on Artificial Intelligence (AAAI), 2019

[Oral]

Deep Learning Based Instance Segmentation in 3D Biomedical Images Using Weak Annotation. PDF
Zhuo Zhao, Lin Yang, Hao Zheng, Ian H Guldner, Siyuan Zhang, Danny Z Chen
Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2018

full list