Nasy

1. 01

   Computational RNA design

   RNA inverse folding and machine-learning methods for modeling mRNA translational efficiency.

2. 02

   Computational biology

   Protein binding prediction, antibody–antigen modeling, and molecular design systems that connect model performance to biological utility.

3. 03

   Biomedical foundation models

   Fine-tuning and prompting strategies that adapt general visual models to microscopy, pathology, and other biomedical data.

4. 04

   Geometric multimodal learning

   Hyperbolic geometry and multimodal alignment for representation learning across images, text, video, and clinical signals.

No publications match these filters.

1. Saiyang Na, Feng Jiang, Qifeng Zhou, Wenliang Zhong, Thao M. Dang, Yuzhi Guo, Hehuan Ma, et al., (2026), "Hyperbolic Gramian Volumes for Multimodal Alignment", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Conference [0 citations] Scholarhttps://scholar.google.com/citations?view_op=view_citation&hl=en&user=rkvOcNEAAAAJ&citation_for_view=rkvOcNEAAAAJ:Se3iqnhoufwCCopyCodehttps://github.com/uta-smile/HyperGramCopy
2. Saiyang Na, (2026), "Multimodal Deep Learning for Biological Data Understanding", Ph.D. Dissertation, University of Texas at Arlington Dissertation [0 citations] Scholarhttps://scholar.google.com/citations?view_op=view_citation&hl=en&user=rkvOcNEAAAAJ&citation_for_view=rkvOcNEAAAAJ:roLk4NBRz8UCCopy
3. Saiyang Na, Junzhou Huang, (2026), "Deep learning for TCR–pMHC binding prediction", Deep Learning in Drug Design, 381-402 Book Chapter [0 citations] DOIhttps://doi.org/10.1016/B978-0-44-332908-1.00029-5Copy
4. Saiyang Na, Yuzhi Guo, Feng Jiang, Hehuan Ma, Jean Gao, Junzhou Huang, (2025), "Segment any cell: A sam-based auto-prompting fine-tuning framework for nuclei segmentation", IEEE Transactions on Neural Networks and Learning Systems Journal [76 citations] arXivhttps://arxiv.org/abs/2401.13220Copy
5. Thao M. Dang, Qifeng Zhou, Yuzhi Guo, Hehuan Ma, Saiyang Na, Thao Bich Dang, Jean Gao, Junzhou Huang, (2025), "Abnormality-aware multimodal learning for WSI classification", Frontiers in Medicine 12, 1546452 Journal [10 citations] DOIhttps://doi.org/10.3389/fmed.2025.1546452Copy
6. Qifeng Zhou, Wenliang Zhong, Thao M. Dang, Hehuan Ma, Saiyang Na, Yuzhi Guo, Junzhou Huang, (2025), "HOMIE: Histopathology Omni-modal Embedding for Pathology Composed Retrieval", arXiv preprint arXiv:2502.07221 Preprint [4 citations] arXivhttps://arxiv.org/abs/2502.07221Copy
7. Bing Song, Kaiwen Wang, Saiyang Na, Jia Yao, Farjana J. Fattah, Alexandra L. Martin, Mitchell S. von Itzstein, et al., (2025), "Profiling antigen-binding affinity of B cell repertoires in tumors by deep learning predicts immune-checkpoint inhibitor treatment outcomes", Nature Cancer 6, 1570-1584 Journal [5 citations] DOIhttps://doi.org/10.1038/s43018-025-01001-5Copy
8. Qifeng Zhou, Thao M. Dang, Yuzhi Guo, Hehuan Ma, Wenliang Zhong, Saiyang Na, Jean Gao, Junzhou Huang, (2025), "Contrastive Pretraining for Computational Pathology with Visual-Language Models", 2025 IEEE 22nd International Symposium on Biomedical Imaging (ISBI), 1-4 Conference [3 citations] IEEEhttps://ieeexplore.ieee.org/abstract/document/10981180Copy
9. Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenliang Zhong, Yi Han, Tao Wang, Junzhou Huang, (2024), "GTE: a graph learning framework for prediction of T-cell receptors and epitopes binding specificity", Briefings in Bioinformatics 25 (4), bbae343 Journal [26 citations] Articlehttps://academic.oup.com/bib/article/25/4/bbae343/7713742Copy
10. Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Weizhi An, Bing Song, Yi Han, Jean Gao, Tao Wang, Junzhou Huang, (2024), "AlphaEpi: Enhancing B Cell Epitope Prediction with AlphaFold 3", Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics Conference [11 citations] ACM DLhttps://dl.acm.org/doi/10.1145/3698587.3701389Copy
11. Thao M. Dang, Yuzhi Guo, Hehuan Ma, Qifeng Zhou, Saiyang Na, Jean Gao, Junzhou Huang, (2024), "MFMF: multiple foundation model fusion networks for whole slide image classification", Proceedings of the 15th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics Conference [8 citations] ACM DLhttps://dl.acm.org/doi/10.1145/3698587.3701372Copy
12. Bing Song, Kaiwen Wang, Saiyang Na, Jia Yao, Farjana J. Fattah, Mitchell S. von Itzstein, Donghan M. Yang, Jialiang Liu et al., (2024), "Cmai: Predicting Antigen-Antibody Interactions from Massive Sequencing Data", bioRxiv Preprint [1 citation] bioRxivhttps://www.biorxiv.org/content/10.1101/2024.06.27.601035v2Copy
13. Bing Song, Kaiwen Wang, Saiyang Na, Jia Yao, Farjana J. Fattah, Mitchell S. von Itzstein, Donghan M. Yang, Jialiang Liu et al., (2024), "An Artificial Intelligence Model for Profiling the Landscape of Antigen-binding Affinities of Massive BCR Sequencing Data", bioRxiv, 2024.06.27.601035 Preprint [0 citations] bioRxivhttps://www.biorxiv.org/content/10.1101/2024.06.27.601035v2Copy
14. Lu Zhang, Saiyang Na, Tianming Liu, Dajiang Zhu, Junzhou Huang, (2023), "Multimodal deep fusion in hyperbolic space for mild cognitive impairment study", International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) Conference [14 citations] Springerhttps://link.springer.com/chapter/10.1007/978-3-031-43904-9_65Copy
15. Xinyue Ye, Jiaxin Du, Xi Gong, Saiyang Na, Weimin Li, Sonali Kudva, (2021), "Geospatial and semantic mapping platform for massive COVID-19 scientific publication search", Journal of Geovisualization and Spatial Analysis 5 (1), 5 Journal [24 citations] DOIhttps://doi.org/10.1007/s41651-021-00073-yCopy