About Me
I'm Saiyang Na, a Computer Science Ph.D. candidate supervised by Dr. Junzhou Huang in Computer Science Department at University of Texas at Arlington, USA. I focus on creating open-source libraries with JAX and Python for deep learning and LLM applications.
Research
- Cell Segmentation - Auto-prompt generation pipeline for SAM
- Protein-Protein Interaction - TCR-pMHC binding prediction
- Deep Learning in Hyperbolic Space - MCI classification
- Retrosynthesis - Multi-step retrosynthesis on USPTO dataset
Projects
nadl
A deep learning framework based on JAX and Equinox for building efficient neural networks
jaxrie
A JAX library for hyperbolic neural networks, enabling geometric deep learning in hyperbolic space
naipyext
IPython Extensions with enhanced trace exception handling for better debugging experience
Segment Any Cell Demo
Interactive demo for cell segmentation using SAM-based auto-prompting framework
Skills
Expert: Python, JAX with Equinox, PyTorch, NumPy
Proficient: TensorFlow with Keras, Lisp (Emacs Lisp), LLM
Familiar: Haskell, JavaScript, C/C++
Publications
- Saiyang Na, Junzhou Huang, (2026), "Deep learning for TCR–pMHC binding prediction", Deep Learning in Drug Design, 381-402 Book Chapter DOIhttps://doi.org/10.1016/B978-0-44-332908-1.00029-5Copy
- Saiyang Na, Yuzhi Guo, Feng Jiang, Hehuan Ma, Jian 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 [48 citations] arXivhttps://arxiv.org/abs/2401.13220Copy
- Thao M Dang, Qifeng Zhou, Yuzhi Guo, Hehuan Ma, Saiyang Na, TB Dang, Jian Gao, Junzhou Huang, (2025), "Abnormality-aware multimodal learning for WSI classification", Frontiers in Medicine 12, 1546452 Journal [2 citations] DOIhttps://doi.org/10.3389/fmed.2025.1546452Copy
- Qifeng Zhou, Thao M Dang, Wenliang Zhong, Yuzhi Guo, Hehuan Ma, Saiyang Na, Hao Li, Junzhou Huang, (2025), "MLLM4PUE: Toward Universal Embeddings in Digital Pathology through Multimodal LLMs", arXiv preprint arXiv:2502.07221 Preprint [1 citation] arXivhttps://arxiv.org/abs/2502.07221Copy
- Bing Song, Kaiwen Wang, Saiyang Na, Jingxuan Yao, Fatemeh J Fattah, Amber L Martin, Muhammad 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 DOIhttps://doi.org/10.1038/s43018-025-01001-5Copy
- Qifeng Zhou, Thao M Dang, Yuzhi Guo, Hehuan Ma, Wenliang Zhong, Saiyang Na, Jian 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 IEEEhttps://ieeexplore.ieee.org/abstract/document/10981180Copy
- Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenliang Zhong, Yikang 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 [18 citations] Articlehttps://academic.oup.com/bib/article/25/4/bbae343/7713742Copy
- Feng Jiang, Yuzhi Guo, Hehuan Ma, Saiyang Na, Wenjie An, Bing Song, Yikang Han, Jian 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 [7 citations] ACM DLhttps://dl.acm.org/doi/10.1145/3698587.3701389Copy
- Thao M Dang, Yuzhi Guo, Hehuan Ma, Qifeng Zhou, Saiyang Na, Jian 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 [4 citations] ACM DLhttps://dl.acm.org/doi/10.1145/3698587.3701372Copy
- Bing Song, Kaiwen Wang, Saiyang Na, Jingxuan Yao, Fatemeh J Fattah, Muhammad S von Itzstein, David M Yang, Jialiang Liu et al., (2024), "Cmai: Predicting Antigen-Antibody Interactions from Massive Sequencing Data", bioRxiv Preprint [2 citations] bioRxivhttps://www.biorxiv.org/content/10.1101/2024.06.27.601035v2Copy
- Bing Song, Kaiwen Wang, Saiyang Na, Jingxuan Yao, Fatemeh J Fattah, Muhammad S von Itzstein, David 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 bioRxivhttps://www.biorxiv.org/content/10.1101/2024.06.27.601035v2Copy
- 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 [11 citations] Springerhttps://link.springer.com/chapter/10.1007/978-3-031-43904-9_65Copy
- Xinyue Ye, Jiaxin Du, Xi Gong, Saiyang Na, Wangjun Li, Shwetha 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