• Deep Learning
  • Computer Vision
  • NLP
• Interdisciplinary collaboration
  • Health team
    • NCKU Institute of Clinical Medicine & Stroke Center
    • Howard University MIL, US
    • NIH/NCBI, US
  • Sports team
    • CrowdEyes project
      • Volleyball (TVL)
      • Basketball (NCKU WBT)
      • ES@NITKC, Japan

• Hsu, C.-H., Hsu, Y.-Y., Chang, B.-M., Raffensperger, K., Kadden, M., Ton, H., Ette, E. A., Lin, S., Brooks, J., Burke, M., Lee, Y.-J., Wang, P., Shoykhet, M., & Tu, T.-W. (2025). StainAI: Quantitative mapping of stained microglia and insights into brain-wide neuroinflammation and therapeutic effects. Communications Biology.
• Islamaj, R., Lai, P.-T., Wei, C.-H., Luo, L., Almeida, T., Jonker, R. A. A., Conceição, S. I. R., Sousa, D. F., Phan, C.-P., Chiang, J.-H., Li, J., Pan, D., Meesawad, W., Tsai, R. T.-H., Sarol, M. J., Hong, G., Valiev, A., Tutubalina, E., Lee, S.-M., Hsu, Y.-Y., ... Lu, Z. (2024). The overview of the BioRED (Biomedical Relation Extraction Dataset) track at BioCreative VIII. Database, 2024. https://doi.org/10.1093/database/bae010
• Hsu, Y.-Y., Clyne, M., Wei, C.-H., Khoury, M. J., & Lu, Z. (2019). Using deep learning to identify translational research in genomic medicine beyond bench to bedside. Database, 2019, baz010. https://doi.org/10.1093/database/baz010
• Gobeill, J., Gaudet, P., Dopp, D., Morrone, A., Kahanda, I., Hsu, Y.-Y., Wei, C.-H., Lu, Z., & Ruch, P. (2018). Overview of the BioCreative VI text-mining services for Kinome Curation Track. Database, 2018, bay104. https://doi.org/10.1093/database/bay104
• Hsu, Y.-Y., Wei, C.-H., & Lu, Z. (2018). Assisting document triage for human kinome curation via machine learning. Database, 2018, bay091. https://doi.org/10.1093/database/bay091
• Lee, H.-C., Hsu, Y.-Y., & Kao, H.-Y. (2016). AuDis: An automatic CRF-enhanced disease normalization in biomedical text. Database, 2016, baw091. https://doi.org/10.1093/database/baw091
• Hsu, Y.-Y., & Kao, H.-Y. (2015). Curatable named-entity recognition using semantic relations. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 12(4), 785–792. https://doi.org/10.1109/TCBB.2014.2366770
• Hsu, Y.-Y., Chen, W.-J., Chen, S.-H., & Kao, H.-Y. (2014). Using hidden Markov models to predict DNA-binding proteins with sequence and structure information. Soft Computing, 18(12), 2365–2376. https://doi.org/10.1007/s00500-013-1210-8
• Hsu, Y.-Y., & Kao, H.-Y. (2013). CoIN: A network analysis for document triage. Database, 2013, bat076. https://doi.org/10.1093/database/bat076
• Hsu, Y.-Y., Chen, H.-Y., & Kao, H.-Y. (2013). Using a search engine-based mutually reinforcing approach to assess the semantic relatedness of biomedical terms. PLoS ONE, 8(11), e77868. https://doi.org/10.1371/journal.pone.0077868
• Sun, K.-T., Wei, C.-H., Hsu, Y.-Y., et al. (2010). On deriving an equation of the mutation rate of the Hepatitis B Virus. Journal of Convergence Information Technology, 5(5), 131–137. https://doi.org/10.4156/jcit.vol5.issue5.15

• Lautan, D., & Hsu, Y.-Y. (2025). Vital-Net: Vision integrated transformer and attention network for lung nodule segmentation on full-scale images. The 17th Asian Conference on Intelligent Information and Database Systems.
• Shih, M.-J., & Hsu, Y.-Y. (2025). Real-time action detection in volleyball matches using DETR architecture. The International Conference on Multimedia Modelling 2025.
• Wu, C.-C., Hsu, C.-H., Wang, P. C., Tu, T.-W., & Hsu, Y.-Y. (2024). Influence of Rician noise on cardiac MR image segmentation using deep learning. In A. Abraham, A. Bajaj, T. Hanne, & P. Siarry (Eds.), Intelligent Systems Design and Applications. ISDA 2023. Lecture Notes in Networks and Systems, vol 1046 (pp. xxx-xxx). Springer, Cham.
• Chung, P.-C., Yang, W.-J., Wu, T.-H., Huang, C.-R., & Hsu, Y.-Y. (2022). Emerging research directions of deep learning for pathology image analysis. IEEE Biomedical Circuits and Systems Conference (BioCAS), Taipei, Taiwan.
• Iwamoto, N., Hsu, Y.-Y., Ohnishi, A., Misaki, Y., Murakami, Y., & Tokunaga, H. (2022). A semi-virtual JetBot racing competition in AI and robotics education. Proceedings of the International Symposium on Advances in Technology Education (ISATE), Singapore.
• Hsu, Y.-Y., Clyne, M., Wei, C.-H., Khoury, M. J., & Lu, Z. (2019). Using deep learning to identify translational research in genomic medicine beyond bench to bedside. Proceedings of the 12th International Biocuration Conference, Cambridge, UK.
• Hsu, Y.-Y., Wei, C.-H., & Lu, Z. (2018). Assisting document triage for human kinome curation via machine learning. Proceedings of the Sixth BioCreative Challenge Evaluation Workshop, Bethesda, USA, 46-50.
• Lee, H.-C., Hsu, Y.-Y., & Kao, H.-Y. (2015). An enhanced CRF-based system for disease name entity recognition and normalization on BioCreative V DNER task. Proceedings of the Fifth BioCreative Challenge Evaluation Workshop, Sevilla, Spain.
• Hsu, Y.-Y., & Kao, H.-Y. (2014). Curatable named-entity recognition using semantic relations. Proceedings of the 25th International Conference on Genome Informatics (GIW-2014).
• Hsu, Y.-Y., & Kao, H.-Y. (2012). CoIN: A network exploration for document triage. Proceedings of the BioCreative 2012 Workshop, Washington, D.C., USA, 39-44.
• Wei, C.-H., Huang, I.-C., Hsu, Y.-Y., & Kao, H.-Y. (2009). Normalizing biomedical name entities by similarity-based inference network and de-ambiguity mining. Proceedings of the Ninth IEEE International Conference on Bioinformatics and Bioengineering Workshop: Semantic Biomedical Computing, Taichung, Taiwan, 461-466.
• Sun, K.-T., Wei, C.-H., Chang, T.-T., Liu, W.-C., & Hsu, Y.-Y. (2007). Deriving the formula of mutation rate of HBV. Conference on Medical Informatics in Taiwan, 103.
• Sun, K.-T., Wei, C.-H., Chang, T.-T., Liu, W.-C., & Hsu, Y.-Y. (2007). The study of computing evolutionary distance. Conference on Medical Informatics in Taiwan, 49.

...

• Introduction to Artificial Intelligence for Neuroscience, Spring 2024-25
• Natural Language Processing, Spring 2023, 2025
• AI Ethics and Human Rights: Applications of Explainable AI, Spring 2023
• Exploring Explainable AI in Biomedical Data Science, Spring 2022
• Introduction to Image Recognition AI and Robotics lab with NITKC (Japan), Fall 2021-25

Master program students:
Wang Cheng-Yang, Tao Yong-Lun, Yeh Shih-Chi, Liu Ren-Xin, Chen Bo-An, Huang Hong-Ming, Chen Hsing-Yu, Lin Shih-Xuan

Alumni:
Shih Mu-Ran, Wu Chien-Cheng

• Best performance in the disease-kinome curation subtask of BioCreative VI, 2017
• IICM Ph.D. Dissertation Award-Outstanding, 2015
• Best performance in the BioCreative V DNER task, 2015
• Best performance in the chemical recognition subtask of BioCreative Triage task, 2012
• Second place in the BioCreative Triage task, 2012