Organisation profile

Organisation profile

The rise of Big Data Analysis has revolutionized the related industries and applications in recent years. Data Science has also inspired the resurgence of artificial intelligence, which has led to the competition for the cultivation of talents in data science research and related industry of international and domestic academic fields. Today's so-called Data Scientists refer to experts who can extract useful information from various data sets and apply them in different fields. Therefore, data scientists must not only have the ability of statistical data analysis and scientific computing related programing, but more importantly, they can integrate big data analysis into various professional fields. Basically, data science is a cross-disciplinary science that includes statistical science, information science, and knowledge in related fields. Compared with other data science-related teaching units, the training of our institute emphasizes the statistical data analysis courses required by data science as the main axis, supplemented by information engineering courses. In addition, NCKU is a comprehensive university, the faculty of each department has a strong lineup, and the complete information of each center can be used as a strong backing for the professional application knowledge field of the institute and the development of data science.

UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Our work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being
  • SDG 7 - Affordable and Clean Energy
  • SDG 11 - Sustainable Cities and Communities
  • SDG 16 - Peace, Justice and Strong Institutions

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Collaborations and top research areas from the last five years

Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
  • 1stWorkshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results

    Kiefer, B., Kristan, M., Pers, J., Zust, L., Poiesi, F., De Alcantara Andrade, F. A., Bernardino, A., Dawkins, M., Raitoharju, J., Quan, Y., Atmaca, A., Hofer, T., Zhang, Q., Xu, Y., Zhang, J., Tao, D., Sommer, L., Spraul, R., Zhao, H., Zhang, H., & 52 othersZhao, Y., Augustin, J. L., Jeon, E. I., Lee, I., Zedda, L., Loddo, A., Di Ruberto, C., Verma, S., Gupta, S., Muralidhara, S., Hegde, N., Xing, D., Evangeliou, N., Tzes, A., Bartl, V., Spanhel, J., Herout, A., Bhowmik, N., Breckon, T. P., Kundargi, S., Anvekar, T., Tabib, R. A., Mudengudi, U., Vats, A., Song, Y., Liu, D., Li, Y., Li, S., Tan, C., Lan, L., Somers, V., De Vleeschouwer, C., Alahi, A., Huang, H. W., Yang, C. Y., Hwang, J. N., Kim, P. K., Kim, K., Lee, K., Jiang, S., Li, H., Ziqiang, Z., Vu, T. A., Nguyen-Truong, H., Yeung, S. K., Jia, Z., Yang, S., Hsu, C. C., Hou, X. Y., Jhang, Y. A., Yang, S. & Yang, M. T., 2023, Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023. Institute of Electrical and Electronics Engineers Inc., p. 265-302 38 p. (Proceedings - 2023 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops, WACVW 2023).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)
  • Classifying and clustering noisy images using subset learning based on convolutional neural networks

    Jeng, S. L. & Chang, Y. C., 2023 Oct, In: Quality and Reliability Engineering International. 39, 6, p. 2343-2364 22 p.

    Research output: Contribution to journalArticlepeer-review

    1 Citation (Scopus)
  • CoANE: Modeling Context Co-Occurrence for Attributed Network Embedding

    Hsieh, I. C. & Li, C. T., 2023 Jan 1, In: IEEE Transactions on Knowledge and Data Engineering. 35, 1, p. 167-180 14 p.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    2 Citations (Scopus)