We are the Computational Biology & Intelligence System Research Group @ National Cheng Kung University. If you are interested in doing multidisciplinary research projects, please feel free to contact us. Students interested in artificial intelligence or its application in biomedical areas are welcome to join us.

Congragulation to our lab members:

2025
1. Kai-Wei Yu (游鎧蔚), 2025「AI 應用論文競賽」佳作

2. Zhe-Yu Wu (吳哲宇), Kai-Wei Yu (游鎧蔚), 入選 2025「AI 應用論文競賽」入選決賽 @ Taipei

3. Kai-Wei Yu (游鎧蔚), 2025 ISEGB (Poster) @ Tainan
4. Xing-Yo Wang (王興祐), 114 年大專生研究計畫
5. He-Ruei Lee (李和叡), 114 年大專生研究計畫 (與護理系林梅鳳老師合作指導)
6. Chong-Lun Chen (陳崇倫), 114 年大專生研究計畫 (與生技系許觀達老師合作指導)
7. Ting-Hsuan Lin (林庭亘), 114 年大專生研究計畫 (與醫技系、成大醫院病理部分子診斷組陳怡伶老師合作指導)
8. En-Hsun Cheng (鄭恩汛), 2025 ISEGB (Poster) @ Tainan
9. Zhe-Yu Wu (吳哲宇), 2025 ISEGB (Poster) @ Tainan
10. Kai-Wei Yu (游鎧蔚), 2025 ISEGB (Poster) @ Tainan
11. Cheng-Wei Liu (劉政緯), 2025 ISEGB (Poster) @ Tainan
2024
12. Cheng-Wei Liu (劉政緯), 2024 MOPM (Poster) @ Taipei
13. You-An Kuo (郭祐安), 2024 SMBE Regional Meeting in Taiwan (Poster) @ Taipei
14. Han-Ting Hong (洪翰霆), 2024 SMBE Regional Meeting in Taiwan (Poster) @ Taipei
15. Guan-Liang He (何冠良), 2024 SMBE Regional Meeting in Taiwan (Poster) @ Taipei
16. Hua-Yi Lin (林華毅), 2024 SMBE Regional Meeting in Taiwan (Poster) @ Taipei
17. You-An Kuo (郭祐安), 2024 SMBE Regional Meeting in Taiwan (Travel Grant Winner) @ Taipei
18. Chin-Cheng Lee (李縉丞), 2024 ICBCB (Oral Presentation) @ Tokyo

2021
19. Ya-Chiao Yang (楊雅喬), Hsiu-Chun Tsai (蔡琇鈞), Chung-Yu Wang (王仲佑), and Kai-Chi Tu (涂凱祺), 2021 TAAI (Oral Presentation) @ Taichung

2020
20. Yu-Cian Lin (林郁茜), 2020 InCoB (Top 5 Best Poster Presentation) @ Virtual
21. Yu-Huai Yu (尤毓淮), 2020 InCoB (Top 5 Best Poster Presentation) @ Virtual

Our research is focused on Computational Biology, Systems Biology, and Bioinformatics. The central theme of these cross-domain research fields is integrating different genome-wide high-throughput data using electrical engineering and computer science techniques to construct and analyze biological systems. Mastering both information engineering techniques and biological knowledge is required to tackle these types of problems. The results combine biological knowledge (molecular biology and cell biology) and information engineering techniques (network analysis, Digital Signal Processing, algorithm design, dynamic system modeling, machine learning, and big data analysis).

The following categories outlined our current research focuses: