Advanced Biomedical Informatics Lab (ABI Lab)
Research Field
- 2024.03- Director, Graduate Institute of Biomedical Informatics, Taipei Medical University
- 2021.08- Director, Bioinformatics Center, Office of Data Science, Taipei Medical University
- 2019- Professor, Graduate Institute of Biomedical Informatics, Taipei Medical University
- 2019- Professor, Professional Master Program for Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University
- 2018-2023.09 Dean, Office of Information Technology, Taipei Medical University
- 2019-2021 Director, Clinical Data Science, Taipei Medical University
- 2016-2019 Associate professor, Graduate Institute of Biomedical Informatics, Taipei Medical University
- 2012-2016 Assistant professor, Graduate Institute of Biomedical Informatics, Taipei Medical University
- Postdoctoral Fellow, Institute of Bioinformatics and Systems Biology, National Chiao Tung University
The primary research interests of ABI Lab encompass a range of fields, including but not limited to bioinformatics, machine learning, metagenomics, systems biology, and medical informatics. In recent years, ABI Lab has concentrated its research efforts on gene regulatory networks, deep learning, and precision medicine, among other areas of investigation. Moreover, ABI Lab places a premium on collaboration with biologists and researchers from a multitude of disciplines, with the objective of enhancing the value of cross-domain research (wet lab + dry lab). Moreover, the laboratory has allocated a significant amount of resources to the analysis of clinical data. The research is primarily concerned with the analysis of biomedical big data and the analysis of disease prognosis through the utilisation of deep learning methodologies. The research topics are original and innovative, and the research is diverse, offering both depth and clinical value. The ABI Lab has made significant contributions to the field of medical diagnosis and care research, which demonstrates the efforts and contributions of the ABI Lab in developing the value of biomedical information in interdisciplinary research. Furthermore, the ABI Lab actively promotes collaboration between biomedical information and various research areas. Furthermore, the ABI Lab has actively promoted the integration of bioinformatics with a range of research disciplines, underscoring the pivotal role of bioinformatics in cross-disciplinary research.
- BioMedical Informatics
- Machine learning
- Data Mining and AI Applications
- Genomics
- Systems Biology
(1) 2021 Future Technology Award: Multi-mode Lung Cancer Clinical Intelligent Decision Making and Sharing Aid System
(2) 2022 Future Technology Award: Multi-mode Artificial Intelligence Personalisation 4D Dementia Prediction Module for Elderly Health
(3) 2022 National Innovation Award: Lung Cancer Clinical Intelligent Decision Making Sharing System
- 2009 Ph.D., Institute of Computer Science and Information Engineering, National Central University, Taiwan
- 2003 M.S., Institute of Information Management, Yuan Ze University
- 2001 B.S., Department of Information Management, National Central University
2 Vacancies
Job Description
We are seeking highly motivated interns to join our research team. This opportunity provides hands-on experience in machine learning, biomedical informatics, and AI applications in medicine. Interns will work closely with researchers on cutting-edge projects, gaining exposure to clinical data integration, predictive modeling, and AI-driven decision support tools.
This internship offers:
✔ Exposure to real-world medical AI projects
✔ Hands-on experience with healthcare big data and machine learning techniques
✔ Collaboration with healthcare professionals and data scientists
✔ Opportunities for academic publication and conference presentations
Preferred Intern Education Level
We welcome applications from students at various academic levels:
- Undergraduate (final-year students) in Biomedical Informatics, Computer Science, Bioinformatics, Data Science, or Healthcare Management.
-Master’s and Ph.D. students in Biomedical Informatics, Artificial Intelligence, Machine Learning, Bioinformatics, or related fields.
- Postdoctoral researchers with expertise in AI, medical data analysis, or precision medicine are also encouraged to apply.
Skill sets or Qualities
Ideal candidates should have one or more of the following skills:
✔ Programming skills: Proficiency in Python, R, or MATLAB; experience with TensorFlow, PyTorch, or Scikit-learn is a plus.
✔ Machine learning & AI expertise: Strong knowledge of deep learning, NLP, and generative AI models.
✔ Healthcare data experience: Familiarity with biomedical datasets (NGS, EMR, imaging, wearable data).
✔ Statistical & data analysis: Understanding of biostatistics, regression models, survival analysis.
✔ Research mindset: Ability to analyze complex datasets and generate innovative solutions in biomedical informatics.
✔ Communication skills: Strong written and verbal English skills to collaborate with interdisciplinary teams.