Nutrition Genomic Laboratory
Research Field
Dr. Sing-Chung Li is a mentor and researcher at the School of Nutrition and Health Sciences, Taipei Medical University. He earned his Ph.D. in Agricultural Chemistry from National Taiwan University and has an interdisciplinary background in nutrition, food science, and biotechnology. Dr. Li’s research focuses on genomics, biotechnology, food analysis, food microbiology, infant and early childhood nutrition, diet-related diabetes, and AI-assisted image-based dietary assessment to understand and prevent chronic metabolic diseases, emphasizing translational research that bridges basic science and practical applications. His laboratory investigates bioactive compounds from Taiwanese local resources, such as sweet potatoes, mushrooms, and green bananas, using cell, animal, and human models. In parallel, the lab conducts a feasibility study on an AI-assisted image-based dietary recording tool for dietary self-management among university students, integrating nutrition science with artificial intelligence and digital health. Dr. Li collaborates with leading institutes, including Academia Sinica, and has published extensively in SCI journals. As an IIPP mentor, he provides a supportive environment for international students to gain hands-on research experience in nutrition and digital health in Taiwan.
- The Nutrition Genomics Laboratory (NGL), led by Dr. Sing-Chung Li at Taipei Medical University, conducts interdisciplinary research integrating nutrition, genomics, functional foods, metabolic health, and digital health technologies. The laboratory aims to translate basic nutritional science into practical strategies for preventing and managing chronic metabolic diseases and improving dietary self-management.
- NGL’s research areas include nutrition and metabolic diseases, vitamin and mineral nutrition, disease-specific formula foods, health food function evaluation, dietary assessment, molecular nutrition, and AI-assisted image-based dietary assessment. The laboratory places strong emphasis on functional ingredients from local Taiwanese resources, particularly sweet potatoes and edible mushrooms (Lingzhi, Nameko, and Pleurotus species), and their roles in diabetes, insulin resistance, sarcopenic obesity, and maternal–infant nutrition. In parallel, NGL is conducting a feasibility study on an AI-assisted image-based dietary recording tool for dietary self-management among university students.
- The laboratory adopts cell, animal, and human research models and provides training in laboratory techniques, dietary data analysis, and scientific writing. With active collaborations, including Academia Sinica, NGL offers an international-friendly environment and hands-on research opportunities for IIPP interns.
Our laboratory focuses on nutrigenomics, functional foods, and the prevention of diabetes and insulin resistance in metabolic diseases. We investigate health-promoting materials derived from local Taiwanese resources, such as sweet potatoes, edible mushrooms, and green bananas, using cell-based, animal, and human models to evaluate their biological functions and mechanisms.In addition, our research includes AI-assisted image-based dietary assessment, particularly the feasibility of image-based dietary recording tools for dietary self-management among university students, integrating nutrition science with artificial intelligence and digital health technologies.The laboratory emphasizes translational and interdisciplinary research and maintains close collaborations with the Institute of Plant and Microbial Biology and the Agricultural Biotechnology Research Center at Academia Sinica.
- Teaching Material Innovation Award, Academic Year 96
- Creative Teaching Award, Academic Year 97
- Teaching Material Innovation Award, Academic Year 98
Education:
- Ph.D. in Agricultural Chemistry, National Taiwan University, 2001
- M.S. in Agricultural Chemistry, National Taiwan University, 1994
- B.S. in Health and Nutrition, Taipei Medical College, 1992
Experience:
- Associate Professor, Department of Health and Nutrition, Taipei Medical University, 2011.02-present
- Assistant Professor, Department of Health and Nutrition, Taipei Medical University, 2003.09-2011.01
- Visiting Scholar, Duke University Medical Center, 2003.06-2003.08
- Ph.D. Research, Institute of Biomedical Sciences, Academia Sinica, 2002.07-2003.08
- Ph.D. Research, Institute of Plant and Microbial Biology, Academia Sinica, 2001.07-2002.06
Job Description
Specific tasks may include assistance with cell culture experiments, preparation of bioactive compound extracts from edible mushrooms, basic biochemical assays, data organization and analysis, and support for literature review and scientific writing. The intern will also engage in regular research meetings and academic discussions.
Preferred Intern Educational Level
Applicants should be senior undergraduate students, master’s students, or early-stage PhD students majoring in nutrition, food science, biomedical sciences, biotechnology, or related disciplines.
Skill sets or Qualities
Basic knowledge of nutrition or life sciences, strong motivation for research, willingness to learn laboratory techniques, good communication skills in English, and the ability to work independently as well as collaboratively in a research team. Prior laboratory experience is preferred but not mandatory.
Job Description
Key responsibilities include assisting with the development and testing of AI-based dietary recording systems, supporting data collection and annotation, basic statistical analysis, and literature review. The intern may also contribute to pilot studies involving university students and participate in research meetings and interdisciplinary discussions.
Preferred Intern Educational Level
Applicants should be senior undergraduate students, master’s students, or early-stage PhD students in nutrition, public health, food science, data science, computer science, biomedical sciences, or related fields.
Skill sets or Qualities
Strong interest in AI-assisted nutrition research, basic knowledge of nutrition or data analysis, familiarity with spreadsheets or statistical software, willingness to learn AI or image-analysis tools, good English communication skills, and the ability to work independently and collaboratively.