Assistant Professor Ivy Hui-Yuan Yeh joined Nanyang Technological University (NTU) from the University of Cambridge, where she was working on her PhD in the Division of Biological Anthropology. She was a finalist for the SET for Britain poster presentation (Biological and Biomedical Science Session) held at the House of Parliament, UK, on the topic of ‘Detecting Diseases in Past Civilizations: How Ancient Parasites Could Help Us Fight Modern Allergies’.
Her research expertise lies in biological anthropology, coming from an interdisciplinary background.Ivy’s PhD in Biological Anthropology focused on migration, health and diet in populations past and present. Ivy mentored and supervised students for both lab work and essays at the University of Cambridge for two years.
I. Bioanthropology and Bioarchaeology Projects:
She is especially interested in the analysis of the health, disease, diet and nutrition of human communities, as well as population interactions. In particular, the spread of disease on a global scale from an evolutionary perspective. Her research projects explore how pathogen transference patterns via population interactions and migrations throughout human history to understand how human health has been impacted by diseases. Pathogens co-evolve with humans and have been transmitted among different regional populations to impact various societies’ health. Investigating pathogens throughout history and geographic areas sheds light on how humankind has been shaped by them and what may happen in the future. Ivy is also leading a research team in the northwestern region of China where a partial section of the Silk Road was located. She has a team working on the region, in particular the Mogou site, to better understand the interactions between early populations, their cultural exchange and how this might influence the formation of the early state of China.
2. Healthcare Projects:
2.1. Machine Learning for Diabetes Management:
Diabetes refers to a group of metabolic diseases described by hyperglycemia resulting from irregularities in insulin function. The chronic hyperglycemia of diabetes is related to long-term damage, dysfunction, and failure of multiple organs. Diabetes affects more than 200 million people, and it will continue to increase in the future. To prevent, cure and ameliorate conditions of diabetics, creating a precise model to predict diabetes is essential. Given the development of big data sets, studies have been conducted to apply AI/data mining in diabetes prediction. However, in these approaches, researchers attempted to improve prediction by using datasets or advanced algorithms predicated upon a high niche group of people or clinician information without lifestyle information. Lifestyle information plays important roles in the prediction of diabetes. Therefore, in our research, we wish to incorporate lifestyle information in our dataset. We aim to build a powerful model with complete information for diabetes prediction.
3. Python, Data Analysis and Deep Learning
I am into Python, Data Analysis and Deep Learning. For those who are interested in these areas, please feel free to contact me for free materials you can use.