About

Current Position:  Nanyang Assistant Professor, NTU, Singapore 

Email Address: hyyeh@ntu.edu.sg

Google Scholar

https://www.researchgate.net/profile/Ivy-Hui-Yuan-Yeh-yehuiyuan

Ivy was trained in the Department of Anthropology and the School of Medicine at National Taiwan University. After working at Academia Sinica in Taipei, she pursued her PhD in the Division of Biological Anthropology at the University of Cambridge. Her research expertise lies in biological anthropology, supported by an interdisciplinary background. For two years, Ivy supervised and mentored students in both laboratory work and essay writing at Cambridge. 

Throughout her career, Ivy has held several roles, including Coordinator of the Medical Humanities Research Cluster at NTU, NTU iGave Ambassador of the School of Humanities, member of the International Advisory Committee (IAC) of the Chinese Heritage Centre (CHC) at NTU, Preparation Committee member for the Conference on Pan-Pacific Anthropocene (ConPPA), editorial board member of the International Journal of Osteoarchaeology, and Topic Editor for Frontiers in Genetics.

Ivy currently has three main projects below: 

I. Bioanthropology and Bioarchaeology Projects:

Ivy studies the health, disease, diet, and nutrition of human communities, with a focus on how pathogens and population interactions have shaped human health across history. Her research investigates the global spread of disease from an evolutionary perspective, including projects along the Silk Road and the Austronesian expansion, exploring how long-distance trade, migration, and seafaring influenced disease transmission and nutrition. By examining pathogens in historical and geographical contexts, her work sheds light on how societies have been affected by disease—and what this may reveal for the future. These studies are conducted in collaboration with Harvard University and University of Cambridge.

 

2. Artificial Intelligence in Art & Market Analysis:

In addition to research in biological anthropology, bioarchaeology, and medical AI, I explore the application of artificial intelligence to art and archaeology. I am developing deep learning models to classify and interpret blue-and-white porcelain by dynastic period. Using a multi-view dataset of 284 Ming and Qing objects (986 images), a fine-tuned ResNet-50 achieved the highest classification accuracy, and incorporating multiple views per object further improved performance. Explainable AI techniques show that the model focuses on features such as shape and decorative motifs, while feature visualizations reveal clear clustering by dynasty and object type. This work highlights how AI can uncover patterns in cultural heritage and support the analysis of artifacts for research and public engagement. The next step is to extend the models to predict art market values, combining cultural insights with economic analysis in the art world.

3. Deep Learning Algorithms in Forensic Anthropology: 

Ivy uses machine learning to support forensic medicine doctors in identifying unknown victims. We are currently collaborating with a Taiwanese forensic team, and you’re very welcome to join us if you’re interested. Beyond modern forensics, this approach also helps correct biases in historical and archaeological datasets—by refining age, sex, and population estimates, it improves the accuracy of ancient population reconstruction and the interpretation of past demographic structures.
 
 
Geographic Distribution of Ivy’s International Collaboration Network