Search

Beatriz Carmona received her BS in Nutrition/Dietetics with a minor in Statistics from Auburn University in 2021. She is now a doctoral candidate in Community Nutrition in the Division of Nutritional Sciences at Cornell University, and an NIH-funded T32 trainee in Maternal and Child Nutrition. 

Naiwen is PhD candidate in Nutritional Sciences and minor in Epidemiology and Data Science. Her study focuses on understanding the dimension of diet-related factors and malnutrition among vulnerable populations including children, adolescents, and women of reproductive age in low/middle-income settings using both traditional statistical approaches and machine learning.

Siwen Xue is a Ph.D. student in Nutritional Sciences at Cornell University, where she studies how cellular and molecular pathways regulate muscle regeneration and metabolism. With a background in food science and biotechnology, she is passionate about translating laboratory discoveries into real-world innovations that promote health. Before Cornell, Siwen completed her Ph.D. in Food Science at Nanjing Agricultural University and was a visiting scholar at Purdue University. Her work is driven by a curiosity about

Pei-Yin  is interested in the relationship between metabolism and chronic diseases. Her research focuses on how adipocytes are involved in obesity and cancer cachexia. She is fascinated by the ways in which various biological pathways influence energy homeostasis and their intricate cross-talk. She hopes to contribute her efforts toward unraveling these mechanisms and identifying potential strategies to slow the progression of chronic diseases.

Zhuoheng Li is a Ph.D. candidate in Molecular Nutrition, working with Dr. Nathaniel Vacanti. He holds an M.S. in Biochemical and Molecular Nutrition from the Friedman School of Nutrition Science and Policy at Tufts University and a B.S. in Food Science and Technology from the University of California, Davis. Zhuoheng is dedicated to developing algorithms and pipelines for the integration and analysis of multi-omics data, with the objective of translating complex data into cancer biology