Peien joined Prof Cornelia van Duijn’s group as a DPhil student in 2023, funded by the Clarendon Scholarship and NDPH. He is jointly supervised by Prof Cornelia van Duijn, Dr David Preiss and Dr Louisa Gnatiuc. His project focuses on using machine learning techniques to analyze proteomic and other omic data in Alzheimer’s and other dementia diseases, specifically in mechanisms and targets for intervention and detection. Given his multidisciplinary background, his work integrates advanced computational methods with medical insights, aiming to solve complex disease causal pathways.
Peien completed an MPhil in Population Health Sciences (Health Data Science) at University of Cambridge. He developed skills in machine learning, Bayesian statistics, genetic epidemiology and genomics. He got Distinction in his master thesis "Improving Genetic Prediction of Multi-omics Traits on Large-scale Omics QTL Summary Statistics Using Machine Learning" and several courses. These experiences deepened his understanding of advanced statistical methods and equipped him with proficiency in working in high-performance computing environments using Linux.
Peien earned his Bachelor of Medicine in Public Health from Sun Yat-sen University. He gained experience in various epidemiological fields, such as Environmental Health, Health Behavior, and Gut Microbiome studies. His systematic medical education not only provided him with a broad understanding of numerous diseases but also an appreciation for the complex interrelations among these conditions. During his medical studies, he passionately self-learned Python and R. His dream is to pioneer advancements in medical science, improve healthcare outcomes and population health with the help of data science.