Xu Chen is a Lecturer in Data Science at the School of Mathematics, Statistics and Actuarial Science (SMSAS), University of Essex since 2023. She holds a PhD in Statistics from the University of Warwick (2014) and a BSc in Information and Computational Science from Shanghai University of Finance and Economics (2009). Her research focuses on developing statistical and computational methods for analyzing large-scale neuroimaging data, particularly in quantifying brain activity, heritability analysis, and functional connectivity studies. Prior to Essex, she conducted postdoctoral research at Leiden University Medical Center (2019–present) and Maastricht University (2015–2018) in biomedical data science and cognitive neuroscience. Her work emphasizes statistical methodologies for neuroimaging, including permutation-based inference, cluster thresholding, and accelerated estimation techniques for ACE models. She has contributed to studies on genetic influences on nervous system activity during fear conditioning and pain processing, leveraging twin studies and functional MRI datasets. Dr. Chen’s expertise spans computational neuroscience, biostatistics, and interdisciplinary applications of statistical methods in biomedical research. Key research outputs include advancements in neuroimaging data analysis frameworks, such as NetTDP for differential co-expression networks and adaptive cluster thresholding methods. Her contributions are reflected in peer-reviewed publications and collaborative projects involving the Human Connectome Project (HCP) datasets.
