Scholars@Duke
Cristiano Villa

Cristiano Villa

Associate Professor of Statistics at Duke Kunshan University
DKU Faculty

Overview

Prof. Cristiano Villa main research area is in Bayesian statistics, with particular interest in objective methods. His output has been published in several peer-reviewed journals and presented at international conferences, such as the ISBA International Conference, the O-Bayes conference, and the ERCIM conference. In addition to his research, Prof. Villa is deeply committed to teaching and enjoys interacting with students. His teaching interests include probability, statistics, linear modelling, and risk management. Before joining Duke Kunshan University (DKU), Prof. Villa was a member of the Newcastle University (UK) and the University of Kent (UK). Prior to joining academia in 2014, he worked as an auditor and as an advisor for KPMG in several countries, including, Italy, UK, New Zealand, and Singapore. He holds an M.Sc. and a Ph.D. from the University of Kent, UK.

Current Appointments & Affiliations

Associate Professor of Statistics at Duke Kunshan University · 2023 - Present DKU Faculty
Associate Professor of the Practice of DKU Studies at Duke University · 2025 - Present DKU Studies

Recent Publications

Copula modelling with penalized complexity priors: the bivariate case

Journal Article Test · June 1, 2023 We explore the use of penalized complexity (PC) priors for assessing the dependence structure in a multivariate distribution F, with a particular emphasis on the bivariate case. We use the copula representation of F and derive the PC prior for the paramete ... Full text Cite

Bayesian Models Applied to Cyber Security Anomaly Detection Problems

Journal Article International Statistical Review · April 1, 2022 Cyber security is an important concern for all individuals, organisations and governments globally. Cyber attacks have become more sophisticated, frequent and dangerous than ever, and traditional anomaly detection methods have been proved to be less effect ... Full text Cite

An objective Bayes factor with improper priors

Journal Article Computational Statistics and Data Analysis · April 1, 2022 A new look at the use of improper priors in Bayes factors for model comparison is presented. As is well known, in such a case, the Bayes factor is only defined up to an arbitrary constant. Most current methods overcome the problem by using part of the samp ... Full text Cite
View All Publications

Education, Training & Certifications

University of Kent (United Kingdom) · 2014 Ph.D.