I am a postdoctoral research associate in Statistics, supervised by Professor Richard J. Samworth. I am also a Teaching By-Fellow at Churchill College.

My research interests include shape-constrained density estimation and regression, as well as the statistical analysis of approximate message passing (AMP) algorithms.

Education

2017–2021: PhD in Statistics, University of Cambridge, supervised by Professor Richard J. Samworth. Thesis: Topics in shape-constrained inference.

2013–2017: BA and MMath, Trinity College, University of Cambridge.

Publications and preprints

Feng, O. Y., Venkataramanan, R., Rush, C. and Samworth, R. J. (2022). A unifying tutorial on Approximate Message Passing. Foundations and Trends in Machine Learning, 15, 335–536.

Feng, O. Y., Chen Y., Han, Q., Carroll, R. J. and Samworth, R. J. (2022). Nonparametric, tuning-free estimation of S-shaped functions. J. Roy. Statist. Soc., Ser. B, 84, 1324–1352. Accompanying R package: Sshaped. 

Feng, O. Y., Guntuboyina, A., Kim, A. K. H. and Samworth, R. J. (2021). Adaptation in multivariate log-concave density estimation. Ann. Statist., 49, 129–153.

Teaching and other activities

In Lent 2022, I taught a graduate course on Nonparametric Inference under Shape Constraints.

I have supervised the following undergraduate courses: Part IA Probability; Part IB Linear Algebra, Markov Chains, Statistics and Optimisation; Part II Mathematics of Machine Learning, Principles of Statistics and Probability and Measure. I have also given examples classes for the Part III Topics in Statistical Theory course.

I am a member of the Statistics Clinic team.