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. (2021). A unifying tutorial on Approximate Message Passing. Preprint.

Feng, O. Y., Chen Y., Han, Q., Carroll, R. J. and Samworth, R. J. (2021+). Nonparametric, tuning-free estimation of S-shaped functions. J. Roy. Statist. Soc., Ser. B, to appear. 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 will be giving a graduate course on Nonparametric Inference under Shape Constraints.

I have supervised the following undergraduate courses: 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.