Statistical Estimation: This is a proof-based, graduate or advanced undergraduate level introduction to the theory of statistical estimation. The course covers basic approaches in mathematical statistics, including the minimax and the Bayesian point of view coupled with asymptotic or finite-sample analysis.
Hypothesis Testing: This is a proof-based, graduate or advanced undergraduate level introduction to the theory of hypothesis testing. The course covers fundamentals of hypothesis testing, large-sample theory, and various examples of statistical tests in classical and modern settings.
Introductory Probability and Statistics: This is an undergraduate level introduction to probability and statistics for engineering students.
Adaptive Estimation with Lepski's Method, co-written with Jan-Christian HÃ¼tter
Ranking from Pairwise Comparisons, as part of Yihong Wu and Jiaming Xu's lecture notes on statistical inference on graphs