Shaokui Wei

Shaokui Wei

Ph.D. Candidate in CUHK(SZ)

Teaching

Teaching Assistant - DDA4340

DDA4340 Computational Methods for Finance, CUHKSZ, 2024

This course provides an introduction to the field of computational finance, focusing on the application of computational methods to solve complex financial problems. Topics include: random number generation; the fundamentals of Monte Carlo (MC) simulation; variance-reduction techniques for MC simulation and related issues; numerical solutions to stochastic differential equations by means of MC simulation and their implementation.

Teaching Assistant - STA4000

STA 4010 Causal Inference, CUHKSZ, 2023

This course is designed to study causal inference. Topics include discussions of observational studies, propensity score analysis, and double machine learning. Additionally, the course covers topics such as causal graphs, structural causal models, and causal discovery.

Teaching Assistant - STA3006

STA 3006 Design and Analysis of Experiments, CUHKSZ, 2022

This course is designed to study various statistical aspects of models in the analysis of variance. Topics include randomization, replication and blocking, randomized blocks, Latin squares and related designs, missing values, incomplete block designs, factorial designs, nested designs and nested-factorial designs, and 2k factorial designs. The use of statistical packages are demonstrated.

Teaching Assistant - STA4030

STA 4030 Categorical Data Analysis, CUHKSZ, 2021

This course deals with major statistical techniques in analysing categorical data. Topics include measures of association, inference for two-way contingency tables, loglinear models, logit models and models for ordinal variables. The use of related statistical packages are demonstrated.

Teaching Assistant - DDA4230

DDA 4230 Reinforcement Learning, CUHKSZ, 2021

This course is a basic introduction to reinforcement learning algorithms and their applications. Topics include: multi-armed bandits; finite Markov decision processes; dynamic programming; Monte Carlo methods; temporal-difference learning; actor-critic methods; off-policy learning; and introduction to approximation methods.

Teaching Assistant - STA3050

STA3050 Statistical Software, CUHKSZ, 2020

This course aims at providing students with basic knowledge of programming in R. A problem-solving approach is employed. Algorithm development and implementation with emphasis on examples and applications in statistics are discussed.