Chengchun's research is concentrated on statistical learning methods in individualized decision making and statistical analysis of complex data.
The motivation behind his work stems from real world applications. In precision medicine, individualizing the treatment decision rule can capture patients’ heterogeneous response towards treatment. In finance, individualizing the investment decision rule can improve individual’s financial well-being. In a ride-sharing company, individualizing the order dispatching strategy can increase its revenue and customer satisfaction. With the fast development of new technology, modern datasets often consist of massive observations, high-dimensional covariates and are characterized by some degree of heterogeneity. In an era of big and complex data, he is interested in developing computationally efficient algorithms with statistical performance guarantees.
Prior to joining LSE in 2019, Chengchun obtained his PhD in statistics at North Carolina State University, under the supervision of Dr. Wenbin Lu and Dr. Rui Song.