Ting Shu was born in July 1979 and obtained his Ph.D. in Computer Science from Zhejiang University in 2010. Currently, he serves as an associate professor at the School of Information Science and Technology, Zhejiang Sci-Tech University in Hangzhou, China. His research interests primarily focus on software testing, metaheuristic algorithms, and network protocol testing.
Throughout his scientific research career, Ting Shu has achieved a series of remarkable results. Below are some of his research contributions:
Model-based diversity-driven learn-to-rank test case prioritization: This study, published in the journal "Expert Systems with Applications," explores how to optimize the priority of test cases through learning-to-rank methods to improve the efficiency and effectiveness of software testing.
Resource scheduling optimization for industrial operating systems using deep reinforcement learning and WOA algorithm: Also published in "Expert Systems with Applications," this article introduces a novel method to optimize resource scheduling in industrial operating systems aimed at enhancing system efficiency and stability.
Structure-aware preserving projections with applications to medical image clustering: This journal article, published in June 2024, focuses on a new projection method that preserves the intrinsic structure of data, which is particularly useful for the analysis and processing of medical images, appearing in the journal "Applied Soft Computing".
