an Chengli currently serves as an Associate Professor and Postdoctoral Researcher at the School of Mathematics and Statistics, Northwestern Polytechnical University. His primary research focuses on the generalization theory of machine learning and stochastic optimization algorithms.

He obtained his PhD degree in Statistics from the School of Mathematics and Statistics, Xi'an Jiaotong University in 2024, under the supervision of Professor Zhang Jiangshe. Both his master's and bachelor's studies were completed in related majors at the same university, laying a solid foundation in mathematics and statistics.

Since April 2025, he has joined the "Statistics and Complexity Science" team at Northwestern Polytechnical University, conducting postdoctoral research under the guidance of Professor Xu Yong. His work centers on achieving theoretical breakthroughs in the Sharpness-Aware Minimization (SAM) algorithm. To address the challenges of SAM—such as its tendency to get trapped in saddle points and low escape efficiency—he proposed the Stable Sharpness-Aware Minimization (SSAM) strategy. By designing a non-normalized algorithm, SSAM enhances generalization performance and stability, and the related achievements have attracted attention from the academic community. His research interests also include image processing and complex network analysis, exploring key issues in engineering optimization by integrating statistical models.

Dr. Tan has a prolific academic record. As the first author or corresponding author, he has published more than 10 papers in top international journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), IEEE Transactions on Neural Networks and Learning Systems (TNNLS), and Journal of Machine Learning Research (JMLR). His core findings have been applied in National Natural Science Foundation of China projects and industry-university cooperation research topics. In May 2025, he was invited to deliver special reports at universities including Nanjing Audit University and Northeast Normal University, systematically elaborating on the innovative mechanism and application value of the SSAM algorithm.

In teaching, he works as an undergraduate supervisor, guiding students in mathematical modeling competitions and scientific research practices, with an emphasis on integrating theory with engineering applications. As a key academic member, he deeply participates in interdisciplinary team research and promotes the transformation of achievements in the fields of statistical machine learning and complex networks. The latest research developments and cooperation information can be found on his personal homepage.