Kuo Gai

BIO

Kuo Gai is currently an assistant professor at the Shanghai Institute of Mathematics and Interdisciplinary Sciences (SIMIS). He graduated in 2022 from the Academy of Mathematics and Systems Science, Chinese Academy of Sciences. Subsequently, he held positions as a postdoctoral researcher and assistant professor at the School of Mathematical Sciences, Peking University, and School of Artificial Intelligence, Wuhan University. His research focuses on the abrupt changes in system eigenvalues under stochastic perturbations, feature learning theory in neural networks, and applications of deep learning in bioinformatics.

Education Experience

• 2013-2017，School of Mathematical Sciences，Fudan University, Bachelor of Science
• 2017-2022，Academy of Mathematics and Systems Science of the Chinese Academy of Sciences，PhD in Applied Mathematics

Work Experience

• 2022.9-2025.3, School of Mathematical Sciences, Peking University, Postdoctoral Researcher
• 2025.5-2025.9, School of Artificial Intelligence, Wuhan University, Assistant Professor

Publications

1. Gai K, Zhang S. Tessellating the Latent Space for Non-Adversarial Generative Auto-Encoders, IEEE Transactions on Pattern Analysis and Machine Intelligence,2024
2. Zhang C.∗, Gai K∗, and Zhang S. Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling. Pattern Recognition, 2024
3. Li S∗, Gai K∗, Dong K.∗, Zhang Y., and Zhang S. High-density Generation of Spatial Transcriptomics with STAGE. Nucleic Acids Research, 2024
4. Wang S∗, Gai K∗ and Zhang S. Progressive Feedforward Collapse of ResNet Training. IEEE Transactions on Neural Networks and Learning Systems, 2025