Jingwen Shao

2026-09-01 — 2029-07-01
👤 Personal Information
- Class of 2026, Master candidate in Electronic Information
- Document Analysis and Pattern Recognition Laboratory, School of Information Science and Technology, Shihezi University
🔬 Research Interests
- Pattern Recognition and Machine Learning
This research focuses on feature representation and model optimization in pattern recognition and machine learning. Traditional machine‑learning methods rely on manually‑designed features and cannot adaptively capture deep semantic information from data. Based on deep‑learning frameworks, this work explores how to automatically learn compact and discriminative feature representations from high‑dimensional data, and improves model generalization and robustness combined with statistical learning theory. Specific research includes feature selection and dimensionality reduction, classifier design and model interpretability analysis, aiming to provide efficient and reliable intelligent recognition solutions for practical application scenarios.
Keywords: machine learning, pattern recognition, deep learning, feature extraction, model optimization
📄 Academic Outputs
None
🏆 Honors & Awards
None
