从事人工智能与应用数学的交叉研究与应用。研究内容包括机器学习的基础算法、AI for Industry。
教育经历
教育经历：
2011.9-2015.6,苏州大学,本科
2015.9-2020.6,苏州大学,博士
工作经历
工作经历：
2020.7-2023.10,昆山杜克大学,研究员
2023.11-2024.11,The Fields Institute for Research in Mathematical Sciences, Canada,博士后
2025.2-至今,苏州大学, 数学科学学院,讲师
社会职务
个人简介
个人简介：个人简介：
从事人工智能与应用数学的交叉研究与应用。研究内容包括机器学习的基础算法、AI for Industry。
社会职务
研究领域
研究方向：
1, 科学计算、计算机辅助几何设计
2, 机器学习、深度学习
3, AI for Industry
开授课程
开授课程：
1、Python程序设计
2、非结构化数据分析
3、统计机器学习
4、数据挖掘
科研项目
科研项目：
1、面向小样本多模态机器学习任务的优化建模,江苏省高校自然科学研究面上项目
2、医疗表格数据的深度学习稀疏建模,江苏省自然科学青年基金
论文
论文：
1、Jiaqi Luo, Hongmei Kang, and Zhouwang Yang. Knot calculation for spline fitting based on the unimodality property. Computer Aided Geometric Design 73 (2019): 54-69.
2、Jiaqi Luo, Hongmei Kang, and Zhouwang Yang. Knot placement for B-spline curve approximation via l_{infty, 1}-norm and differential evolution algorithm. Journal of Computational Mathematics 40(4) (2022): 589-606.
3、Zepeng Wen, Jiaqi Luo, and Hongmei Kang. The deep neural network solver for B-spline approximation. Computer-Aided Design 169 (2024): 103668.
4、Jiaqi Luo, Zihao Wei, Junkai Man, and Shixin Xu. TRBoost: A Generic Gradient Boosting Machine based on Trust-region Method. Applied Intelligence 53.22 (2023): 27876-27891
5、Jiaqi Luo and Shixin Xu. NCART: Neural Classification and Regression Tree for Tabular Data. Pattern Recognition 154 (2024): 110578.
6、Jiaqi Luo, Yuan Yuan, and Shixin Xu. Improving GBDT Performance on Imbalanced Datasets: An Empirical Study of Class-Balanced Loss Functions. Neurocomputing 634 (2025) : 129896.
7、Jiaqi Luo, Yahong Yang, Yuan Yuan, Shixin Xu, and Wenrui Hao. An Imbalanced Learning-based Sampling Method for Physics-informed Neural Networks. Journal of Computational Physics 534 (2025): 114010.
8、Jiaqi Luo, Yuan Yuan, and Shixin Xu. TIME: TabPFN-Integrated Multimodal Engine for Robust Tabular-Image Learning. arXiv:2506.00813
9、Jiaqi Luo, Yuedong Quan, and Shixin Xu. Robust-GBDT: Leveraging Robust Loss for Noisy and Imbalanced Classification with GBDT. Knowledge and Information Systems. 67(12) (2025): 12361-12381.
10、Jiaqi Luo, Shixin Xu, and Zhouwang Yang. Efficient Global-Local Fusion Sampling for Physics-Informed Neural Networks. arXiv:2510.24026
11、Ruizhe Liu and Jiaqi Luo. TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes. arXiv:2605.14915
12、Jiaqi Luo. Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning. arXiv:2606.11682
13、Jiaqi Luo and Shixin Xu. TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data. arXiv:2607.10077
