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
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 & Healthcare
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
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
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, 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.
9、Jiaqi Luo, Shixin Xu, and Zhouwang Yang. Efficient Global-Local Fusion Sampling for Physics-Informed Neural Networks. arXiv:2510.24026
10、Ruizhe Liu and Jiaqi Luo. TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes. arXiv:2605.14915
11、Jiaqi Luo. Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning. arXiv:2606.11682
12、Jiaqi Luo and Shixin Xu. TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data. arXiv:2607.10077
13、Jiaqi Luo, Yuan Yuan, and Shixin Xu. TIMF: TabPFN-integrated multimodal framework for robust tabular-image learning. Neurocomputing 705 (2026) : 134975.
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
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 & Healthcare
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
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
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, 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.
9、Jiaqi Luo, Shixin Xu, and Zhouwang Yang. Efficient Global-Local Fusion Sampling for Physics-Informed Neural Networks. arXiv:2510.24026
10、Ruizhe Liu and Jiaqi Luo. TILBench: A Systematic Benchmark for Tabular Imbalanced Learning Across Data Regimes. arXiv:2605.14915
11、Jiaqi Luo. Parameter-Efficient Adapter Tuning for Tabular-Image Multimodal Learning. arXiv:2606.11682
12、Jiaqi Luo and Shixin Xu. TabLoRA: Parameter-Efficient Low-Rank Ensemble Learning for Large-Scale Tabular Data. arXiv:2607.10077
13、Jiaqi Luo, Yuan Yuan, and Shixin Xu. TIMF: TabPFN-integrated multimodal framework for robust tabular-image learning. Neurocomputing 705 (2026) : 134975.
