个人简介
李凌丰博士现任河套数学与交叉科学研究院（深圳）助理教授。在加入 HIMIS 之前，他在香港心脑血管健康工程中心担任副研究员，导师为陈汉夫教授（Prof. Raymond Chan）。他于2022年在香港浸会大学获得数学博士学位，导师为台雪成教授（Prof. Xue-Cheng Tai）和杨将教授。此外，他分别于罗格斯大学（Rutgers University）和中山大学获得金融数学硕士及应用数学学士学位。
研究兴趣
机器学习在科学计算中的理论与应用
图像处理问题中的变分模型与算法
教育经历
博士/2018-2022 香港浸会大学 专业：数学
硕士/2016-2018 罗格斯大学-新布朗斯维克分校 专业： 金融数学
本科/2012-2016 中山大学 专业： 数学与应用数学
工作经历
2026-至今 河套数学与交叉学科研究院（深圳） 助理教授
2022-2025 香港心脑血管健康工程研究中心 副研究科学家
荣誉奖项
2022 香港浸会大学亚坤研究生奖学金
出版物
1. Li, L., Liu, H., Tai, X. C., & Chan, R. H. (2026). New Ways to Construct Graph Neural Networks from Variational Models and Control Approaches. Accepted by Multiscale Modeling & Simulation.
2. Chu, Y. K., Li, L., Kang, S. H., Zhang, J., & Tai, X.-C. (2026). A Unified Variational Framework for Deep Weakly Supervised Image Segmentation. Journal of Mathematical Imaging and Vision, 68(5), 63.
3. Tai, X.-C., Liu, H., Li, L., & Chan, R. H. (2026). A Mathematical Explanation of Transformers. SIAM Journal on Imaging Sciences, 19(3), 1542～1568.
4. Zhang, H., Li, L., Tai, X. C., & Chan, R. H. F. (2025). Parametrized sampling for 3D blood simulation in deformable vessels using Physics-Informed Neural Networks. Journal of Computational and Applied Mathematics, 117197.
5. Zhang, K., Li, L., Liu, H., Yuan, J. & Tai, X. C. (2025). Deep convolutional neural networks meet variational shape compactness priors for image segmentation.Neurocomputing, 129395.
6. Tai, X. C., Liu, H, Chan, R. H. F., & Li, L. (2024). A mathematical explanation of UNet. Mathematical Foundations of Computing.
7. Li, L., Tai, X. C., & Chan, R. H. F. (2024). A new method to compute the blood flow equations using the physics-informed neural operator. Journal of Computational Physics, 113380.
8. Li, L., Tai, X. C., Yang, J., & Zhu, Q. (2024). A priori error estimate of deep mixed residual method for elliptic PDEs. Journal of Scientific Computing, 98(2),44.
9. Li, L., Tai, X. C., & Yang, J. (2022). Generalization error analysis of neural networks with gradient based regularization. Communications in Computational Physics, 32 (4), 1007-1038.
10. Tai, X., Li, L., & Bae, E. (2021). The Potts model with different piecewise constant representations and fast algorithms: a survey. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging: Mathematical Imaging and Vision, 1-41.
11. Li, L., Luo, S., Tai, X. C., & Yang, J. (2021). A level set representation method for N-Dimensional convex shape and applications. Communications in Mathematical Research, 37(2), 180.
12. Li, L., Luo, S., Tai, X. C., & Yang, J. (2021). A new variational approach based on level-set function for convex hull problem with outliers. Inverse Problems & Imaging, 15(2), 315.
13. Li, L., Luo, S., Tai, X. C., & Yang, J. (2019). A variational convex hull algorithm. In International Conference on Scale Space and Variational Methods in Computer Vision (pp. 224-235). Springer, Cham.
科研基金
(2026-2028) 香港研资局优配研究金LU13300125，1,071,000港元，图神经网络的数学建模与分析（Co-Inverstigator）
专利
1. 李凌丰;台雪成;陈汉夫;张元亭（2023）血管信息预测方法、装置、设备及存储介质[CN117257244A]. 中国国家知识产权局.
2. 陈翰杰;吕良一;李凌丰;张元亭（2023）基于PPG信号确定血压的方法、装置、设备及存储介质[CN117257256A]. 中国国家知识产权局.
学术报告
1. Hong Kong Joint Universities Conference on Structured Matrices and Scientific
Computing, September 25 - September 28, 2025, Hong Kong, China
2. International Conference on Applied Mathematics, Hong Kong, China, May 28 -
June 1, 2024
3. Second Ph.D. Student Seminar in Computational and Applied Mathematics, Beijing, China, September 2 - September 4, 2019.
4. Seminars of Mathematical Theories and Methods in Image Processing and Analysis,
Shenzhen, China, July 19 - July 22, 2019.
5. Seventh International Conference on Scale Space and Variational Methods in Computer Vision, Hofgeismar, Germany, June 30 - July 4, 2019.
期刊审稿
SIAM Journal on Imaging Science, Journal of Mathematical Imaging and Vision, Inverse Problem & Imaging, Partial Differential Equations and Applications