- Ph.D., Computer Application Technology, School of Computer Science and Technology, Tianjin University, Tianjin, China, 2016.
- B.Sc., Computer Science and Technology, School of Computer Science and Technology, Tianjin University, Tianjin, China, 2009.
Honors & Awards
- 2014 National Scholarship for Ph.D. Students, China
Lizhong Ding worked as a Postdoctoral research fellow at Prof. Xin Gao's Structural and Functional Bioinformatics Group (SFB) at King Abdullah University of Science and Technology (KAUST) during 2016-2018. Currently, Lizhong is a research scientist at the Inception Institute of Artificial Intelligence.
- Machine learning theory
- Impact of approximation on learning algorithms, especially discrepancy bounds between approximate and accurate learning, for kernel learning and deep learning
- Large scale machine learning
- Large scale matrix analysis/approximation
- Scalable model selection criteria and algorithms of statistical guarantees for kernel learning and deep learning
1. L. Ding and S. Liao, “An approximate approach to automatic kernel selection,” IEEE transactions on Cybernetics, Online, DOI:10.1109/TCYB.2016.2520582, 2016.
2. L. Ding and S. Liao, “Approximate consistency: Towards foundations of approximate kernel selection,” in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML PKDD), 2014, pp. 354–369.
3. L. Ding and S. Liao, “Model selection with the covering number of the ball of RKHS,” in Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM), 2014, pp. 1159–1168.
4. L. Ding and S. Liao, “Nyström approximate model selection for LSSVM,” in Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference (PAKDD), 2012, pp. 282–293.
5. L. Ding and S. Liao, “Approximate model selection for large scale LSSVM,” in JMLRW&CP 20 — Asian Conference on Machine Learning (ACML), 2011, pp. 165–180.