赵婷婷，教授，硕士生导师，澳门9159游戏官网副院长，日本东京工业大学(Tokyo Institute of Technology)博士。天津市“131”第二层次人选及“中青年骨干创新人才培养计划”人选。主持承担国家自然科学基金面上项目、国家自然科学青年基金、教育部留学回国人员科研启动基金项目等纵向项目6项。近年来撰写专著1部，在机器学习领域发表论文60余篇，其中包括顶级国际期刊Neural Networks、Neural Computation及顶级国际会议论文NeurIPS、 IJCAI、ACML及ECML/PKDD。拥有核心专利，其中授权专利15项。产学研成果获山西省科学技术奖科技进步奖二等奖、中国商业联合会服务业科技创新奖一等奖、天津市科技进步三等奖、中国轻工业联合会技术进步奖、中国商业联合会科技进步奖三等奖等。主要研究领域为机器学习及智能信息处理，其中主要包括深度强化学习算法，智能控制及智慧医疗方面的应用。
3. Tingting Zhao, Hirotaka Hachiya, Gang Niu and Masashi Sugiyama. Analysis and improvement of policy gradient estimation. Neural Networks, 2012, 26: 118-129. （中科院1区Top）
4. Tingting Zhao, Shuai Wu, Guixi Li, Yarui Chen, Gang Niu, Masashi Sugiyama. Learning intention-aware policies in deep reinforcement learning, Neural Computation, 2023(35), 1657–1677 .（CCF-B类推荐期刊，影响因子2.9）
5. Tingting Zhao, Hirotaka Hachiya, Voot Tangkaratt, Jun Morimoto, and Masashi Sugiyama. Efficient sample reuse in policy gradients with parameter-based exploration. Neural Computation, 2013, 25:1512-1547. （JCR二区 ；CCF-B类）
6. Tingting Zhao∗, Guixi Li, Yajing Song, Yuan Wang, Yarui Chen, Jucheng Yang. A multi-scenario text generation method based on meta reinforcement learning. Pattern Recognition Letters, 2023,165: 47–54. （JCR 2区，影响因子5.1）
7. Tingting Zhao, YingWang，Guixi Li，LeKong，Yarui Chen，Yuan Wang，NingXie，JuchengYang. A model-based reinforcement learning method based on conditional generative adversarial network. Pattern Recognition Letters, 2021，152: 18-25. （JCR 2区，影响因子5.1）
8. Tingting Zhao, H. Hachiya, G. Niu and M. Sugiyama. Analysis and improvement of policy gradient estimation. Advances in Neural Information Proceeding System (NeurIPS 2011), pp.262-270, 2011. （CCF- A类推荐国际会议）
9.Ning Xie, Tingting Zhao*, Feng Tian, Xiaohua Zhang, Masashi Sugiyama. Stroke-based stylization learning and rendering with inverse reinforcement learning. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI 2015), pp.2531-2537, Buenos Aires, Argentina, Jul. 25-31, 2015.（CCF- A类推荐国际会议）
10.Tingting Zhao*, G. Niu, N. Xie, J. Yang and M. Sugiyama. Regularized policy gradients: Direct variance reduction in policy gradient estimation. Proceedings of the 7th Asian Conference on Machine Learning (ACML 2015),vol.45, pp.333-348, Hong Kong, China, Nov. 20-22, 2015. （CCF-C类推荐国际会议）
11. Haibo Li, Zhanshuo Liu, Tuo Zhao, Tingting Zhao*, Yarui Chen, Ning Xie. MS-RainMamba: Learning Multi-Scale State Space Models for Single Image Deraining. 2025 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2025).（CCF- B类推荐国际会议）
