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欢迎各位有意从事机器学习算法研究的同学与我联系~

教育及工作经历：

1. 2020.08至今：南京信息工程大学人工智能学院，专任教师

2. 2015.09-2020.07：中国科学技术大学信息科学技术学院，工学博士

3. 2018.09-2019.09：Department of Electrical and Computer Engineering, George Mason University，联合培养

4. 2011.09-2015.06：华南理工大学自动化学院，工学学士

研究领域与主持课题：

主要从事分布式机器学习、优化算法的相关领域研究，目前在IEEE Transactions on Signal Processing，IEEE Transactions on Neural Networks and Learning Systems、ICASSP、CDC等国际知名期刊、重要会议上发表学术论文数篇，GoogleScholar同行引用百余次，部分参与项目如下：

1. 江苏省基础研究计划（自然科学青年基金项目），2021-2024，主持

2. 江苏省创新创业博士项目，2021-2024，主持

3. 人才启动经费资助项目，2021-2024，主持

教学工作：

承担《数字图像处理》、《机器学习》、《最优化方法》等多门人工智能专业课程教学工作。

发表论文：

1. Yaohua Liu, Gang Wu, Zhi Tian, and Qing Ling: “DQC-ADMM: Decentralized dynamic ADMM with quantized and censored communications,” IEEE Transactions on Neural Networks and Learning Systems, 2021. (IF: 8.79)

2. Yaohua Liu, Wei Xu, Gang Wu, Zhi Tian, and Qing Ling: “Communication-censored ADMM for decentralized consensus optimization,” IEEE Transactions on Signal Processing, vol. 67, no. 10, pp. 2565-2579, 2019. (IF: 5.03)

3. Qing Ling, Yaohua Liu, Wei Shi, and Zhi Tian: “Weighted ADMM for fast decentralized network optimization,” IEEE Transactions on Signal Processing, vol. 64, no. 22, pp. 5930-5942, 2016. (IF: 5.03)

4. Weiyu Li, Yaohua Liu, Zhi Tian, and Qing Ling: “Communication-censored linearized ADMM for decentralized consensus optimization,”IEEE Transactions on Signal and Information Processing over Networks, vol. 6, no. 1, pp.18-34, 2019. (IF: 3.15)

5. Yaohua Liu, Cameron Nowzari, Zhi Tian, and Qing Ling: “Asynchronous periodic event-triggered coordination of multi-agent systems,” In: Proceedings of the 56th Conference on Decision and Control (CDC), pp. 6696-6701, IEEE, 2017.

6. Yaohua Liu, Kun Yuan, Gang Wu, Zhi Tian, and Qing Ling: “Decentralized dynamic ADMM with quantized and censored communications,” In: Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers (ACSSC), pp. 1496-1500, IEEE, 2019.

7. Yaohua Liu, Wei Xu, Gang Wu, Zhi Tian, and Qing Ling: “COCA: Communication-censored ADMM for decentralized consensus optimization,” In: Proceedings of the 52nd Asilomar Conference on Signals, Systems, and Computers (ACSSC), pp.33-37, IEEE, 2018.

8. Qing Ling, Yaohua Liu, Wei Shi, and Zhi Tian: “Communication-efficient weighted ADMM for decentralized network optimization,” In: Proceedings of the 41st International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4821-4825, IEEE, 2016. 

9. Weiyu Li, Yaohua Liu, Zhi Tian, and Qing Ling: “COLA: Communication-censored linearized ADMM for decentralized consensus optimization,” In: Proceedings of the 44th International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5237-5241, IEEE, 2019.