I currently serve as an Assistant Professor and Master’s Supervisor at the School of Computer Science and Technology, Harbin Engineering University. I graduated in 2023 from the School of Computer Science and Technology, Harbin Institute of Technology. My research focuses primarily on Deep Reinforcement Learning, Intelligent Software Engineering, and Mobile Edge Computing，committed to applying existing artificial intelligence technologies to practical scenarios. Contact me by email zhaoyingnan@hrbeu.edu.cn.

Education

2017-2023 PhD in Computer Science, Harbin Institute of Technology
2021-2022 Visiting scholar in University of Alberta
2015-2017 MS in Computer Science, Harbin Institute of Technology
2011-2015 BS in Software Engineering, Harbin Institute of Technology

Publications

1. Ke Sun, Yingnan Zhao, Wulong Liu, Bei Jiang, Linglong Kong. Distributional Reinforcement Learning with Regularized Wasserstein Loss. Advances in Neural Information Processing Systems (NeurIPS), 2024, CCF-A
2. Ke Sun, Yingnan Zhao, Linglong Kong* et al. Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observation. ECML-PKDD, 2023, CCF-B
3. Yingnan Zhao, Peng Liu, Wei Zhao. et al. Variational Diversity Maximization for Hierarchical Skill Discovery. Neural Process Lett, 2023
4. Wenshan Wang, Guoyin Zhang, Qingan Da, Dan Lu, Yingnan Zhao*.Multiple Unmanned Aerial Vehicle Autonomous Path Planning Algorithm Based on Whale-Inspired Deep Q-Network, 2023
5. Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, et al. Damped Anderson mixing for deep reinforcement learning: Acceleration, convergence, and stabilization. Advances in Neural Information Processing Systems(NeurIPS), 2021, CCF-A
6. Chenjia Bai, Peng Liu, Kaiyu Liu, Yingnan Zhao, et al. Variational dynamic for self-supervised exploration in deep reinforcement learning. IEEE Transactions on neural networks and learning systems, 2021, CCF-B
7. Yingnan Zhao，Peng Liu, Chenjia Bai, Wei Zhao*, Xianglong Tang. Obtaining accurate estimated action values in categorical distributional reinforcement learning. Knowledge-Based Systems, 2020
8. Chenjia Bai, Peng Liu, Yingnan Zhao, et al. Generating attentive goals for prioritized hindsight reinforcement learning[J]. Knowledge-Based Systems, 2020
9. 赵英男,刘鹏,赵巍*,唐降龙. 深度 Q 学习的二次主动采样方法.自动化学报, 2019, CCF-A中文期刊
10. Peng Liu, Yingnan Zhao, Wei Zhao*, Xianglong Tang，Zichan Yang. An exploratory rollout policy for imagination-augmented agents. Applied Intelligence, 2019

Teaching

1. 2023-2024, Fall, Operating System.
2. 2023-2024, Fall, Artificial Intelligence.
3. 2022-2023, Spring, C Pprogramming Design.

Join us

Welcome to join us if you are interested in fields such as Artificial Intelligence, Reinforcement Learning, and Data Science， I am recruiting 2 – 3 MS students every year. Please send your resume to zhaoyingnan@hrbeu.edu.cn.