Main Research Interests Large-Batch Training Yong focus on Large-Batch Training on large-scale distributed systems. We can use Large-Batch Training to accelerate the training process of deep neural networks. Multi-Agent Systems Yong focus on simplification of learning process in multi-agent systems, i.e., game abstraction. The large number of agents and complex game relationship cause great difficulty for policy learning. Therefore, simplifying the learning process is an important research issue. Reinforcement Learning Yong focus on the algorithm framework of reinforcement learning and applications, especially in multi-agent systems. Reinforcement learning learn the policy through the feedback from environment, which is a way closer to the human model. I'm really interested in it. Transfer Learning Yong focus on the transfer learning in multi-agent systems, especially between environments with different number of agents. Policy learning is difficult in large-scale multi-agent systems. We use incremental learning and teansfer learning to solve the problem.