Machine learning provides us a new tool set and, more importantly, a new way of thinking about many-body physics. I will first give a pedagogical introduction to machine learning and review its recent applications in many-body physics with personal remarks. Then, I will present several key models and techniques of machine learning on blackboard. Finally, I will talk about our efforts hinge on the question: Can we make new scientific discovery and invent new efficient algorithms with machine learning ? Our answer: YES, hopefully.
Lei Wang received his Bachelor degree in physics in 2006 from Nanjing university. In 2011, he received his PhD degree in theoretical physics from the Institute of Physics, Chinese Academy of Sciences. He works as a postdoctoral researcher in the computational physics group of ETH Zurich from 2011 to 2016. Since 2016, he starts to work as an assistant professor in the Institute of Physics, Chinese Academy of Sciences. His Erdős number is 2.