Scholar profiling from the open Internet has become a hot research topic in recent years. Its goal is to extract the attribute information of a scholar. Scholar profiling is a fundamental issue in large-scale expert databases for finding experts, evaluating academic influence, and so on. In the open Internet, scholar profiling faces new challenges, such as large amount of data, data noise and data redundancy. The traditional user profiling methods and algorithms cannot be directly used in the user profiling system in the open Internet environment. In this paper, the existing technologies are summarized and classified to provide reference for further research. Firstly, we analyze the problem of scholar profiling, and give a general overview of the information extraction method, which is the basic theory of user profiling. Then, the three basic tasks of scholar profiling including scholar information annotation, research interest mining and academic impact prediction are introduced in detail. What’s more, the successful application system of scholar profiling called AMiner is introduced. Finally, open research issues are discussed and possible future research directions are prospected.