Haochuan Cui

 we study the evolution processes on citation networks to exploit the hidden microscopic information. Instead of considering the citation speed and total number of citations, we develop a new approach to predict the future popularity of papers based on their early local structure, which contains its references and early citation. By using the data obtained from the American Physical Society citation networks, we found that our method outperforms the accurate short-term extrapolation and identifies the potentially popular items long before they become prominent. (Chinese Systems Science Conference, 2017.5)

We propose a method using local diffusion process on citation networks to identify the key references for each scientific publication.The effectiveness and robustness of the method is validated in a subset of the American Physical Society data in which the key references are mentioned in the abstract of papers. We further define an effective citation metric for quantifying the actual impact of each paper and its evolution, which additionally reveals the interdisciplinarity of research at journal and nation levels. ( under review )

When  quntifying the impact of a scientist, most methods ignore the impact of other members in the team. Here, we proposes a team-based model to modify Q model.It considers the collaboration fator in a scientific research and emphasize the importance of teamwork. Not only our method can predict the paper's impact, but also it can quantify the cooperative preference for every scientist based on data. This model can help scientist choose collaborater much more scientific. It can also help to quantify the impact of a teamwork. (Chinese Network Science, 2019)

In this topic, I try to answer a series of questions, such as how a scientific field identify itself and separate it from the others, how it lost itself and is annexed by another field and the processing that practical article is driven by the theoretical article to explore the knowledge space and the interaction.