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Haochuan Cui

Ph.D. student  @ School of Systems Science, Beijing Normal University


I'm a Ph.D. Student at School of Systems Science, Beijing Normal University. My recent research focus on the evolution of the knowledge systems,such as  how new ideas emerge and how they become the mainstream . I use complex network analysis, statistic modeling to explore the real world. 



Mathematics and Applied Mathematics, Anhui University, 2012.09-2016.07

I participated many mathematical modeling competition
First prize in the China Undergraduate Mathematical Contest in Modeling 2015
Meritorious Winner of the Interdisciplinary Contest In Modeling 2014&2015


Systems Theory, Beijing Normal University , 2016.09 - present

I study the scientists behaviors through Big Data. And my work is to help young sicentists get funded  more equally and help new scientific communities become more sustainable.


Visiting student, Arizona State University, 2018.01-2018.02

I visited Arizona State University and completed the ASU intensive winter school on complex systems during  Jan 11 - Feb 11 , 2018. I studied the history of the city's innovation under Dr. Sander's advising.  



familiar with the following programming languages, Python, Matlab, R 

Mathematical modeling

good at mathematical modeling and statistical modeling

  Deep Thinking

A cup of tea and
keep daily thinking

Research Topics

Predicting the popularity of scientific publication based on early structure


 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)

The direct inspiration source of scientific publications


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 )

Quantifying Team's impact in scientific systems


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)

Evolution of the Scientific System


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.



I joined in the project to provide Education Data Service for Chinese Government. It is leaded by iflyTek. Co & CIT@BNU


Address:    Beijing Normal University , No.19 XinJieKouWai St.,                     Haidian district, Beijing 100875, China

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