Prof. Xiang Li has been included in Elsevier’s 2016 “Most Cited Chinese Researchers (中国高被引学者)”, a listing of 1774 most influential Chinese researchers. Prof. Li has been listed in the field of “Electrical and Electronic Engineering”. He also has been included in 2015 and 2014 “Most Cited Chinese Researchers” .
Get the entire list of 2016 “Most Cited Chinese Researchers” in Electrical and Electronic Engineering.
See the news released in Elsevier Webpage.
Recently, the science news website Phys.org has introduced our work entitled “Encounters with ‘familiar strangers’ play overlooked role in human interactions”.
Click to view the full news.
The associated article has been published by Europhysics Letters in 2016.
More details can be found in the article L. Di, X. Li (correspondence author), Y.Q. Zhang. Identifying familiar strangers in human encounter networks, EPL, 2016, 116, 18006.
DOI: 10.1209/0295-5075/116/18006
Abstract:
Familiar strangers, pairs of individuals who encounter repeatedly but never know each other, have been discovered for four decades yet lack an effective method to identify. Here we propose a novel method called familiar stranger classifier (FSC) to identify familiar strangers from three empirical datasets, and classify human relationships into four types, i.e., familiar stranger (FS), in-role (IR), friend (F) and stranger (S). The analyses of the human encounter networks show that the average number of FS one may encounter is finite but larger than the Dunbar Number, and their encounters are structurally more stable and denser than those of S, indicating the encounters of FS are not limited by the social capacity, and more robust than the random scenario. Moreover, the temporal statistics of encounters between FS over the whole time span show strong periodicity, which are diverse from the bursts of encounters within one day, suggesting the significance of longitudinal patterns of human encounters. The proposed method to identify FS in this paper provides a valid framework to understand human encounter patterns and analyse complex human social behaviors.
日前, 童东兵博士获国家自然科学基金面上项目立项支持. 课题名称为《鞅驱动的随机神经网络自适应状态估计与最优控制》
Baoyu Hou has passed his mid-term evaluation for the PhD programme. His supervisors are Porf. Xiang Li and Prof. Guanrong Chen.
Prof. Mario di Bernardo also attended the evaluation, as well as Dr. Cong Li and other students of the CAN lab.
HOU Baoyu has been awarded the Best Student-Paper Award in the 12th Chinese Conference on Complex Network, 2016, Shanxi.
Professor Mario di Bernardo from the University of Naples Federico II, Italy gave invited talks at 9:00 am. Oct. 19th 2016, at Room 521, Henglong Physics Building, Fudan Campus.
The topics were “Synchronization and Control of Networks with Dynamic Links, Multiplex and Adaptive Structures” and “Convergence and Synchronization in Piecewise Smooth Networks”. The poster is as attachment.
mario_20161019_invitedtalk
After the lecture, Prof. Bernardo received the certificate of being the concurrent professor of Fudan University from Prof. Li.
In the afternoon, Prof. Bernardo attended the CAN lab seminar.
