Beijing University of Posts and Telecommunications is a prestigious public university established in 1955 in China. It is represented by 853 scientists in the AD Scientific Index. The university’s scientists are particularly concentrated in Engineering & Technology (489 scientists), Natural Sciences (27 scientists), and Social Sciences and Humanities (12 scientists).

Total 4 scientist
* Total H Index Rankings
Ranking Based On Selection :1
Bin Wu (武斌)
Evolutionary Game Theory
Population Dynamics
Complex Systems
Biological Modelling
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
49
41
0.837
* Total H Index Rankings
Ranking Based On Selection :2
Changwei Huang
Evolutionary Game Theory Opinion Dynamics Statistical Physics Complex Networks
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
15
15
1.000
* Total H Index Rankings
Ranking Based On Selection :3
Hongyan Cheng
Evolution of Cooperation
Game Theory
Complex Networks
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
14
11
0.786
* Total H Index Rankings
Ranking Based On Selection :4
Xingru Chen|陈 星如
evolutionary game theory
public health
reinforcement learning
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
6
6
1.000
* Total H Index Rankings
Rankings
Ranking Based On Selection: 1
Bin Wu (武斌)
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
49
41
0.837
Evolutionary Game Theory
Population Dynamics
Complex Systems
Biological Modelling
* Total H Index Rankings
Rankings
Ranking Based On Selection: 2
Changwei Huang
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
15
15
1.000
Evolutionary Game Theory Opinion Dynamics Statistical Physics Complex Networks
* Total H Index Rankings
Rankings
Ranking Based On Selection: 3
Hongyan Cheng
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
14
11
0.786
Evolution of Cooperation
Game Theory
Complex Networks
* Total H Index Rankings
Rankings
Ranking Based On Selection: 4
Xingru Chen|陈 星如
H-Index Metrics
Total
Last 6 Years
Last 6 Years / Total
6
6
1.000
evolutionary game theory
public health
reinforcement learning