陈超，男，博士研究生。
教育经历：2012年-2016年本科就读于大连海事大学；2019年至今就读于埃因霍芬理工大学联合培养博士；2016年至今就读于大连理工大学硕博连读(保送)。
研究领域：交通行为、城市规划、群体智能算法。
教学经历：主要承担《交通流理论》《交通管理与控制》等课程的教学工作。
主要成果：（部分发表论文）
[1] Yao B, Chen C, Cao Q, et al. (2017). Short‐term traffic speed prediction for an urban corridor[J]. Computer‐Aided Civil and Infrastructure Engineering, 32(2): 154-169.(SCI, JCR Q1, ESI, IF: 11.775,引用: 167次)
[2] Yao B, Chen C, Zhang L, et al. (2019). Allocation method for transit lines considering the user equilibrium for operators[J]. Transportation Research Part C: Emerging Technologies, 105:666-682. (SCI, JCR Q1, ESI, IF:8.089,引用: 24次)
[3] Chao C, Zhihui T, Baozhen Y. (2019). Optimization of two-stage location–routing–inventory problem with time-windows in food distribution network[J]. Annals of Operations Research, 273(1-2):111-134. (SCI, JCR Q1, IF: 4.854,引用: 44次)
[4] Yao B, Chen C*, Song X, et al. (2019). Fresh seafood delivery routing problem using an improved ant colony optimization[J]. Annals of Operations Research, 273(1): 163-186.(SCI, JCR Q1, IF: 4.854,引用: 30次)
[5] Shan W, Yan Q, Chen C, et al. (2019). Optimization of competitive facility location for chain stores[J]. Annals of Operations Research, 273(1-2): 187-205.(SCI, JCR Q1, ESI, IF: 4.854,引用: 37次)
[6] Chen, C, Feng, T., Gu X. (2022) Role of latent factors and public policies in travel decisions under COVID-19 pandemic: Findings of a hybrid choice model [J]. Sustainable Cities and Society,78:103601. (SCI, JCR Q1, IF:7.587)
[7] Chen, C, Feng, T., Ding, C., et al. (2021). Examining the spatial-temporal relationship between urban built environment and taxi ridership: Results of a semi-parametric GWPR model[J]. Journal of Transport Geography, 96, 103172. (SCI, JCR Q1, IF:4.986)
[8] Chen, C., Feng, T., Gu, X., & Yao, B. (2022). Investigating the effectiveness of COVID-19 pandemic countermeasures on the use of public transport: A case study of The Netherlands. Transport policy, 117: 98-107. (SCI, JCR Q1, IF: 4.674)
[9] Chen C, Wang H, Yuan F, et al. (2020). Bus travel time prediction based on deep belief network with back-propagation[J]. Neural Computing and Applications, 32(14): 10435-10449.(SCI, JCR Q1, IF:5.606)
