王龙博士，英国伦敦大学学院（University College London）杰出（Distinction）硕士，香港城市大学博士。主要从事机器学习、数据挖掘和计算机视觉及其工业应用等方面的研究。现为IEEE、IEEE工业电子学会和中国计算机学会会员，中国计算机学会计算机视觉专委会委员，是2014年香港政府博士奖学金（Hong Kong PhD Fellowship）获得者。目前担任SCI期刊IEEE Access (IF: 4.098) 和Canadian Journal of Electrical and Computer Engineering (IF: 1.53) 的副主编，PLOS ONE (IF: 2.776) 的学术编辑、编委，Intelligent Automation & Soft Computing (IF: 0.79) 和Water (2.524) 的客座编辑。

1.    L. Wang, Z. Zhang, and J. Chen, “Short-term Electricity Price Forecasting with Stacked Denoising Autoencoders,” IEEE Transactions on Power Systems, vol. 32, no. 4, July 2017. (IF: 6.807)

2.    L. Wang, Z. Zhang, H. Long, J. Xu, and R. Liu, “Wind Turbine Gearbox Failure Identification with Deep Neural Networks,” IEEE Transactions on Industrial Informatics, vol. 13, no. 3, pp. 1360-1368, June 2017. (IF: 7.377)

3.    L. Wang and Z. Zhang, “Automatic Detection of Wind Turbine Blade Surface Cracks Based on UAV-taken Images,” IEEE Transactions on Industrial Electronics, vol. 64, no. 9, 2017. (IF: 7.503)

4.    L. Wang, Z. Zhang, J. Xu, and R. Liu, “Wind Turbine Blade Breakage Monitoring with Deep Autoencoders,” IEEE Transactions on Smart Grid, vol. 9, no. 4, 2018. (IF: 10.486)

5.    L. Wang, Z. Zhang, and X. Luo, “A Two-stage Data-driven Approach for Image based Wind Turbine Blade Crack Inspections,” IEEE-ASME Transactions on Mechatronics, vol. 24, no. 3, pp. 1271-1281, 2019. (IF: 4.943)

香港研究资助局主题研究计划“Safety, Reliability, and Disruption Management of High Speed Rail and Metro Systems”，参与
香港研究资助局杰出青年学者计划“Scheduling Power Production of Hybrid Power Systems with Data Mining and Computational Intelligence”，参与。
横向项目：
丹麦Dong Energy公司项目“Wind Turbine Generation Performance Monitoring with Representation Learning”，主持

2017年香港城市大学Outstanding Academic Performance Award
2014年香港政府博士奖学金（Hong Kong PhD Fellowship）
2014年香港城市大学Chow Yei Ching School of Graduate Studies Entrance Scholarships