一、个人简介：

郑重，男，讲师。博士毕业于香港城市大学数据科学系。研究方向为深度学习及其在时间序列数据分析和可再生能源领域的交叉应用。以第一作者身份在IEEE Transactions on Neural Networks and Learning Systems、IEEE Transactions on Power Systems、IEEE Transactions on Sustainable Energy、International Journal of Production Economics等高水平SCI/SSCI期刊发表论文8篇。

二、讲授课程：

本科生：《人工智能》、《Python与大数据分析》

三、研究成果：

发表论文：

[1] Zheng Z, Zhang Y. Predictive recurrent neural networks based carbon price forecasting: A generative perspective[J]. Computational Economics, 2025: 1-19.

[2] Zheng Z, Zhang Z. A stochastic recurrent encoder decoder network for multistep probabilistic wind power predictions[J]. IEEE Transactions on Neural Networks and Learning Systems, 2024, 35(7): 9565-9578.

[3] Zheng Z, Yang L, Zhang Z. Conditional variational autoencoder informed probabilistic wind power curve modeling[J]. IEEE Transactions on Sustainable Energy, 2023, 14(4): 2445-2460.

[4] Zheng Z, Zhang Z. A temporal convolutional recurrent autoencoder based framework for compressing time series data[J]. Applied Soft Computing, 2023, 147: 110797.

[5] Zheng Z, Zhang Z, Wang L, et al. Denoising temporal convolutional recurrent autoencoders for time series classification[J]. Information Sciences, 2022, 588: 159-173.

[6] Zheng Z, Wang L, Yang L, et al. Generative probabilistic wind speed forecasting: A variational recurrent autoencoder based method[J]. IEEE Transactions on Power Systems, 2021, 37(2): 1386-1398.

[7] Zheng Z, Qi H, Zhuang L, et al. Automated rail surface crack analytics using deep data-driven models and transfer learning[J]. Sustainable Cities and Society, 2021, 70: 102898.

[8] Zheng Z, Chen Z, Savaser S K. The implications of contract timing on a supply chain with random yield[J]. International Journal of Production Economics, 2021, 240: 108215.

四、获得荣誉：

1.东莞市三类特色人才

五、社会兼职：

1. IEEE Transactions on Sustainable Energy、Journal of Intelligent Manufacturing、 IEEE Transactions on Sustainable Energy匿名审稿人