Mr Ryan Zhang

Postdoctoral Research Fellow

School of Information Technology and Electrical Engineering
Faculty of Engineering, Architecture and Information Technology

Overview

Dr. Ruiyuan Zhang is a Postdoctoral Research Fellow in Data Science and Analytics at the Centre for Energy Data Innovation (CEDI) of the University of Queensland (UQ). He also works as the Data Scientist at Redback Technologies. His research works are mainly focusing on energy generation/consumption forecasting, energy smart management, machine learning/deep learning and cloud computing.

Dr. Zhang received his PhD degree from UQ in 2021. Previously, he obtained his Bachelor degree from Tongji University in 2012, China and Master's degree from RWTH Aachen University, Germany in 2015.

Research Impacts

Dr. Zhang is keen on bridging the gap between advanced algorthim and real application of renewable energy. Australia has confirmed it is seeking to get to net zero emission by 2050. Fully utilizing renewable energy is vital to achieve such goal. Dr. Zhang has committed himself to miximizing the value of the energy data for the related industries and and society. His research works are focusing on reducing the unnecessary waste of energy and improving the efficiency of energy utilization .

Qualifications

  • Doctor of Philosophy, The University of Queensland

Publications

View all Publications

Publications

Journal Article

Conference Publication

  • Zhang, Ruiyuan, Ma, Hui, Saha, Tapan Kumar and Zhou, Xiaofang (2020). On sky imaging analysis and deep learning for photovoltaic output nowcasting. 2020 IEEE Power & Energy Society General Meeting (PESGM), Montreal, QC Canada, 2-6 August 2020. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/pesgm41954.2020.9281668

  • Ruan, Boyu, Hua, Wen, Zhang, Ruiyuan and Zhou, Xiaofang (2017). Decomposition-based approximation of time series data with max-error guarantees. 28th Australasian Database Conference, ADC 2017, Brisbane, QLD, 25-28 September 2017. Heidelberg, Germany: Springer Verlag. doi: 10.1007/978-3-319-68155-9_6