Rui Yuan
Higher Degree by Research Candidate
School of Electrical and Mechanical Engineering
Faculty of Sciences, Engineering and Technology
As a PhD candidate working on an industrial program, I'm commencing research aiming to develop, test, and verify statistical models based on machine learning techniques to quantify prosumers’ responsiveness to time-varying prices in real-time. My research interest includes Power and Energy System Engineering, Pattern Recognition, Data Mining, and Explainable Machine Learning in Power System. My other skills include forecasting and modelling (achieved 5th place in IEEE-CIS DATA CHALLENGE 2021), web development (served as web chair of the 32nd Australasian Universities Power Engineering Conference), and synthetic data generation (Synthetic dataset published in Scientific Data by Nature).
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Appointments
Date Position Institution name 2020 - 2020 Research Assistant RMIT University 2019 - 2020 Software Engineer Sage View Technology 2016 - 2017 Software Developer Intern China Unicom -
Education
Date Institution name Country Title 2017 - 2019 The University of Melbourne Australia Masters' degree in Electrical Engineering 2012 - 2016 Harbin Institute of Technology China Bachelors' degree in Telecommunication Engineering -
Certifications
Date Title Institution name Country 2020 AZ-900 Microsoft (United States) United States 2018 Certified Associate Network Engineer (JNCIA-Junos) Juniper Networks (United States) United States -
Research Interests
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Journals
Year Citation 2024 Yuan, R., Pourmousavi, S. A., Soong, W. L., Black, A. J., Liisberg, J. A. R., & Lemos-Vinasco, J. (2024). Unleashing the benefits of smart grids by overcoming the challenges associated with low-resolution data. Cell Reports Physical Science, 5(2), 18 pages.
2023 Yuan, R., Pourmousavi, S. A., Soong, W. L., Nguyen, G., & Liisberg, J. A. R. (2023). IRMAC: Interpretable Refined Motifs in Binary Classification for smart grid applications. Engineering Applications of Artificial Intelligence, 117, 105588.
Scopus4 WoS12023 Yuan, R., Pourmousavi, S. A., Soong, W. L., Black, A. J., Liisberg, J. A. R., & Lemos-Vinasco, J. (2023). A synthetic dataset of Danish residential electricity prosumers. Scientific Data, 10(1), 15 pages.
Scopus1 Europe PMC12023 Dinh, N. T., Karimi-Arpanahi, S., Yuan, R., Pourmousavi, S. A., Guo, M., Liisberg, J. A. R., & Lemos-Vinasco, J. (2023). Modelling Irrational Behaviour of Residential End Users using
Non-Stationary Gaussian Processes.2023 Yuan, R., Pourmousavi, S. A., Soong, W. L., Black, A. J., Liisberg, J. A. R., & Lemos-Vinasco, J. (2023). A New Time Series Similarity Measure and Its Smart Grid Applications. -
Conference Papers
Year Citation 2022 Kumar, Y. P. S., Yuan, R., Dinh, N. T., & Pourmousavi, S. A. (2022). Optimal activity and battery scheduling algorithm using load and solar generation forecasts. In 2022 32nd Australasian Universities Power Engineering Conference (AUPEC) Vol. abs/2210.12990 (pp. 1-6). Adelaide, SA. Aust: IEEE.
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Preprint
Year Citation 2024 Yuan, R., Pourmousavi, S. A., Soong, W. L., & Liisberg, J. A. R. (2024). Dynamic and Memory-efficient Shape Based Methodologies for User Type
Identification in Smart Grid Applications.
Teaching assistant for:
ELEC_ENG_2100 Digital System (FPGA)
ELEC_ENG_1102 Digital Electronics
ELEC_ENG_4100 Business Management Systems
Head of Teaching Assistants for:
COMP_SCI_7210 Foundations of Computer Science A
COMP_SCI_7211 Foundations of Computer Science B
Connect With Me
External Profiles
