Research fellow at the University of New South Wales’ City Futures Research Centre. He has been involved in several research and industry-based projects that focus on developing machine learning and deep learning models for time series modelling and Natural Language Processing. His research interests include probabilistic time series forecasting, long-term time series forecasting and anomaly detection.

Education

• PhD in Computer Science (03/2019 - 06/2022)
  • University of Sydney
  • Thesis: Deep Learning for Time Series Forecasting
• BEng (Hons) in Electrical Engineering (07/2015 - 12/2018)
  • University of Sydney
  • Honours Class I and the University Medal

Publications

You can find my full publication list on Google Scholar.

1. Progressive neural network for multi-horizon time series forecasting
   Yang Lin
   Information Sciences, 2024
   [PDF]
   
2. AMLNet: Adversarial Mutual Learning Neural Network for Non-AutoRegressive Multi-Horizon Time Series Forecasting
   Yang Lin
   International Conference on Data Science and Advanced Analytics (DSAA), 2023
   [PDF]
   
3. SSDNet: State Space Decomposition Neural Network for Time Series Forecasting
   Yang Lin, Irena Koprinska, Mashud Rana
   International Conference on Data Mining (ICDM) (regular paper), 2021
   [PDF] [Code]
   
4. Temporal Convolutional Attention Neural Networks for Time Series Forecasting
   Yang Lin, Irena Koprinska, Mashud Rana
   International Joint Conference on Neural Networks (IJCNN), 2021
   [PDF] [Code]
   
5. SpringNet: Transformer and Spring DTW for Solar Power Forecasting
   Yang Lin, Irena Koprinska, Mashud Rana
   International Conference on Neural Information Processing (ICONIP), 2020
   [PDF]
   
6. Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning
   Yang Lin, Irena Koprinska, Mashud Rana
   International Conference on Artificial Neural Networks (ICANN), 2020
   [PDF]
   
7. Temporal Convolutional Neural Networks for Solar Power Forecasting
   Yang Lin, Irena Koprinska, Mashud Rana
   International Joint Conference on Neural Networks (IJCNN), 2020
   [PDF]
   
8. Pattern Sequence Neural Network for Solar Power Forecasting
   Yang Lin, Irena Koprinska, Mashud Rana, Alicia Troncoso
   International Conference on Neural Information Processing (ICONIP), 2019
   [PDF]
   
9. Novel Piecewise Linear Formation of Droop Strategy for DC Microgrid
   Yang Lin, Weidong Xiao
   IEEE Transactions on Smart Grid, 2019
   [PDF] [Code]
   
10. Hardware-in-the-loop Implementation of a Hybrid Circuit Breaker Controller for MMC-based HVDC Systems
    Yang Lin, Harith R Wickramasinghe, Georgios Konstantinou
    IEEE PES Asia-Pacic Power and Energy Engineering Conference (APPEEC), 2018
    [PDF]
    

Contact

Email: linyang1997@yahoo.com.au;