Zhiyuan (Leo) Zhao

mypic.jpeg

S1371CC

756 W Peachtree St NW

Atlanta, GA 30308

I’m a third-year Machine Learning Ph.D. student in Department of Computational Science and Engineering at Georgia Institute of Technology. I am affiliated with AdityaLab and advised by Dr. B Aditya Prakash. My research focuses on time-series forecasting with various techniques, such as attention, causality, physics-regularization, and LLMs. These research results have made real-world influences such as Flu and COVID-19 forecasting challenges organized by CDC.

I am also interested in pre-trained foundation models and applications of LLMs in time series tasks. Previously, my research spanned physics-informed neural networks with the advice of Prof. Aarti Singh and federated learning under the advice of Prof. Gauri Joshi at Carnegie Mellon University.

My current research focus includes:

  1. Out-of-distribution (OOD) generalization for time series;
  2. Time series fundation models and multi-modality time series forecasting;
  3. Time series forecasting in industrial application (with Amazon SCOT).

Selected Publications

  1. Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis
    Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, and 8 more authors
    Neural Information Processing Systems Datasets and Benchmarks Track, 2024
  2. Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning
    Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, and 3 more authors
    International Conference on Machine Learning, 2024
  3. LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting
    Zhiyuan Zhao, Haoxin Liu, Jindong Wang, and 2 more authors
    Findings of the Association for Computational Linguistics, 2024
  4. Performative Time-Series Forecasting
    Zhiyuan Zhao, Alexander Rodriguez, and B Aditya Prakash
    arXiv preprint arXiv:2310.06077, 2023
  5. PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks
    Zhiyuan Zhao, Xueying Ding, and B Aditya Prakash
    International Conference on Learning Representations, 2024
  6. A dynamic reweighting strategy for fair federated learning
    Zhiyuan Zhao, and Gauri Joshi
    In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022