Ming Jin
PhD Candidate @ Monash University
I am a final-year Ph.D. Candidate at Monash University under the supervision of Prof. Shirui Pan and A/Prof. Yuan-Fang Li. Before this, I obtained my Bachelor’s and Master’s degrees from Hebei University of Technology and University of Melbourne in 2017 and 2019.
Previously, I also worked as Research Engineer at Metso Outotec and Research & Teaching Assistants at Monash University.
I am dedicated to conducting high-impact research and open for collaborations 🤗. My research interests are in (1) time series analysis, (2) graph neural networks, and (3) multimodal learning, with a special focus on temporal settings (e.g., GNNs & FMs & LLMs for time series and spatio-temporal data) in solving both fundamental and real-world problems.
News
| Apr 7, 2024 | [Paper] Our survey “Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects” has been accepted by IEEE TPAMI (IF 23.6) 🎊🥳 |
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| Apr 6, 2024 | [Talk] I am honored to be invited by Talk on MLLM to give a talk on the topic of Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. 👉 [Slide] |
| Feb 18, 2024 | [Paper] Our research “Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective” is now on arXiv ✨ |
| Feb 5, 2024 | [Paper] Our position paper “What Can Large Language Models Tell Us about Time Series Analysis” is now on arXiv 💭 |
| Jan 17, 2024 | [Paper] Our research “Time-LLM: Time Series Forecasting by Reprogramming Large Language Models” has been accepted by ICLR 2024 🎊🥳 |
| Jan 11, 2024 | [Paper] Our research “Graph Spatiotemporal Process for Multivariate Time Series Anomaly Detection with Missing Values” has been accepted by Information Fusion (IF 18.6) 🎊🥳 |