Ming Jin

Assistant Professor @ Griffith University

I am an incoming assistant professor at the School of Information and Communication Technology, Griffith University. Before joining Griffith, I was a Ph.D. candidate in the Faculty of Information Technology at Monash University, and expects to receive my Ph.D. degree in 2024.

I specialize in time series analysis and spatio-temporal data mining, with a good track record of publishing high-impact papers in top-ranked venues, including NeurIPS, ICLR, ICML, KDD, and IEEE TPAMI, among others.

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

May 25, 2024 [Tutorial] Our tutorial on Foundation Models for Time Series (FM4TS) has been accepted by KDD 2024 🎊🥳 See you in Barcelona! 🇪🇸
May 3, 2024 [Paper] Our position paper “What Can Large Language Models Tell Us about Time Series Analysis” has been accepted by ICML 2024 🎊🥳 See you in Vienna! 🇦🇹
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) 🎊🥳
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] [Video]
Feb 18, 2024 [Paper] Our research “Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective” 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 🎊🥳 See you in Vienna! 🇦🇹