Ming Jin

PhD Candidate @ Monash University

I am a Ph.D. Candidate in Computer Science at Monash University under the supervision of Prof. Shirui Pan and A/Prof. Yuan-Fang Li. Before this, I obtained my Bachelor’s degree and Master’s degree from Hebei University of Technology and The University of Melbourne in 2017 and 2019.

Also, I work as Research Engineer at Metso Outotec and Research Assistant at Monash University.

My research interests are in graph neural networks and geometric deep learning, with a special focus on temporal settings (e.g., dynamic graph neural networks) in solving real-world problems, e.g., time series forecasting, industrial process modeling, and anomaly detection.


Jan 17, 2023 [Call for Papers] Our special session titled Deep Learning for Graphs (DL4G) at IJCNN 2023 is now accepting submissions. The full paper deadline is 31 Jan 2023.
Nov 21, 2022 [Service] I will serve as a Program Committee member of IJCAI 2023
Nov 21, 2022 [Service] I will serve as a Program Committee member of PAKDD 2023
Oct 9, 2022 [Paper] Our paper “Multivariate Time Series Forecasting with Dynamic Graph Neural ODEs ” has been accepted by IEEE TKDE 🍻
Oct 9, 2022 [Award] I am honoured to receive a NeurIPS 2022 Scholar Award
Oct 4, 2022 [Paper] Our paper “Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming” has been accepted by IEEE TNNLS ✌️