November 08, 2026
FS-GNN Paper Accepted by IEEE BigData 2026 Special MLBD Session
A paper jointly written by lab RA Zeyang Zhang, lab manager Jae Yeon (Jane) Pyo and lab director Pierre Jinghong Liang, "Learning from Flow-Graph Panel: Temporal Graph Neural Network for Predicting Financial Outcomes," has been accepted to the 11th IEEE Special Session on Machine Learning on Big Data (MLBD 2026), co-located with the 2026 IEEE International Conference on Big Data. The paper develops temporal graph neural-network methods for predicting financial outcomes from flow-graph panels. The authors will present the work at MLBD 2026 in Phoenix, Arizona, December 14-17. Accepted papers will appear in the official IEEE BigData 2026 proceedings. A high-level schematics of the paper's idea is show in this figure.
**Conference link:** < https://bigdataieee.org/BigData2026/calls/special-machine-learning/ >
Zeyang Zhag: paper lead author
About IEEE BigData 2026
The IEEE International Conference on Big Data convenes researchers, practitioners and industry participants working on methods and applications for large-scale data. IEEE BigData 2026 will take place in Phoenix, Arizona, December 14-17. Its 11th Special Session on Machine Learning on Big Data (MLBD) focuses on machine-learning methods, systems and applications for big-data settings, including graph and temporal data. More information is available at the [MLBD 2026 special-session page](https://bigdataieee.org/BigData2026/calls/special-machine-learning/).