Our research is mainly focusing on Automated, Efficient, and Explainable ML/DL, including:
Automated Machine Learning and Deep Learning
AutoML, Neural Architecture Search (NAS), Hyperparameter Optimization, Bi-Level Optimization, Meta-Learning, Continual Learning, GNN Structure Learning
Efficient Machine Learning and Deep Learning
Unstructured/Structured Neural Network Pruning, Knowledge Distillation
Explainable Machine Learning and Deep Learning
Influence Function based Explanations, Neural Tangent Kernel, High-dimensional Bayesian Optimization, Bayesian Deep Learning
Currently, my research interests are especially shifting from model to dataset. Looking forward to more collaboration in this direction.
I am fortunately co-supervising several Ph.D. students:
Hongrong Cheng (University of Adelaide, Neural Architecture Search and Network Pruning)
Xin Zheng (Monash University, AutoML in Graph Neural Network)
Xinle Wu (Aalborg University, Neural Architecture Search and Its Application on Time Series)
Kai Zhao (Aalborg University, Explainable Graph Neural Network on Time Series)
David Gonzalo Chaves Campos (Aalborg University, Model Compression on Time Series)