Rate My Professor Ze Yang

In his academic career, Dr. Yang serves as a lecturer, teaching courses such as Neural Networks and Deep Learning (ECE4179) and Probability Models in Engineering (ECE2191). He has authored publications in high-impact journals including IEEE Transactions on Industrial Informatics and Soft Robotics, along with numerous conference papers. Notable recent works include 'Multi-Objective Optimization of Cloud Energy Storage Placement and Sizing in Peer-to-Peer Energy Market under Line Congestion' (2025, with J. Q. Ling, W. S. Tan, Y. K. Wu), 'ST-HCSS: Deep Spatio-Temporal Hypergraph Convolutional Neural Network for Soft Sensing' (2025, with H. H. Tew et al.), 'Transformer-based Deep Learning Model for Joint Routing and Scheduling with Varying Electric Vehicle Numbers' (2025, with J. K. Yap et al.), 'Cross-Domain Transfer Learning Using Attention Latent Features for Multi-Agent Trajectory Prediction' (2024, with J. Q. Loh et al.), and 'Deep Learning Based Hybrid Assisted Stochastic Unit Commitment with Transportable Energy Storage' (2024, with J.-S. Chia, W.-S. Tan, Y.-K. Wu), all presented at IEEE conferences. Dr. Yang is accepting PhD students in deep learning, industrial AI, soft sensors, machine intelligence, and autonomous systems. His research supports UN Sustainable Development Goals such as good health and well-being, affordable and clean energy, and sustainable cities and communities.