Hao Wang

Hybrid mechanistic-machine learning models in biosciences: causality, forecasting, and lab-to-field translation.

Biological and environmental systems rarely present a clean choice between first-principles equations and black-box learning. More often, core mechanisms such as disease progression, conservation relations, reaction stoichiometry, or transport direction are known, while key drivers such as behavior, regulation, unresol...

Spatial Decision Support for Controlled Environment Agriculture in Cold Regions: Evidence from Alberta, Canada

Learning PDE Time-Stepping with Neural Cellular Automata

This paper proposes a trainable Neural Cellular Automata (NCA) based surrogate model for learning long time PDE dynamics that achieves the lowest long-horizon relative errors on the majority of the experiments.