Ioannis N. Athanasiadis

The paper introduces SINN, a structured multimodal deep learning model that improves genomic prediction in new environments by combining statistical decomposition with deep learning, achieving higher accuracy than existing methods.

The paper develops a Physics-Informed Neural Network (PINN) for predicting plant height growth, showing improved accuracy over traditional models with limited data.

ChromaX simulates genetic recombination and breeding value calculations using GPU acceleration, offering faster performance than existing tools.