Jianquan Zhao

This paper introduces OCDesign, a curriculum-guided framework for multi-property protein design, showing that staged objective introduction improves success rates compared to one-shot optimization.

ProAffinity++ predicts protein-protein binding affinities using sequence and structure representations, outperforming existing methods in accuracy and handling complex cases like antigen-antibody interactions.

This paper introduces NeuralNJ, a deep learning method for phylogenetic inference that improves accuracy and efficiency by using an end-to-end framework and reinforcement learning.