Joshua Yao-Yu Lin

DyAb predicts antibody properties and designs new sequences with high binding affinity using a low-data approach.

Property Enhancer optimizes antibody properties using a data-efficient framework, achieving significant affinity gains in both in silico and in vitro tests.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

Diffusion histology imaging noninvasively and accurately detects and grades prostate cancer.

This paper introduces a novel Diffusion Histology Imaging (DHI) approach combining DBSI and machine learning to improve detection and classification of glioblastoma histopathology features.

This paper introduces DHI, a method combining diffusion basis spectrum imaging and deep neural networks to classify pediatric brain tumor histology with high accuracy.