My projects in explainable AI aims to make today’s powerful models genuinely understandable to humans, and to use those explanations to advance machine learning for scientific discovery.
2025 to Present
From Interpretability to Explainability
Explaining the model training procedure that transforms interpretation into explanation.
View project
2024 to Present
Interpretable TCR-Epitope Prediction
Interpretable models for predicting and interpreting how T-cell receptors recognize peptide-MHC complexes.
View project
2024 to Present
Antigen Processing Prediction Acceleration
GPU-accelerated modeling of antigen processing to predict CD4+ T-cell epitopes.
View project