Stephen J. Schuster

Deep learning representations of human Immune Health for precision immunology

The paper develops MAESTRO, a self-supervised deep learning framework to transform immune profiles into embeddings capturing immune health, enabling clinical prediction and precision immunotherapy.

Harnessing the CD2 axis to broaden and enhance the efficacy of CAR T cell therapies

This paper develops anti-CD2 CAR T-cells that overcome fratricide and improve efficacy by incorporating a PD-1:CD2 switch receptor to restore CD2 signaling.

Directed evolution-based discovery of ligands for in vivo restimulation of CAR-T cells

This study develops a method to generate optimized peptide ligands for CAR-T cell restimulation, demonstrating enhanced expansion and memory development in preclinical models.

A general approach to reduce off-target radioactivity in vivo via Tetrazine-Knock-Out (TKO)

This paper develops a method to rapidly clear radioactivity from blood using a tetrazine-knock-out (TKO) approach, improving imaging contrast and reducing radiation exposure.