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Sai Reddy is an Associate Professor (since 2018) at ETH Zurich in the Department of Biosystems Science and Engineering, located in Basel, Switzerland. His research centers on systems, synthetic, and computational immunology, with a focus on developing technologies that impact immunotherapy and biotechnology.  Sai Reddy also serves as the Scientific Director of the Botnar Institute of Immune Engineering (BIIE), a newly established non-profit organization dedicated to advanced research in immunology for translational medicine and health.

Antibody discovery has relied on experimental screening – hybridoma, phage display, yeast display – powerful technologies that remain fundamentally brute-force. The field still lacks a computational method that reliably predicts, from sequence alone, which antibodies bind which antigens. We are developing CALM (Cross-attention Adaptive Immune Receptor-Antigen Language Model), a sequence-based architecture that learns antibody-antigen specificity through contrastive learning in a shared embedding space. Early results demonstrate that the model captures generalizable features of binding specificity with notable data efficiency, and that training data diversity is the key driver of generalization performance. Guided by a theoretical framework connecting the mathematics of immune recognition to transformer architectures, we outline a path toward immune specificity foundation models – systems capable of computationally predicting and designing antibody sequence-to-specificity at repertoire scale, complementing and potentially transforming existing discovery workflows.