Yi Shi, PhD

The Shi Laboratory 

Yi Shi, PhD, is a Professor and Director of the Center for Protein Engineering and Therapeutics at the Icahn School of Medicine at Mount Sinai. He is a protein engineer, structural biologist, and biologics platform builder whose research integrates mass spectrometry-based proteomics, artificial intelligence, chemical biology, structural biology, and therapeutic engineering to transform natural immune repertoires into programmable medicines. His laboratory develops platforms for proteomics-scale nanobody discovery, AI-guided candidate selection, and modular biologics design, with applications across infectious disease, cancer, bacterial toxins, membrane proteins, and targeted therapeutic delivery.

Dr. Shi’s group has generated large repertoires of multi-epitope binders and antigen-specific nanobodies, creating experimental and computational resources that support antibody engineering, nanobody humanization, structural modeling, and therapeutic design. During the COVID-19 pandemic, his laboratory developed potent multivalent and inhalable nanobody candidates, as well as AMETA, a modular multi-epitope antiviral platform designed to retain activity against antigenically divergent variants. His broader work extends these principles to antitoxin biologics, pharmacokinetic engineering tools, receptor-directed delivery systems, and AI-enabled biologics discovery.

Before joining Mount Sinai, Dr. Shi earned his PhD from Baylor College of Medicine, where he studied proteomic approaches to protein ubiquitination, and completed postdoctoral training at The Rockefeller University, where he developed integrative structural proteomic methods to investigate large macromolecular assemblies. In 2017, he joined the University of Pittsburgh School of Medicine as an Assistant Professor and was recruited to Mount Sinai in 2022. Through his work in proteomics, nanobody discovery, and AI-enabled protein engineering, Dr. Shi aims to create innovative molecular tools and therapeutic platforms that accelerate biomedical discovery and enable more precise approaches to diagnosing and treating disease. He also trains scientists across experimental biology, AI, structural biology, protein engineering, intellectual property, and translation.