Fei Li, Associate Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “Quantum Algorithms for High-Performance Analysis of Single-Cell Omics Data and Explainable Drug Discovery.”
This project leverages quantum computing to develop innovative, explainable methods for drug target discovery by integrating biological omics data—such as single-cell RNA sequencing (scRNA-seq) from disease tissue samples—with ex vivo drug screening results.
Li will tackle key computational challenges by developing QOTBox, the first quantum network computing platform tailored for high-performance analysis of single-cell omics data and explainable drug discovery.
QOTBox will offer exceptional scalability, efficiency, and accuracy, supporting system-level analysis of large, complex datasets. Li will demonstrate cutting-edge applications of quantum computing to reveal novel biological insights. The project will also introduce new quantum network analysis algorithms to power advanced computational biology, with expected breakthroughs in areas such as metabolism and the brain connectome.
These innovations promise broad biomedical impact, including more precise diagnostics, improved therapies, and a deeper understanding of complex biological systems—laying the groundwork for future advances in biology and medicine.
Li received a $100,000 grant from the National Science Foundation for this project. Funding began in September 2025 and will conclude in August 2027.