Project Grant 2624558

The National Science Foundation Office of Integrative Activities awarded the University of Louisiana at Lafayette $299,985 on January 1, 2027, under the Integrative Activities program (CFDA 47.083) to develop quantum-inspired vector symbolic architectures for biomedical big data processing.

The award funds a Research Infrastructure Improvement fellowship to an assistant professor and graduate student training, supporting research that combines quantum computing with compact, pattern-based information representations to improve analysis of large and complex biomedical datasets. The work examines how health records and genetic data can be summarized in forms that remain useful when information is incomplete or noisy. The project will establish a bidirectional quantum-vector symbolic architecture framework and contribute new methods for quantum-assisted hypervector generation, vector symbolic preprocessing for hybrid quantum machine learning, and robust multimodal data integration. Research activities include evaluating representation bias, correlation, separability, and crosstalk as symbol loads increase, and measuring task performance under data non-idealities and noise. Hardware-aware experiments will quantify qubit use, circuit depth, latency, and memory using Cleveland Clinic's quantum computing and biomedical workflow infrastructure.

Performance runs from January 1, 2027, through December 31, 2028, at Lafayette, Louisiana. The project will expand Louisiana's research capabilities, provide hands-on STEM student training, support university course materials, and produce openly available software workflows that integrate computer science, quantum information science, artificial intelligence, and biomedical data science. Work is conducted in collaboration with researchers at the Cleveland Clinic.