Epscor research fellows: NSF: quantum-inspired vector symbolic architectures for biomedical big data processing

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.

Abstract

This research infrastructure improvement (RII) epscor research fellows project provides a fellowship to an assistant professor and training for a graduate student at the university of louisiana at lafayette. This work is conducted in collaboration with researchers at the cleveland clinic. Through the fellowship, the PI will develop computing methods that combine quantum computing with compact, pattern-based representations of information to improve the analysis of large and complex biomedical datasets. The project will examine how health records and genetic data can be summarized in forms that remain useful when information is incomplete or noisy. The work will bring together computer science, quantum information science, artificial intelligence, and biomedical data science. IT will expand research capabilities in louisiana, provide hands-on stem student training, support university course materials, and produce openly available software workflows. These outcomes will strengthen the emerging computing workforce for biomedical research and data-driven health discovery. This project will establish a bidirectional quantum-vector symbolic architecture framework for large-scale biomedical data processing. IT will contribute new methods for quantum-assisted hypervector generation, vector symbolic preprocessing for hybrid quantum machine learning, and robust multimodal data integration. The research will evaluate representation bias, correlation, separability, and crosstalk as symbol loads increase, and will measure 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. The project will extend the host team's software ecosystem with biomedical encoders, quantum interfaces, benchmarking utilities, and workflows compatible with the galaxy biomedical analysis platform, producing an open-source toolkit for reproducible research. The fellowship will advance faculty expertise, train a graduate researcher, strengthen quantum and biomedical computing capacity at the university of louisiana at lafayette, support curriculum development, and establish a long-term research partnership with cleveland clinic. This project is supported by the epscor research infrastructure improvement program: epscor research fellows (ERF). The ERF program supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation?S private, government or academic research institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.