Data management plan for the grant, "SaTC: CORE: Small: Probing Fairness of Ocular Biometrics Methods Across Demographic Variations."

Data management plan for the grant, "CICI: UCSS: Secure Containers in High-Performance Computing Infrastructure." Ensuring the security and privacy of high-performance computing (HPC) infrastructures is of utmost importance due to their handling of sensitive data and critical scientific computations. HPC infrastructures commonly employ containers, which provide lightweight and isolated environments for running applications. Nevertheless, containers in HPC infrastructures encounter security challenges, including insecure container images and vulnerabilities related to isolation. Existing container image scanners face a major challenge of low coverage, while current container runtimes struggle to ensure both security and performance for HPC workloads simultaneously. This project addresses these challenges by developing secure containers specifically tailored for HPC infrastructures. The project introduces innovative solutions, including the development of an efficient image vulnerability scanner and a secure container runtime.

Data management plan for the grant, "GenCyber Teachers Camp." The goal of the UNT GenCyber Teacher Camp is to increase the cybersecurity expertise of middle and high school Computer Science teachers so that they can introduce cybersecurity curriculum into their classrooms. We will recruit 20 teachers who teach Computer Science and STEM-related middle/high school courses. We will create modules that teachers can use to create positive environments for students and thus to motivate them to gain interest in cybersecurity.

Data management plan for the grant "Integrating multi-omics datasets to infer phenotype-specific driver genes, regulatory interactions and drug response." Research to develop open source integrative computational tools that perform secondary analysis of publicly available multi-omics biological, clinical and environmental exposure datasets to infer context-specific regulatory interactions and modules, and to predict disease associated genes and patient-specific drug response.