Chenghong Wang, assistant professor of Computer Science at the Luddy School of Informatics, Computing, and Engineering, has received a National Science Foundation grant for CICI: UCSS:SciPDF: Usable private data federation for secure scientific collaboration.
Wang is principal investigator for the $599,649 grant, which begins Oct. 1 and runs through September of 2027.
The research centers on Private Data Federations (PDFs), which are emerging systems that allow different groups to work together on private data while keeping that data safe and confidential.
Wang said PDFs provide end-to-end privacy throughout the entire process, but their adoption within the scientific community remains limited due to a substantial usability gap because these systems often require expertise in security and system fundamentals.
“SciPDF democratizes this complex PDF pipeline by making cutting-edge PDF features accessible to the general scientific research community without the need for specialized expertise,” he said. “This work significantly lowers the barriers to research collaboration in critical domains, including healthcare, biomedicine, federal statistics, finance, and criminal investigations.”
Wang said the research findings are part of a comprehensive education, dissemination, and outreach plan that includes new graduate and undergraduate courses, mentoring of students, especially underrepresented minorities, and open-source tutorials accessible to the public.
Wang’s grant has four main research areas:
The design of an innovative self-sustaining query optimizer that autonomously handles complex PDF optimization primitives across various workloads.
The design and implementation of a full-fledged compiler to automatically translate logical queries into various PDF secure protocols.
The construction of high-level interfaces for system tuning, enabling non-expert administrators to fine-tune a PDF system with digestible policies and reason about the trade-offs between domain-specific research goals and privacy concerns.
The assembly of a complete prototype system, benchmarked with real-world scientific workloads and evaluated via usability studies.
“It is exciting that Professor Wang has received this NSF grant to advance his research on data privacy federation, along with his students,” said Yuzhen Ye, Computer Science chair and professor of Informatics and Computer Science. “The system they aim to develop will make secure collaboration involving sensitive data more accessible, creating substantial impacts across various applications.”
The National Science Foundation supports fundamental research and education in all non-medical fields of science and engineering. It promotes the progress of science, advances national health and prosperity, and secures the national defense.