UC Irvine Researchers Lead $9 Million Project for National AI and Data Science Infrastructure

UC Irvine researchers, in collaboration with teams from UCLA and the University of Michigan, have been awarded nearly $9 million by the U.S. National Science Foundation. This funding establishes a new data infrastructure capability, known as NSF BRIDGE, designed to assist scientific communities across the nation in utilizing advanced data science and artificial intelligence tools.

The initiative is led by UC Irvine computer science professor Chen Li. Its core purpose is to enable scientific communities to deploy computing platforms specifically designed for their needs. These platforms will allow researchers to share datasets, analysis pipelines, and machine learning models collaboratively. The infrastructure is built upon the open-source Texera system, which was started in 2016 and is currently supported by the Apache Software Foundation. These specialized platforms can operate on public cloud services, such as Amazon Web Services, or on computing clusters managed by various research laboratories. A key benefit is that scientists can collaborate on data analysis and apply AI techniques without needing advanced IT or programming skills.

The current scientific landscape generates an immense volume of data across numerous fields, complemented by rapid advancements in AI. This combination presents opportunities to convert observations into actionable knowledge. NSF BRIDGE facilitates this transformation by dismantling technical barriers and integrating deep domain expertise with AI and large-scale computing capabilities.

Instead of requiring scientists to configure complex computing systems or write intricate scripts, NSF BRIDGE will allow scientific communities to deploy Texera as an online platform. This platform serves as a central hub where researchers can store data, share it with collaborators, and analyze it using integrated AI-powered tools. Researchers will be able to complete many tasks through visual dataflows and by giving plain-language instructions to AI agents, reducing the necessity to write code in programming languages like Python or R.

Professor Li, from UC Irvine’s Donald Bren School of Information & Computer Sciences, serves as the principal investigator for the three-year project. He stated that the goal is to transform how scientific communities use data science and AI, enabling "seamless knowledge sharing and collaboration without requiring programming expertise." The project extends more than a decade of open-source development through the Texera initiative.

Wei Wang, a co-principal investigator and professor of computer science at UCLA, noted that the Texera system offers a novel platform that makes state-of-the-art AI and machine learning techniques available across a wide range of scientific fields. Wang indicated that through Texera, NSF BRIDGE can "accelerate AI adoption in these fields and significantly benefit the nation."

Steve Parker, a senior personnel member and professor at the University of Michigan, provided an example of its application. He explained that with NSF BRIDGE support, the Texera system is being deployed to empower researchers in the bioinformatics domain who lack programming expertise. This enables them to build and share flexible workflows that integrate their own data with public resources. Parker said it will "bridge the gap between experimental research and computational analysis" to accelerate scientific discovery.

Additional co-principal investigators from UC Irvine include Ardalan Amiri Sani, also from the Donald Bren School of Information & Computer Sciences; Kristin Turney from the School of Social Sciences; and Rui Chen from the School of Medicine. Subawards for the project are directed to Wang and Naomi Sugie from UCLA’s College of Social Sciences, Michigan’s Parker, and the Research Cyberinfrastructure Center at UC Irvine.

The NSF BRIDGE team, having already collaborated with five scientific domains, is actively seeking new partners. These partners would be interested in leveraging the software system and services to enhance their research using data science and AI techniques.