OU’s Data Institute for Societal Change will sponsor three faculty projects to further develop science-based research involving AI technology.
According to a university press release, the institute hosted a two-part workshop to help OU faculty form research teams and competitive proposals for projects involving AI-enabled solutions aligning with the U.S. Department of Energy’s mission to “further develop artificial intelligence.”
According to the release, three research projects with interdisciplinary faculty teams were awarded seed funding — wherein an investor puts money into a project in exchange for a stake in its profit — to “support the development of their proposals.” Various OU professors will be working on these teams.
One team received $4,000 in seed funding to support their research project, “Blending Data Streams to Create Reliable Ecological Forecasts,” according to the release. The project will attempt to improve researchers’ ability to model and make predictions about future environmental states.
Yifu Li, one of the professors on the team, is an assistant professor of industrial and systems engineering at the Gallogly College of Engineering.
“The funding provides a great opportunity for bridging the gap between artificial intelligence advancement and societal challenges,” Li said in the release. “Our joint efforts generate research synergy of AI, engineering and scientific innovation to reveal critical insights from big data.”
The two additional teams each received $3,000 in seed funding for their projects.
According to the release, the project team for “Accelerated Optoelectronic Materials Design and Discovery Guided by Machine Learning and Advanced Computation” includes engineering faculty computer science associate professor Dean Hougen, electrical engineering associate professor Samuel Cheng, chemical engineering associate professor Bin Wang, associate professor Kun Lu of the School of Library and Information Studies and chemistry assistant professor Bayram Saparov.
The team will apply advanced computational methods, data mining and machine learning in predictive preparation of materials for solar energy and energy-saving lighting technologies, like light-emitting diodes (LEDs), according to the release.
The third project is titled “Machine-Learning Assisted Molecular and Coarse-Scaled Dynamics.” This project will focus on developing new techniques in the area of state-space models and deep learning to extend the power of molecular dynamics to make possible the simulations of large molecules, such as proteins and asphaltenes, in realistic environments.
The institute plans to continue the program this spring, according to the release.
“We started a seed funding program in December 2020 and plan to continue it this year,” Yessenia Torres, a Data Institute for Societal Change managing director, said in an interview with the Daily. “Last December, we awarded $10,000 to three teams. The teams can use this money to support OU activities such as support faculty and grad student time, team-building meetings, stakeholder engagement/outreach and acquiring pilot data.”
Torres also said the institute hopes to work closely with each team.
“We plan to stay involved with the teams and check in periodically to see how the Data Institute for Societal Change can support them,” Torres said.
