Computer Science Faculty Receive Inaugural UMD Grand Challenges Grants

The University of Maryland recently awarded $30 million to 50 projects through its Grand Challenges Grants Program, an institution-wide initiative to tackle major societal issues. 

The College of Computer, Mathematical, and Natural Sciences (CMNS) received 16 Grand Challenges grants—and UMD CS faculty members are involved in 5 of them. These projects aim to address climate change, human health and disease, artificial intelligence and inclusion in STEM.

“I would like to congratulate all our faculty colleagues who are among the recipients of these grand challenges grants. Our colleagues’ projects demonstrate the importance of Computer Science as a crucial field that will enable breakthroughs in addressing these pressing challenges. We are thrilled to support their research in our department.” says Matthias Zwicker, Chair of the Computer Science Department.

Impact Awards

Cross-disciplinary collaborations that address a grand challenge focus or theme. These awards provide up to $250K per year for 2 years of funding, which includes a 1:1 match of resources from participating colleges and/or departments.

Maryland Institute for Digital Accessibility – These projects will make more digital technologies and content accessible for people with disabilities and create technologies that may alleviate inaccessibility in the physical world, leading to fewer structural barriers, more inclusion in society, better educational outcomes and employment success for people with disabilities.

 Computer Science Department Team Members: Huaishu Peng, Abhinav Shrivastava

Microbiome Sciences – This initiative will conduct transformative research to advance microbiome science and support the development of a regional innovation ecosystem that contributes to economic growth in microbiome-related industries in Maryland.

 Computer Science Department Team Member: Mihai Pop (principal investigator)

Values-Centered Artificial Intelligence – This center aims to have local, national and international impact to move artificial intelligence from a technology-centered approach to a values-centered approach. By combining top-down ethical considerations and bottom-up community insights, this approach has the potential to transform the practice of artificial intelligence globally.  

 Computer Science Department Team Members: Hal Daumé III (principal investigator), Jordan Boyd-Graber, Marine Carpuat, John Dickerson, Furong Huang, Huaishu Peng, Pratap Tokekar

Team Project Grants

Projects are advanced by research teams that are targeted toward a specific component of a grand challenge topic or theme. Team Project awards provide up to $500K per year for 3 years of funding, which includes a 1:1 match of resources from participating colleges and/or departments.

Effective and Equitable Weather Forecasting in a Changing Climate with Machine Learning – This project aims to characterize and improve machine learning weather forecasting, with an emphasis on designing systems that are both accurate and equitable. The project aims to significantly and meaningfully advance the science of weather forecasting by expanding beyond the traditional focus on physical processes to include uncertainty and societal considerations in the forecasting workflow.

 Computer Science Department Team Member: Christopher Metzler

Individual Grants

Projects by individual investigators that are targeted toward a specific component of a grand challenge. Individual Project Grant awards provide up to $50,000 per year for 3 years, which includes a 1:1 match of resources from the PI's college and/or department.

Accurate, Equitable, and Transparent Genetic Ancestry Inference – Michael Cummings (Computer Science Affiliate Professor) seeks to develop improved computational methods to more accurately infer genetic ancestry at the sub-chromosome level (i.e., segments of chromosomes). These improvements will advance healthcare justice and contribute to the general understanding of the principles of population genetics, evolution and the genetic basis of human biology.

—This article was adapted from a news release published by the College of Computer, Mathematical, and Natural Sciences and Maryland Today