Morgado and Eliceiri selected for WARF Big Data Challenge Grants

Pedro Morgado, an assistant professor in electrical and computer engineering at the University of Wisconsin-Madison and Kevin Eliceiri, the RRF Walter H. Helmerich Professor of Medical Physics and Biomedical Engineering, lead two of five research teams selected to receive a Wisconsin Alumni Research Foundation (WARF) Accelerator Big Data Challenge Grant.

The grants, which total $100,000, are allocated to fund new technologies focused on processing and handling large amounts of data. This can include everything from data-driven communications to enhanced imaging software and biomedical data processing.

Morgado is an expert in computer vision and machine learning. He creates systems that learn to perceive the world through multiple sensory modalities. The project he submitted for the Big Data Challenge is a context modeling framework for machine learning using naturally occurring video.

Eliceiri’s lab specializes in new biomedical imaging and analysis methods to understand the roles of cells in disease. This includes building instruments to collect more detailed data, using machine learning to classify biomedical images and developing open-source software for the global image analysis community. His Big Data Challenge project involves developing a smart compression framework for multidimensional biomedical images.

“Turning big data into actionable information is critical to helping organizations identify new opportunities and make informed decisions,” says Erik Iverson, CEO of WARF. “We’re delighted to support UW-Madison innovators rising to the challenge of managing large amounts of data.”

In total, 24 competitive research teams from across the university applied for the grants.