By  Karen Walker

The total amount of data created, captured, copied and consumed globally in 2020 exceeded 64 trillion gigabytes, and German market research firm Statista projects that by 2025 the total data created could surpass 180 trillion gigabytes. To put that in perspective, with just one gigabyte, you could send 350,000 emails, view 600 web pages and stream 200 songs. This data revolution has transformed scientific research, especially in the physical and life sciences, including health care. The problem is there's only enough storage capacity for about 10% of the data produced globally. New algorithms and architectures for networked data-intensive computing are needed, based on storage, processing and use. Farzad FarnoudHassanzadeh, an assistant professor of electrical and computer engineering and computer science at the University of Virginia School of Engineering and Applied Science, has earned a prestigious National Science Foundation CAREER award to meet this need. He will use his $560,000 five-year award to develop new models and data compression algorithms that will make the storage and analysis of large data sequences more efficient and accurate. The CAREER program, one of the NSF's most prestigious awards for early-career faculty, recognizes the recipient's potential for leadership in research and education. Farnoud leads theinformation processing and storage lab, whose members solve problems at the intersection of information theory, computational biology and machine learning — aresearch strengthof the Charles L. Brown Department of Electrical and Computer Engineering.