Like other complex systems, computer networks can break down and suffer bottlenecks. Keeping such systems running requires algorithms that can identify problems and find solutions on the fly so information moves quickly and on time.

Mariam Kiran – a network engineer for the Energy Sciences Network (ESnet), a DOE Office of Science user facility managed by Lawrence Berkeley National Laboratory – is using an early-career research award from DOE’s Office of Science to develop methods combining machine-learning algorithms with parallel computing to optimize such networks.

Read more: http://ascr-discovery.science.doe.gov/2017/12/thinking-networks/