Mariam Kiran is a research scientist with shared positions with Energy Sciences Network (ESnet) and the Scientific Data Management (SDM) group in the Scientific Data Division. Her work specifically concentrates on using advanced software and machine learning techniques to advance system architectures, particularly high-speed networks such as DOE networks.
Her current work is exploring reinforcement learning, unsupervised clustering and classification techniques to optimally control distributed network resources, improving high-speed big data transfers for exascale science applications, and optimizing how current network infrastructure is utilized. Kiran is the recipient of the DOE ASCR Early Career Award in 2017. Before joining LBNL in 2016, Kiran held positions as a lecturer and research fellow at the Universities of Sheffield and Leeds in the UK. She earned her undergrad and Ph.D. degrees in software engineering and computer science from the University of Sheffield, UK in 2011.
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