Senior Research Scientist, Brain-Inspired Computing Lab
Nesreen is a senior research scientist at Intel Labs. She received her Ph.D. from the Computer Science Department at Purdue University in 2015, and her M.S. in statistics and computer science from Purdue University in 2014. In 2018, she is the PC Chair of the IEEE Big Data Conference. Nesreen was a visiting researcher at Facebook, Adobe research, Technicolor, and Intel. Her research interests in machine learning and data mining span the theory and algorithms of large-scale statistical machine learning, deep learning, graph theory, and their applications in social and information networks. Nesreen has authored numerous papers/tutorials in top-tier conferences/journals. Her research was selected among the best papers of ICDM in 2015, BigMine in 2012, and covered by popular press such as the MIT Technology Review. She was selected by UC Berkeley among the top female rising stars in computer science and engineering in 2014.
This is paper introduces a new single-pass reservoir weighted-sampling stream aggregation algorithm, Priority-Based Aggregation (PBA). While order sampling is a…
We propose Graph Priority Sampling (GPS), a new paradigm for order-based reservoir sampling from massive streams of graph edges. GPS…
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