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	rdfs:comment	"Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning (Trusted AI) and the director of the Information Theory and Machine Learning (vITAL) research lab. He is also the CEO and Co-Founder of FedML. Avestimehr's contributions in research and publications are in the areas of information theory, machine learning, large-scale distributed computing, and secure/private computing and learning. In particular, he is best known for deterministic approximation approaches to network information theory and coded computing. He was a general co-chair of the 2020 International Symposium on Information Theory"@en ;
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	dbo:abstract	"Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning (Trusted AI) and the director of the Information Theory and Machine Learning (vITAL) research lab. He is also the CEO and Co-Founder of FedML. Avestimehr's contributions in research and publications are in the areas of information theory, machine learning, large-scale distributed computing, and secure/private computing and learning. In particular, he is best known for deterministic approximation approaches to network information theory and coded computing. He was a general co-chair of the 2020 International Symposium on Information Theory (ISIT), and is a Fellow of IEEE. He is also co-authors of four books titled \u201CAn Approximation Approach to Network Information Theory\u201D, \u201CMultihop Wireless Networks: A Unified Approach to Relaying and Interference Management\u201D, \u201CCoded Computing\u201D, and \u201CProblem Solving Strategies for Elementary-School Math.\u201D"@en ;
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	dbp:thesisTitle	"Wireless network information flow: a deterministic approach"@en ;
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