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Nathan Beckmann is an Associate Professor in the School of Computer Science at Carnegie Mellon University. He received his PhD from MIT in 2015 under the supervision of Daniel Sanchez, and has a Master's from MIT in 2010 advised by Anant Agarwal, as well as a Bachelor's degree in Electrical Engineering and Computer Science and Mathematics from UCLA in 2008. His doctoral dissertation was awarded the George M. Sprowls Award for outstanding dissertation in electrical engineering and computer science at MIT. Nathan has received several accolades including multiple paper awards, the NSF CAREER Award, the Google Research Scholar Award, and the Sloan Research Fellowship. His research focuses on building energy-efficient, general-purpose computers, addressing the significant challenge that general-purpose computing faces due to stagnated architectures and the shift towards specialized hardware. His work aims to reconcile programmability and energy efficiency to facilitate a sustainable future in computing, leveraging spatial dataflow architectures to reduce inefficiencies associated with traditional von Neumann CPUs. His research integrates hardware and software, emphasizing the design of complete systems that run on production data centers and silicon test chips.
Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.