Registered user since Thu 8 Mar 2018
Michael Carbin is the Jamieson Career Development Assistant Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology.
His primary research focus is the design of programming systems that manipulate system uncertainty to deliver improved performance, energy consumption, and resilience. Uncertainty — in the form of sampled and sensed values, dynamic computation structure, and intermittently available computing — is a first-order challenge in modern computing systems.
His research on verifying the reliability of programs that execute on unreliable hardware has received best paper awards at leading programming languages conferences (OOPSLA 2013 and OOPSLA 2014) as well as a Communications of the ACM Research Highlight in 2016. He has also published work at leading programming languages and systems conferences, including PLDI, OOPSLA, ASPLOS, LICS, SOSP, ICSE, and PPoPP.
|ESEC/FSE 2021||Generalizable and Interpretable Learning for Configuration Extrapolation|
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