Michael Carbin

Michael Carbin is the Jamieson Career Development Assistant Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT) and leads the MIT Programming Systems Group. His research focuses on programming systems that address system uncertainty to enhance performance, energy efficiency, and resilience, particularly in environments involving neural networks, approximate computing, and unreliable hardware.

His work spans probabilistic programming, quantum computing, and machine learning systems. Articles highlight contributions in pruning neural networks, quantum data structures, and compiler optimization, reflecting trends in deep learning, formal verification, and language-driven systems.

Scientific Awards:

• MIT Frank E. Perkins Award (2020)
• Sloan Research Fellowship (2020)
• Facebook Research Award (2019)
• NSF CAREER Award (2018)
• Best Paper Awards at OOPSLA (2013, 2014)

He has advised numerous graduate students and postdocs including Eric Atkinson, Cambridge Yang, and Charles Yuan, and served on program committees for conferences like POPL, OOPSLA, and ICLR. His group collaborates with institutions such as MIT CSAIL and explores applications in quantum algorithms and probabilistic inference.