Michael Carbin

Michael Carbin is an Associate Professor at MIT in the Department of Electrical Engineering and Computer Science (EECS), where he leads the Programming Systems Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research centers on developing programming systems that handle uncertainty through probabilistic programming, quantum computing, and neural networks.

Carbin's work spans programming languages, systems, and machine learning, with themes including uncertainty management, efficiency optimization, and formal verification. His publications demonstrate a strong focus on probabilistic inference methods, neural network optimization, and quantum programming frameworks.

Awards and Honors:

• Sloan Research Fellowship (2020)
• Multiple Best Paper Awards (OOPSLA 2013, 2014; ICLR 2019)
• NSF CAREER Award (2018)
• Google Faculty Research Award (2018)

As the head of the Programming Systems Group, he advises 10+ graduate students and postdocs, focusing on cutting-edge systems research. He has secured grants including Facebook Research Awards and NSF funding.