MIT Associate Professor Jonathan Ragan-Kelley specializes in developing programming languages and machine learning techniques to optimize hardware performance for applications like graphics, visual effects, and computational photography. His research focuses on creating new programming languages that can efficiently utilize complex hardware. Ragan-Kelley's work includes the development of Halide, an image-processing language that has transformed the image editing industry, and a project in collaboration with the MIT-IBM Watson AI Lab that aims to provide control and optimization options for low-level programming.
He also explores high-level ways to unlock hardware potential through machine learning and "exocompilation. " Ragan-Kelley is driven by the pursuit of unconventional ideas that have the potential to significantly impact the field. Additionally, he teaches a course at MIT that emphasizes the optimization of memory and specialized hardware for achieving optimal performance. The goal is to unlock the computational potential of new machines and enable the development of innovative applications.
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