I originally used this space to report on my research. Over time, and especially since joining Google in 2014, my focus has shifted towards building production systems. Currently, I indulge my passion for compilers as compiler architect and distinguished compiler engineer at NVIDIA.
Before joining NVIDIA in 2023, I was the technical lead for Google’s ML Compilers for CPU and GPU that power frameworks like TensorFlow or JAX. My technical contributions span XLA and the MLIR compiler infrastructure.
Before working on TensorFlow, I have participated in various compiler projects at Google. Initially, I joined the Dart team and helped extend the compiler from Dart to JavaScript. I was also invoked in shrinking the Dart runtime to work on embedded systems.
Next, I helped build the new compiler toolchain for Android, with particular focus on optimizing and shrinking applications.
As part of the v8 team, I worked on making WebAssembly faster, with a focus on improved register allocation.
My interest for dynamic languages, especially those for the web, was sparked while being a Research Scientist at Intel Labs in Santa Clara. During my stay, I was part of the team behind River Trail, an effort to bring the power of data-parallel programming to the web.
Even earlier, I enjoyed the position of a Research Fellow at the University of Hertfordshire. More precisely, I was part of the Compiler Technology and Computer Architecture group where I researched compiling array programming languages to fast executable code.
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