Author

Grigori has an interdisciplinary background in computer engineering, physics and machine learning with more than 20 years of R&D experience. He has pioneered systematic performance analysis, optimization and adaptation of computing systems based on statistical analysis, machine learning, automatic and crowdsourced tuning.

Since 2007 when he joined INRIA as a tenured research scientist, Grigori lead several highly successful R&D projects including the EU-funded MILEPOST project that produced the world's first machine learning based production compiler (MILEPOST GCC). In 2010-2011, Grigori was on leave from INRIA invited to establish the Intel Exascale Lab in France while serving as the head of its program optimization and characterization group.

As founder of the nonprofit cTuning Foundation, Grigori is also leading a new artifact evaluation initiative for PPoPP, PACT and CGO, the premier ACM conferences on parallel programming, architecture and code generation, which aims to encourage sharing of code and data to enable reproducible systems research and engineering.

Grigori is also an active member of the new ACM taskforce on reproducibility defining artifact evaluation procedures and appendices such as ones used by SC '17 reproducibility initiative.