Albert Cohen, Google DeepMind Paris, Research Scientist. Albert works on the acceleration and energy-efficiency of machine learning models. An alumnus of École Normale Supérieure de Lyon and the University of Versailles (Paris Saclay), he first joined INRIA, then also held a part-time associate professor position at École Polytechnique. He has been a visiting scholar at the University of Illinois, an invited professor at Philips Research as a recipient of a Marie Curie technology transfer fellowship, and a visiting professor at Facebook Artificial Intelligence Research. Albert’s work spans the theory and practice of programming languages, parallelism, high-performance and power-efficient computing, as well as safety-critical embedded control, resulting in 250 peer-reviewed publications together with 30 PhD students and international collaborators. Some of this work led to technology transfer, including contributions to the industry standard GCC and LLVM compilers. Since joining Google, Albert contributed to the design and adoption of the MLIR platform for scalable and efficient machine learning.