Emilie Danna

Emilie is a software engineer with a track record of innovation and scaling with transformative business impact since 2005. At Google, she introduced optimization and simulation tools to transform how Google designs and capacity plans its planet-scale inter-datacenter networks for low cost and high availability. Later at Lyft, she built software, hardware, and operations program to collect low-cost, high-quality, high-volume road data in order to train machine learning algorithms for self-driving cars. Most recently, she led the development of an MLOps platform for time series forecasting at startup Myst.ai to accelerate the renewable energy transition.

Emilie has a Ph.D. in operations research from Université d’Avignon, where she invented an integer programming heuristic to find high-quality solutions to hard mathematical optimization problems, which is still used in major integer programming solvers. She also holds an MS in statistics from Ecole Nationale de la Statistique et de l’Administration Economique.