Khaled Zaouk

Khaled Zaouk is a machine learning scientist at Ava. Khaled previously worked as a speech scientist intern at Amazon, where they designed neural network architectures for improving diacritization task within the Cambridge Text-To-Speech Research team for Amazon Alexa and Amazon Polly.

Zaouk received their PhD from École Polytechnique, where their focus was on developing a unified data analytics optimizer for performance tuning of cloud workloads. Khaled designed neural network architectures that were able to outperform their Gaussian Process counterparts in accuracy of modeling latency and throughput of cloud workloads.

During their PhD, Zaouk also explored AutoML approaches (Hyperband and other bandit based methods, Spearmint and Bayesian Optimisation tools), Reinforcement Learning methods, Recommender Systems, Zero-shot & Few-shot learning approaches, Auto-encoders (contractive & variational), and Siamese Neural Networks. Khaled's work has been published in several papers, which are available on their Google Scholar profile. Khaled has also created code repositories for some of their projects, which are available on GitHub.

Some of their coworkers include Sacha Bécourt - Lead iOS Engineer, Sandro Pasquali - Principle Engineer, and Sylvain Conso - Data Engineer. Their manager is Skinner Cheng, CTO & Co-Founder.