Meisam Hejazinia

Research Scientist

I am a Research Scientist at Facebook working on tools and algorithms for privacy preserving machine learning for Ad ranking. Particularly, my works resides in the intersection of scalable multi-stage ranking systems, deep learning, and privacy preserving algorithms and approaches including Federated Learning (FL), Differential Privacy (DP), and secure aggregation via Multi Party Computation (MPC).

Prior to Facebook, I had 8 years experience in industry, working on leveraging statistical and machine learning methods in travel technology, retail technology, game technology, airline technology, telecom, fashion, apparel, and textile industries, leading teams to build recommender systems, revenue management systems, and advertising measurement systems. I got my PhD in Marketing Science from University of Texas at Dallas (UTD).


Federated learning, privacy preserving machine learning, reinforcement learning and contextual multi arm bandits, ranking and recommender systems, deep learning, Bayesian machine learning, two sided marketplaces