engineer of fairness
Osonde Osoba (pronounced “oh-shOwn-day aw-shAw-bah”) is a researcher and data scientist at the RAND Corporation and a professor at the Pardee RAND Graduate School. He has a background in the design and optimization of machine learning algorithms. He has applied his expertise to diverse policy topics such as epidemiology, defense acquisition, and science and technology policy. His recent focus has been on data privacy and accountability in algorithmic systems and artificial intelligence.
Prior to joining RAND, Dr. Osoba’s research at the University of Southern California (USC) was focused on improving the speed and robustness of popular statistical algorithms, specifically expectation-maximization, neural networks, and Bayesian inference.
When he’s not lecturing, writing or registering patents, you can find O Pé (Osonde’s apelido) substitute teaching and event organizing for the United Capoeira Association in Los Angeles (UCAinLA) and enjoying his practice of this Afro-Brazilian art form.