About

Oscar develops mathematical foundations for decentralized learning and non-cooperative coordination under institutional constraints, at the intersection of economic, game, and machine learning theory, with applications to industrial and cyber-physical AI systems across sovereign jurisdictions. He studies how institutional structure —sovereignty, regulatory heterogeneity, and governance— shapes equilibrium, welfare, and learnability in finite- and infinite-horizon stochastic games.

Oscar is advised by Craig Tovey and co-advised by Benoit Montreuil, with mentorship in optimization theory from Arkadi Nemirovski and in stochastic programming from Alexander Shapiro.

Prior to Georgia Tech, he spent 22+ years leading Fortune 50 innovation and transformation across technology, supply chain, and healthcare, in executive and consultative roles. His experience, research interests, and publications are detailed at www.babich.ai.

Leisure

Oscar composes instrumental New Flamenco pieces and arrangements for one and two guitars, which he delivers solo in live multi-track looping act, and duo with Jose Valle Fajardo "Chuscales".

He is descendant of Agustín Barrios "Mangoré" through José Cándido Morales, master keeper of Barrios' legacy.

In Appreciation

• José Cándido Morales†
• Juan Ricardo Salazar-Simpson Bos†, S.J.
• Yossi Serebryanksi
• Alvaro Arias