Filippos completed his M.S. in Symbolic Systems at Stanford, where he did research in NLP, LLM agents, graphical neural networks, and knowledge representation. For his thesis, he worked on a new computational theory of analogical reasoning based on abstraction. During his degree, he interned for Amazon's Alexa team, where he designed and implemented an original time-series model for predicting popular content which was used to choose data for fine-tuning Alexa's NLU model.

Prior to that, Filippos worked for two years at EY (Ernst and Young) in Athens, building various ML models for large regional clients and leading the development for central features of two global analytics applications.

He completed his B.S. at Yale University, double majoring in Mathematics and Philosophy.