Adrià Garriga-Alonso is a scientist at FAR.AI, working on understanding what learned optimizers want.

Previously he worked at Redwood Research on neural network interpretability. He holds a PhD from the University of Cambridge, where he worked on Bayesian neural networks; his advisor was Prof. Carl Rasmussen.

He was a co-organiser of the ICLR 2019 workshop “Safe Machine Learning: Specification, Robustness and Assurance”.