Pehuén Moure

I am a postdoctoral researcher at Cornell Tech in New York City. I completed my PhD at ETH Zurich’s Institute of Neuroinformatics, working at the intersection of machine learning and neuroscience on robust AI systems that generalize across domains, from neuroprosthetic control to reinforcement learning for robotics and personalized speech recognition.

Currently, I’m focused on speech and accessibility: how people whose speech is hard for today’s systems to understand are assessed and supported, and where the technology falls short. Earlier work includes deep learning for controlling neural activity in visual prostheses, Bayesian methods for generalization in reinforcement learning, and neuroscience-inspired approaches to how large language models reason.

My work aims to bridge the gap between theoretical advances in machine learning and practical applications, particularly in healthcare and robotics. I’m passionate about developing AI systems that can adapt to diverse needs and serve specific individuals rather than just average use cases.

A list of my publications can be found on my publications page, and short explainers on some of the work are on my videos page.