Daniel Díaz Quílez
I am a PhD student in Symbolic AI at TU Wien, where I work on AI systems that reason transparently, reliably, and from first principles. Most of my work uses SAT solvers for symbolic and neurosymbolic AI.
I did my master's in Mathematics at the University of Helsinki, specializing in mathematical and computational logic, and my bachelor's in Mathematics and Computer Science at the Universidad Politécnica de Madrid. I am fascinated by the foundations of mathematics: what truths exist, what can be proven, and what the limits of formal reasoning are. I have mostly worked on model theory and set theory, but I am also drawn to proof theory, type theory, and formalizing mathematics in Lean.
Outside of my studies, I like running, traveling, cooking, reading, writing, and playing chess and Go.