I am a postdoc at the April lab working alongside Dr. Antonio Vergari on developing novel probabilistic machine learning approaches to integrate symbolic constraints within neural models, making them properly meet the expectations that we place on them. As such, we aim at making models more reliable and trustworthy.

I completed my PhD at the Probabilistic Machine Learning group working with Prof. Isabel Valera at Saarland University. Before that, I worked at the Max Planck Institute for Intelligent Systems in Tübingen at the Empirical Inference department and the Probabilistic Machine Learning group.

My research focuses on developing methods that are reliable, principled, and efficient. Loosely, this resolves to adding a-priori inductive biases to models such that they comply with our expectations on how they should behave in the wild. My ultimate goal is to conduct interesting and principled research to better understand machine learning models and ease their deployment in the real-world.

I try to be as approachable as possible. Feel free to reach me through email or any of my (active) social media profiles.