Myriam Schönenberger

I'm a Master's student at the Kim Jaechul Graduate School of AI at KAIST, interested in teaching robots to learn new tasks continually and robustly. My research focuses on enabling agents to adapt safely over time while avoiding catastrophic failures that would require human intervention. I'm also fascinated by real-world symmetries and how leveraging them can lead to more efficient and reliable learning.

During my physicist years at the Institute for particle physics and astrophysics (IPA) at ETHZ where I was advised by Rainer Wallny, I searched for supersymmetry in the fully hadronic and Higgs to diphoton final states, which resulted in my PhD thesis.

CV  /  Scholar  /  Github

Publications

Listed below are publications where I contributed significantly.

Original source code by Jon Barrow.