Walter was in the MATS Winter 2023 Cohort under the mentorship of John Wentworth. At Cadenza Labs, he splits his time between being a team lead and research engineering. With other collaborators, his team created an open-source library, where Walter is a main contributor. Before starting his PhD in ML, Walter was working as software engineer for a couple of years after graduating in CS.
Sharan first joined Cadenza Labs to work with Walter on Cluster-Normalization for Unsupervised Probing. He is a first-year PhD student at the Language Technology Lab at the University of Cambridge, where he works on interpretability and evals. Sharan has a background in statistics after studying at Imperial College and Edinburgh.
Grégoire's work at Cadenza Labs primarily focused on the project "Cluster-Norm for Unsupervised Probing of Knowledge." His main contribution was developing contrast-pair clustering techniques for CCS-style methods. This research was presented at the ICML MechInterp workshop. In addition to this project, Grégoire has been investigating how structures emerge in the computational graphs of neural networks. Currently, Grégoire is pursuing a Master's degree in Mathematics and Computer Science at ENS Paris-Saclay. His academic interests are centered on mechanistic interpretability and the analysis of neural networks.
Kieron is currently finishing his thesis for the M.Sc. in AI at the University of Amsterdam in collaboration with Cadenza. In his research, he investigates ways in which supervised and unsupervised probes can fail to predict truthfulness under distributional shifts, with a focus on quantifying and methods to mitigate these failure modes. During his studies he has set up and organized an AI Safety reading group, and has participated in the ML4Good and Talos Fellowships. Before pivoting his career towards technical AI Safety research, he has co-founded two startups and obtained a B.Sc. in Technomathematics.