About Me
Hi! I'm a first year ELLIS PhD student in mechanistic interpretability and AI safety at the MPI for Intelligent Systems advised by Prof. Bernhard Schölkopf, and supported by the Hector Fellow Academy.
I am interested in understanding the internal mechanisms of large language models (LLMs), particularly their "world models"—the structured representations they develop to interpret and make sense of data. My current projects center around cross-layer transcoders and attribution graphs.
Before starting my PhD, I did a BSc in mathematics at EPFL and spent one year at ENS in Paris (Ulm). I then transitioned to pursue a MSc in Neural Systems and Computation at ETH Zürich. During my master, I worked by Prof. Maneesh Sahani at the Gatbsy Unit in London on non-generative representation learning.
Florent Draye
PhD Student in Machine Learning
MPI-IS, Germany
Education
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PhD, Machine Learning
Max Planck Institute | 2024–Present
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MSc, Neural Systems and Computation
ETH Zürich | 2022–2024
GPA: 5.9/6
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Exchange Program, Mathematics
Ecole Normale Supérieure (Ulm) | 2021–2022
GPA: 18.3/20
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BSc, Mathematics
EPFL | 2019–2022
GPA: 5.88/6
Prizes
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Best Bachelor Average Grade (1500$)
Awarded for achieving the highest bachelor average (5.88/6) among 1214 graduates, 2022.
EPFL, 2019–2022
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Part III International Scholarship – University of Cambridge
Awarded based on academic potential for the Master of Applied Mathematics (Part III), declined.
University of Cambridge, 2022
Experiences
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Machine Learning Research Intern
Gatsby Unit UCL, 09/2023-02/2023
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Data Science Intern
Mindmaze, Summer 2023
News
Just started my PhD with Prof. Bernhard Schölkopf
January 2025
Research
A Review on the Universal Approximation Theorems of Artificial Neural Networks
U Faure†, F Draye†, Bachelor Thesis 2022
† Equal contribution
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