About me
I am an Applied Mathematics PhD Candidate in the Machine Learning group of the Mathematical Institute at the University of Oxford advised by Prof. Jared Tanner.
From January to July 2025, I have been a Machine Learning researcher intern in the Apple Machine Learning Research (MLR) group in Paris, where I have been working on leveraging data quality for LLM pretraining.
From September 2025 to February 2026, I will be interning with the Research Team at Mistral AI.
More broadly, I am curious about a wide range of topics in AI, from building (efficient) LLMs to aligning them, and exploring questions in AI safety and societal impact. I expect to graduate in 2026 — feel free to reach out if you’d like to connect.
My PhD research focuses on theories of Deep Learning. In particular, I have been interested in the study of infinitely wide neural networks and possible applications of Random Matrix Theory to prescribe practitioners with effective initialisation schemes.
I also have some interests in Geometric Machine Learning methods, such as applications of Deep Learning models to solve public health issues. In summer 2023, I interned at Owkin as a Research intern in the Computer Vision team. Download my CV.Email : thiziri [dot] naitsaada [at] maths [dot] ac [dot] uk
Interests
- Theoretical Deep Learning
- Efficient LLMs
- AI Safety
- Optimisation
- Applications of Deep Learning
- Geometric Machine Learning
Education
-
University of Oxford (2021-mid 2026)
PhD in Mathematics
-
Ecole Normale Superieure of Saclay (2020-2021)
MSc in Mathematics, Vision and Learning (MVA)
-
Télécom Paris (2018-2021)
Grande École diploma in Data Science
-
Eurecom (2019-2020)
Master's Degree in Computer Science
-
Lycées Henri IV and Saint-Louis (2016-2018)
Preparatory Classes in Physics and Maths