Anissa Alloula
Hi, I’m Anissa, a 3rd year PhD student in Machine Learning at the University of Oxford. I’m broadly interested in how ML models need to be adapted because of the non-i.i.d. nature of real-world data. So far, I have begun to explore one aspect of this area during my PhD by investigating how biases and spurious correlations in training data affect downstream models, and if and when bias mitigation methods can be used to tackle them. Before my PhD, I completed my BSc at Imperial College London.
Outside of research, I spend a lot of (too much?) time exercising, particularly running, triathlon training, and playing tennis.
I’m always happy to connect and discuss my/your research so please reach out if any of the above sounds interesting!
News
| Jul 04, 2025 | Returning to Vancouver for ICML to present my paper on subgroup definition in bias mitigation! |
|---|---|
| Dec 01, 2024 | Looking forward to going to Vancouver for NeurIPS to present two posters at the Algorithmic Fairness workshop and the Women in ML workshop. |
| Oct 01, 2024 | Excited to attend MICCAI in Morocco to present my paper on biases and their mitigation in retinal image classification. |
| Nov 01, 2023 | Officially started my PhD, supervised by Bartek Papiez! |
Selected Publications
- Under Review
- ICMLSubgroups Matter for Robust Bias MitigationIn International Conference on Machine Learning, (ICML), Jul 2025
- MICCAI