Patrik Kenfack
Bio
I’m a PhD Candidate at ÉTS Montréal - Mila advised by Ulrich Aïvodji and Samira Ebrahimi Kahou. My thesis investigates bias mitigation in machine learning under various constraints on sensitive information. Before joining ÉTS Montréal, I was a research assistant at Machine Learning and Knowledge Representation Lab at Innopolis University, advised by Adil Khan. My work focused on studying fairness aspect of machine learning methods such as ensemble learning, GANs, continual learning, and representation learning.
I graduated with a Master’s Degree in Computer Science and a Bachelor’s in Mathematics and CS at University of Dschang.
Research Interest:
- Applied Machine Learning
- Algorithmic Fairness
- Privacy-Preserving Machine Learning (PPML)
- Responsible AI
News
| Oct 2024 | 📄 Paper | Our paper Adaptive Group Robust Ensemble Knowledge Distillation was accepted at Neurips2024 AFME workshop. |
| Aug 2024 | 📄 Paper | Our paper Fairness Under Demographic Scarce Regime was accepted at TMLR. |
| 🛠️ Service | Invited to serve as a reviewer at ICLR 2025. | |
| Jul 2024 | 🛠️ Service | Invited to provide an emergency review at Neurips 2024. |
| Jun 2024 | 📄 Paper | Our Survey on Fairness Without Demographics was accepted at TMLR. |
| Apr 2024 | 🛠️ Service | Selected to join the Mila EDI committee. |
| Jan 2024 | 🛠️ Service | Reviewer for FAcct. |
| Aug 2023 | 🏆 Award | Our TISL lab team won a $10,000 prize at the 2023 Kaggle AI Report Competition. Our report, Exploring the Landscape of AI Ethics, secured first place in the AI Ethics category. |
| Mar 2023 | 🛠️ Service | Reviewer for ICCV 2023. |
| Apr 2023 | 🏆 Award | Awarded the Excellence Scholarships – EDI in Research from Mila, supporting equity, diversity, and inclusion in AI research. |
| Feb 2023 | 🛠️ Service | Reviewer for FAccT 2023. |
| Jan 2023 | 🎤 Talk | Presented our work Learning Fair Representations Through Uniformly Distributed Sensitive Attributes at SaTML 2023. |