Nurbek Tastan
PhD Candidate in Machine Learning, MBZUAI.

Abu Dhabi, UAE
I am Nurbek Tastan, currently pursuing a Doctor of Philosophy degree in Machine Learning. I am associated with the SPriNT-AI lab at MBZUAI, where I conduct my research under the guidance of my supervisor, Dr. Karthik Nandakumar and Dr. Samuel Horvath.
My research focuses on trustworthy federated learning, with particular emphasis on fairness, privacy, efficiency, and robustness in collaborative settings. I also develop methods to make large-scale models, including language models, more efficiently fine-tunable while also preserving utility and user confidentiality.
Passionate about building machine learning systems that are not only performant, but also equitable, privacy-aware, and computationally viable for real-world deployment.
selected publications
- CaPriDe Learning: Confidential and Private Decentralized Learning Based on Encryption-Friendly Distillation LossIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , Jun 2023
- CPALFedPeWS: Personalized Warmup via Subnetworks for Enhanced Heterogeneous Federated LearningIn The Second Conference on Parsimony and Learning (Proceedings Track) , Mar 2025
- Collaborative Learning of Anomalies with Privacy (CLAP) for Unsupervised Video Anomaly Detection: A New BaselineIn Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , Jun 2024