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Ayman Boustati


Ayman graduated in 2021 with a PhD in Mathematics for Real-World Systems.


  • Boustati, A., Vakili, S., Hensman, J., & John, ST (2020). Amortized variance reduction for doubly stochastic objectives. In Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR volume 124.
  • Richter, L., Boustati, A.*, Nüksen, N., Ruiz, F. J., Akyildiz, Ö. D. (2020). VarGrad: A Low Variance Gradient Estimator for Variational Inference. Neural Information Processing Systems (NeurIPS), 2020.
  • Boustati, A., Akyildiz, Ö. D., Damoulas, T., & Johansen, A. (2020). Generalized Bayesian Filtering via Sequential Monte Carlo. Neural Information Processing Systems (NeurIPS), 2020.
  • Boustati, A., Damoulas, T., & Savage, R. S. (2019). Non-linear Multitask Learning with Deep Gaussian Processes. arXiv preprint arXiv:1905.12407. Under Review.

* Joint first author.


  • MSc in Mathematics for Real-World Systems from the University of Warwick 2015-2016
  • Master of Mathematics, Operational Research, Statistics and Economics from the University of Warwick 2011- 2015

Current Projects:

Previous Projects:

Research Interests:

  • Gaussian Processes
  • Multitask and Transfer Learning
  • Bayesian Inference (mainly Variational Inference)
  • Statistical Machine Learning and Probabilistic Modelling
  • Learning Representations
  • Theory and Applications of Deep Learning

    External Links: