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. https://arxiv.org/abs/2003.04125.
- 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. https://arxiv.org/abs/2003.04125.
Boustati, A., Damoulas, T., & Savage, R. S. (2019). Non-linear Multitask Learning with Deep Gaussian Processes. arXiv preprint arXiv:1905.12407. Under Review. https://arxiv.org/abs/1905.12407.
* 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
- I am currently working on my PhD project: Topic in Gaussian Process Model for Machine Learning. I was supervised by Dr Richard Savage and now Dr Theo Damoulas.
- I worked on a project on Identifying Illegal Trading and Market Manipulation using Machine Learning. This project was in collaboration with Spectra Analytics supervised by Dr Dan Sprague and Dr Marcus Ong from Spectra Analytics, and Professor Mark Girolami from the Department of Statistics at Warwick.
- I worked with Peter De Ford, Laura Guzman, Alvaro Cabrejas and Guillem Mosquera on Intelligent Mobility Applications for the UK Strategic Road Network. This project was in collaboration with the Thales Group, under the supervision of Dr Colm Connaughton.
- I worked under the supervision of Dr Ben Graham on Extracting Information from Facial Images Using Artificial Neural Networks.
- I worked with the Visualisation Group at the Warwick Manufacturing Group, and contributed to creating a framework for encoding and decoding High Dynamic Range sequences in Matlab.
- 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