- Ibadulla, R., Chen, T.M. and Reyes-Aldasoro, C.C. (2023). FatNet: High-Resolution Kernels for Classification Using Fully Convolutional Optical Neural Networks. AI, 4(2), pp. 361–374. doi:10.3390/ai4020018.
Contact details
Address
Riad Ibadulla
City, University of London
Northampton Square
London EC1V 0HB
United Kingdom
Northampton Square
London EC1V 0HB
United Kingdom
Personal links
About
Overview
Riad Ibadulla is a PhD candidate in the Department of Computer Science, specialising in the optimisation and adaptation of deep learning architectures for free-space optical accelerators. His research primarily focuses on solving computer vision problems using deep learning approaches like Convolutional Neural Networks and Vision Transformers. He is currently working under the supervision of Prof. Tom Chen and Dr. Constantino Carlos Reyes-Aldasoro.
Qualifications
- MSc Artificial Intelligence, University of St Andrews, United Kingdom, Sep 2018 – Sep 2019
- BEng Computer Systems Engineering, City, University of London, United Kingdom, Sep 2015 – Jul 2018
Employment
- Graduate Teaching Assistant, City University of London, May 2021 – present
- Deep Learning Engineer, Optalysys ltd, Nov 2019 – Aug 2020
Languages
Azerbaijani (can read, write, speak, understand spoken and peer review), English (can read, write, speak, understand spoken and peer review), Russian (can read, write, speak, understand spoken and peer review) and Turkish (can read, write, speak and understand spoken).
Publications
Publications by category
Conference paper/proceedings
- Ibadulla, R., Reyes-Aldasoro, C.C. and Chen, T.M. (2024). Fat-U-Net: non-contracting U-Net for free-space optical neural networks. AI and Optical Data Sciences V 27 Jan 2024 – 1 Feb 2024. doi:10.1117/12.3008618