My research interests lie in the intersection between deep learning and computational neuroscience. The following are some of my published works and articles. You can also find my profile on Google Scholar.

Publication

Bryan M. Li, Alexander Cowen-Rivers, Piotr Kozakowski, David Tao, Siddhartha Rao Kamalakara, Nitarshan Rajkumar, Hariharan Sezhiyan, Sicong Huang, Aidan N. Gomez. RL: A generic reinforcement learning codebase in TensorFlow. Journal of Open Source Software. 2019.

Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser. CipherGAN: Unsupervised Cipher Cracking Using Neural Networks. International Conference on Learning Representations. 2018.

Workshop paper

Aidan N. Gomez, Sicong Huang, Ivan Zhang, Bryan M. Li, Muhammad Osama, Lukasz Kaiser. Unsupervised Cipher Cracking Using Discrete GANs. Neural Information Processing Systems DISCML. 2017.

Preprint

Bryan M. Li, Leonardo V. Castorina, Maria del C. Valdés-Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw. Super-Resolution of Magnetic Resonance Images Acquired Under Clinical Protocols using Deep Attention-based Method. 2022.

Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken. Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks. 2021.

Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken. CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of neuronal populations. 2020.

Thesis

Synthesising Realistic Calcium Imaging Data of Neuronal Populations using Deep Generative Models. MSc by Research, awarded with Distinction. 2020.

Talk

Identifying digital biomarkers of illness activity and treatment response in bipolar disorder. Oral presentation at UKRI AI CDTs in Healthcare Conference 2022.

Blog post

Accelerated TensorFlow model training on Intel Mac GPUs. Towards Data Science. 2021.

Multi-GPUs and custom training loops in TensorFlow 2. Towards Data Science. 2021.

A Transformer Chatbot Tutorial with TensorFlow 2.0. TensorFlow Blog. 2019.

Teaching

Tutor & Marker. INFR11130 Machine Learning and Pattern Recognition. University of Edinburgh. 2021 Autumn.

Teaching Assistant. INFR11077 MSc Dissertation (Informatics). University of Edinburgh. 2020 Sping.

Teaching Assistant. CSC258H1 Computer Organization. University of Toronto. 2018 Winter.

Teaching Assistant. CSC120H1 Computer Science for the Sciences. University of Toronto. 2017 Fall.

Work in news

Powerful AI Algorithm That Cracks Encrypted Messages Could Help Facebook and Google Translate Human Language. Newsweek. 2018.

Cracking the code: This group of U of T computer science researchers are decoding ciphers with AI. University of Toronto News. 2017.