- I’m currently in my 3rd year of my PhD in the
**Machine Learning Research Group**and**Oxford-Man Institute of Quantitative Finance**at the**University of Oxford**under the supervision of Steve Roberts and Stefan Zohren. - I’m interested in Bayesian Continual Learning and their applications to RL and finance.
- I did my first degree in Physics at Imperial College London, then a masters in Statistics at ETH Zurich.

- I will be giving a talk about my research at the AI group research seminar at Dept. of Computer Scicene at the University of Bath on 30/06/21.
- I’ll be presenting my work Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning as a spotlight presentation at UAI 2021.
- I will be interning Huawei Cambridge and applying ideas in Continual Learning to Self-Supervised Automatic Speech Recognition.
- I will be giving a talk about my reserch at the 13th Oxford-Man Institute Machine Learning Workshop on 22nd April 2021.
- I’m sub-reviewing for Neurips 2020 and ACML 2020.
- I’m presenting my work on Practical Bayesian Neural Networks via Adaptive Optimization Methods at the Uncertainty and Robustness workshop and UNCLEAR: A Straightforward Method for Continual Reinforcement Learning at the Continual Learning workshop, both at ICML 2020.
- I’m an external reviewer for IJCAI 2020.
- I’m presenting my work Indian Buffet Neural Networks for Continual Learning at the Bayesian Deep Learning workshop at Neurips 2019 in Vancouver.
- I was selected to attend MLSS Moscow in September 2019.

- Kessler, Samuel et al. “Same State, Different Task: Continual Reinforcement Learning without Interference”, arXiv.
- We show that how leaders emerge in open source software projects in Follow the Leader: Technical and Inspirational Leadership in Open Source Software with Dr. Jerome Hergueux, research done while at ETH Zurich.

- Kessler, Samuel et al. “Continual-wav2vec2: an Application of Continual Learning for Self-Supervised Automatic Speech Recognition”, arXiv, ICML 2021 Workshop: Self-Supervised Learning for Reasoning and Perception.
- Kessler, Samuel, et al. “Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning”, arXiv
*spotlight*, UAI 2021, code. - Kessler, Samuel, et al. UNCLEAR: A Straightforward Method for Continual Reinforcement Learning, ICML 2020 Continual Learning workshop.
- Kessler, Samuel, et al. Indian Buffet Neural Networks for Continual Learning. Neurips 2019 BDL Workshop.
- Kessler, Samuel and Salas, Arnold et al. Practical Bayesian Learning of Neural Networks via Adaptive Optimisation Methods. ICML 2020 Workshop on Uncertainty and Robustness in Deep Learning, arXiv, code.

- Teaching Assistant HT 2021, Applied Machine Learning, Graduate Course, Oxford Univeristy, Oxford Internet Institute.
- Teaching Assistant MT 2020, Machine Learning, Graduate Course, Oxford Univeristy, Oxford Internet Institute.

skessler{at}robots{dot}ox{dot}ac{dot}uk / GitHub/Twitter/Linkedin.