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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
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Posts
Neurosymbolic AI: The Key to Safer and More Interpretable Intelligence?
Published:
This post argues that neurosymbolic AI - by combining the pattern-learning strength of neural networks with the logical structure of symbolic reasoning — offers a promising path toward building interpretable, trustworthy, and safe AI systems
Unifiers and Diversifiers: A Cyclical Dichotomy
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This post summarizes work by Professor Gavin Brown, a lecturer at the University of Manchester, who delivered a captivating talk on a dichotomy of scientific styles: Unifying and Diversifying.
The Interactive AI Research Showcase
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This post reports on events from the 2022 IAI CDT Winter Showcase at the Univeristy of Bristol. A similar post can be found on the IAI CDT website.
portfolio
Portfolio item number 1
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Short description of portfolio item number 1
Portfolio item number 2
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Short description of portfolio item number 2
publications
Deep SAGA: a Deep-learning-based System for Automatic Gaze Annotation from Eye-tracking Data
Published in Behavior Research Methods, 2022
This paper presents a novel system for automatic annotation of gaze tracking data using Mask R-CNN.
Recommended citation: Deane, O., Toth, E., Yeo, S. (2022). Deep SAGA: a Deep-learning-based System for Automatic Gaze Annotation from Eye-tracking Data. Behavior Research Methods. 1(1). https://link.springer.com/article/10.3758/s13428-022-01833-4
End-user-centered Interactive Explanatory Relational Learning with Inductive Logic Programming
Published in NeurIPS 2022: Workshop on Human in the Loop Learning, 2022
This paper explores how logic-based Human-in-the-loop Learning (HILL) systems can help users more effectively deal with confounding factors in relational data.
Recommended citation: Deane, O., Ray, O. (2022). End-user-centered Interactive Explanatory Relational Learning with Inductive Logic Programming. Human in the Loop Learning at NeurIPS 2022. 1(1).
Neuro-Symbolic Inverse Constrained Reinforcement Learning.
Published in 19th Conference on Neurosymbolic Learning and Reasoning, 2025
This paper presents a neuro-symbolic framework that derives social norms governing an environment by interleaving exploration-driven neural policy learning with symbolic norm generation from expert examples.
Recommended citation: Deane, O., & Ray, O. Neuro-Symbolic Inverse Constrained Reinforcement Learning. In 19th International Conference on Neurosymbolic Learning and Reasoning.
A Human-in-the-Loop Approach to Learning Social Norms and Behavioural Policies.
Published in 3rd International Conference on Explainable AI, 2025
This paper presents a suite of interactive mechanisms that enables human-in-the-loop inference of reinforcement learning constraints.
Recommended citation: Deane, O., Ray, O. (2025). A Human-in-the-Loop Approach to Learning Social Norms and Behavioural Policies.. 3rd International Conference on Explainable AI. 1(1).
talks
Talk 1 on Relevant Topic in Your Field
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Artificial Intelligence
Postgraduate Course, University of Bristol, Department of Computer Science, 2021
This unit provides an introduction to the field of artificial intelligence (AI) from the perspective of logic programming. The first half covers the basic principles of knowledge representation and automated inference with the Prolog programming language. The second half covers more advanced methods in natural language processing and machine learning which exploit the representation and reasoning power of Prolog. I am a teaching assistant on this course.
Introduction to Machine Learning
Postgraduate course, University of Bristol, Department of Computer Science, 2022
This unit gives a general introduction to the ideas and the tasks of Artificial Intelligence, with an emphasis on their applications across a range of disciplines, their impact on science and industry, and on their mathematical foundations. I am a lab demonstrator on this course.
Applied Data Science
Postgraduate Course, University of Bristol, Department of Computer Science, 2023
This unit is designed as an introduction to a range of Data Science topics and techniques and a chance for students to gain some practical experience with applying these to real data. It covers topics such as: ethics and privacy, data ingress, storage, wrangling, fusion, exploration and visualization and deployment of data science systems. I work as a teaching assistant and a supervisor to several groups during the coursework assessment period.