Dr Bertie Muller

Research Highlights

1. Williams, S., Ware, J., Müller, B., & Muller, B. (2019). Ethical Surveillance: Applying Deep Learning and Contextual Awareness for the Benefit of Persons Living with Dementia. In Artificial Intelligence in Health-47). Springer Nature Switzerland AG.

   https://doi.org/10.1007/978-3-030-12738-1_3, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa48681

   https://www.springer.com/gp/book/9783030127374
2. Williams, S., Ware, J., & Muller, B. (2018). Preserving safety, privacy and mobility of persons living with Dementia by recognising uncharacteristic out-door movement using Recurrent Neural Networks with low computing capacity. In Proceedings of the First Joint Workshop on AI in Health organized as part of the Federated AI Meeting (FAIM 2018), co-located with AAMAS 2018, ICML 2018, IJCAI 2018 and ICCBR 2018 (pp. 212-223). AIH 2018 - Joint Workshop on AI in Health.

   SU Repository: https://cronfa.swan.ac.uk/Record/cronfa43607

   http://ceur-ws.org/Vol-2142/
3. Williams, S., Müller, B., & Muller, B. (2017). Agents and Dementia — Smart Risk Assessment. In Multi-Agent Systems and Agreement Technologies (pp. 277-284). EUMAS 2016.

   https://doi.org/10.1007/978-3-319-59294-7_22, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50296

   https://link.springer.com/chapter/10.1007/978-3-319-59294-7_22
4. Abdullahi, I. & Muller, B. (n.d.) Towards Efficient Verification of Elementary Object Systems. In Proceedings of the 25th International Workshop on Concurrency, Specification and Programming (pp. 86-100). Concurrency, Specification, and Programming (CS&P 2016).

   SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50306

   http://ceur-ws.org/Vol-1698/CS&P2016_09_Abdullahi&Mueller_Towards-Efficient-Verification-of-Elementary-Object-Systems.pdf
5. Muller, B. & Betts, J. (2014). Engineering MAS - A Device Integration Framework for Smart Home Environments.. Fundamenta Informaticae, 135(4), 341-353.

   https://doi.org/10.3233/FI-2014-1127, SU Repository: https://cronfa.swan.ac.uk/Record/cronfa50304

All Research

• Expanding and Assembling Approaches to Improve Decisions on Identification and Classification of Online Terrorist Content (current)

  PhD

  Other supervisor: Dr Muneeb Ahmad

• The Extreme Right, Online Propaganda, and Hybrid Human-Automated Content Removal (current)

  PhD

  Other supervisor: Dr Lella Nouri

• Explainable AI Techniques for Informed and Fair Decision Making (current)

  PhD

  Other supervisor: Dr Monika Seisenberger

• CSC325 Artificial Intelligence

  CSC325 is an introduction to Artificial Intelligence, focusing primarily on reasoning and problem solving as a search for a solution rather than on statistical techniques for classification. The course may cover topics from amongst: search techniques; knowledge representation and expert systems; planning; scheduling; qualitative reasoning; language processing with grammar rules; and meta-programming, as well as agents, multi-agent systems, and agent collaboration.

• CSCM08 Information Security Management

  This module will address the theory and practice of information security. In particular, it will consider where data comes from, who collects it and what they can do with it. It will further look into theories of monitoring and surveillance, digital identity, legal and regulatory frameworks, data protection, cybercrime, business resilience, disaster recovery, and security audits.

• CSCM23 Designing-in Trust, Understanding and Negotiation

  This module explores state-of-the-art methods and concepts to assist responsible design and development of technology with the aim of creating reliable and trusted systems. The content of this module will be delivered by expert lecturers and practitioners in the areas of trusted computation, bias and explainability in automated decision making and decision support, ethical considerations for AI, argumentation and negotiation, as well as formal methods, such as verification of critical systems.