Dr Jonathan Francis Roscoe (BT Applied Research)

Automated Cyber Threat Detection and Response

Cyber defence is traditionally managed in direct response to vulnerabilities and threats within an IT system. However, security is a non-exhaustive exercise and in the face of an ever-changing threat landscape with highly-motivated threat actors there is a strong need to automate our cyber capabilities. In this talk we’ll explore how artificially intelligence and machine techniques are being practically deployed for the protection of enterprise networks and critical infrastructure. Firstly, we’ll how we better utilise threat intelligence and network telemetry to detect threat activity on our networks. AI/ML technologies are powerful tools to enhance the work of security professionals faced with increasingly complex and broad challenges. We’ll discuss practical measures in augmenting human expertise with new automated technology. We’ll go on to explore the use of reinforcement learning to drive the simulation of threat events on our network in order to automate the response to developing events. Such simulation can support red/blue-team testing in a much more exhaustive manner.

Jonathan Francis Roscoe leads the Automated Detection and Response research group at BT. Jonathan is responsible for managing teams of researchers delivering innovation in cyber defence for BT and its customers. His research interests include anomaly detection, neural networks, malware, red-teaming, disinformation, privacy and open-source intelligence. His work investigating dark web marketplaces and malware vendors was given the TEISS Information Security award and ITP Innovator of the Year. Outside of BT, Jonathan is chair of the IEEE UK&I Cyber Security group as well as an expert fellow to the SPRITE+ network on security, privacy and identity.

Dr Giovanna Martinez-Arellano (University of Nottingham)

AI in Manufacturing: Applications and Challenges

Giovanna Martinez-Arellano has a PhD in Computer Science from Nottingham Trent University and is currently an Anne McLaren Research Fellow in Digital and Smart Manufacturing at the Institute for Advanced Manufacturing at the University of Nottingham. Her area of research particularly focuses on the development of robust Machine Learning models for complex and reconfigurable manufacturing systems.

Dr Fernando Oliveira (University of Bradford)

Using Evolutionary Algorithms to Simulate Land Use Change: The Case of Auckland

In this project we analyze land use change in Auckland. First, we used multinomial logistic regression with geographical cell-level data to analyze the determinants of land usage. We combine logistic regression with real options to explain land-use patterns. Then we use cellular automata to simulate land use change. Our study offers crucial insights for policymakers. Firstly, urbanization, public transportation, and infrastructure development are associated with declining forests and vegetation. Secondly, forests are associated with hospitals, schools, and motorways. Finally, the option value for land use change increases (decreases) with economic downturns (higher volatility). We study the case of Auckland.

Fernando Oliveira is professor of Business Analytics and Sustainability and Head of Business Analytics, Circular Economy and Entrepreneurship Department at the University of Bradford School of Management. He holds a Ph.D. in Management Science and Operations from the London Business School, an MSc in Artificial Intelligence, and a Licenciatura in Economics from the University of Porto, Portugal. Before joining the University of Bradford, Fernando was Associate Professor in Operations Management and Analytics at the Auckland Business School and Professor at ESSEC business school. He has held several visiting positions, including visiting Professor of Operations Management and Analytics at the National University of Singapore and visiting researcher at Johns Hopkins. He has received two prizes for his publications, the Prix Académique SYNTEC, and the European Journal of Operational Research best paper award. His research has been published in top international journals, including Decision Sciences, Energy Economics, European Journal of Operational Research, Informs Journal on Computing, International Journal of Production Economics, Omega, and Operations Research. He is on the International Journal of Data Science editorial board, the International Journal of Business Analytics area editor, and the associate editor of Energy Systems. His teaching and research interests are in applications of artificial intelligence to managerial problems in supply chain management and, more specifically, healthcare, energy markets, and quantitative risk management.

Defence AI Centre (Speaker to be confirmed)

Practical application of AI to support defence outcomes

Dr Genovefa Kefalidou (University Of Leicester)

Human-in-the-Loop in AI-Driven Innovations: Is it still Relevant?

Validate AI (Speaker to be confirmed)

Developing more trusted AI systems