Chair: Dr. Carla Di Cairano-Gilfedder (BT)

Dr Carla Di Cairano-Gilfedder is Distinguished Engineer - Artificial Intelligence and Optimisation research manager at BT Group Research where she has been for over 20 years following a doctorate in maths (Univ. of Southampton, UK) working on numerous projects applying maths widely to network performance, security, and operations. She currently leads R&D offering technical thought-leadership in the applications of AI/ML/Computer Vision to operations’ automation. She has contributed to many past successful external collaborations (UK, EU funded) with industry and academia. She has published in leading journals/conferences and holds several patents (35+ filed and 10+ granted). She was recipient of personal excellence awards including ITP Innovator of Year 2025 and TechWomen100 2025 and several joint awards including BCS UK IT Industry Awards -Winner of IT Project Team of the Year (2016). She serves at Editorial Board and Advisory Board level, advising on industrial application of AI and the interplay with long-established operational research methods. She is Fellow of IMA and member of the OR Society, CEng and CITP MBCS.

Dr Mark Post (University of York)

Safety, Trust, and Perception of Generative AI: Is it deceiving us, or are we deceiving ourselves?

Generative Artificial Intelligence has seemingly taken the world by storm. Thanks to advancements in computing hardware, open learning algorithms, and the availability of vast datasets on the Internet, models with billions to trillions of parameters are now capable of Human-like responses based on far more knowledge than `Humanly` possible. The story of Artificial Intelligence is that of a species seeking safe, trustworthy companionship with our Engineered, mechanistic companions. But are we giving this `Intelligence` too much credit? Can we, or should we, trust an automaton that we have created in our own image as our equal? Or have we somehow elevated it to a level that we want to trust more than ourselves? The future of Generative AI will critically depend not only on its own true capabilities, but also our perception of them.

Dr. Mark Post received his MSc and PhD in Space Engineering from York University in Canada, and is currently a Senior Lecturer in Intelligent Systems and Robotics at the University of York in the UK. His research focuses on intelligent, adaptable autonomous robots and cyber-physical systems for space and other challenging and distant environments. He has created autonomous agricultural mapping systems, probabilistic sensor fusion and control algorithms for orbital and planetary vehicles, tensegrity and bio-inspired land and underwater robots, and communicating modules capable of knowledge-based self-reconfiguration.

Dr Erfu Yang (University of Strathclyde, UK)

Generative AI in Robotics and Automation: Applications, Advancements and Challenges

The rapid advancement of generative AI is transforming robotics and automation. The advanced generative AI technologies offer unprecedented capabilities by enabling robots to perform complex tasks through improved learning, perception, adaptation and control. However, integrating generative AI with robotics and automation in complex, uncertain, dynamic, and unstructured environments remains a significant challenge. This talk highlights some applications and recent advancements of generative AI in robotics and automation, addressing key challenges towards reliable and trustworthy real-world deployment in challenging environments, especially around natural multimodal human-robot interactions.

Dr. Erfu Yang is a Reader of Robotics and Autonomous Systems in the Department of Design, Manufacturing and Engineering Management (DMEM), University of Strathclyde, Glasgow, UK. He is the Co-lead of Robotics and Autonomous Systems (RAS) Group, Programme Lead of MSc in Mechatronics and Automation. He has led several innovative projects over £1.5M awarded by UKRI, Royal Society, High-Value Manufacturing Catapult, EUREKA, NZTC, University and industries etc, including the development of an intelligent collaborative robot system and human-robot collaboration for flexible manufacturing and advanced healthcare. His recent research focuses on the integration of Generative AI with robotics and healthcare, including developing a Multimodal Intelligent Cognitive Assessment (MICA) framework which integrates Generative AI with social robots to perform early cognitive interventions for dementia and other cognitive impairments. He also explores using AI such as Deep Convolutional Generative Adversarial Networks (DCGANs) in Smart Manufacturing and robotic automation, and investigates adaptive path planning and visual navigation for autonomous inspection robots, aiming to enhance safety, efficiency, and flexibility in manufacturing and beyond.

Dr. Yang is the Stanford’s Top 2% Scientist in both 2024 and 2025. He is the Senior Member of the IEEE Society of Robotics and Automation, IEEE Systems, Man, and Cybernetics Society, Engagement Chair of the IEEE UK and Ireland Industry Applications Chapter. He serves as an associate editor and editorial board member for many international journals, including Cognitive Computation, Sensors, Manufacturing Review, Frontiers in Robotics and AI.