Invited Speakers

Evolution, immunity and robots: An interdisciplinary adventure

Biology has been a rich source of inspiration to computer science and engineering for decades.  Evolution has provided inspiration for the design of algorithms that can produce novel and, sometimes quite bizarre solutions to engineering problems.  The immune system is a complex, adaptive system that affords protection to the host. The immune system has evolved to learn, remember and adapt to changing environments and like evolution, has provided inspiration for a myriad of engineering solutions.  This talk will explore how evolution and the immune system can be modelled and then used to develop novel solutions in the context of robotics, both individual robots and swarms of robots.

Jon  Timmis

Prof. Jon Timmis is currently Vice-Chancellor at Aberystwyth University; he was formerly Deputy Vice-Chancellor at the University of Sunderland and Professor of Intelligent and Adaptive Systems. Jon graduated in Computer Science from Aberystwyth University and went on to study a PhD at Aberystwyth in the area of artificial intelligence, with a focus on the immune system. Over the last 22 years, his research has focused on the intersection of immunology, computational and mathematical modelling, machine learning, robotics and swarm robotics. Jon left Aberystwyth to take up a Lectureship at the University of Kent in 2000, then moved to the University of York in 2005 as a Reader and was promoted to Professor in 2008. At York, Jon held a joint appointment between Computer Science and Electronic Engineering for 6 years, before moving full time to Electronic Engineering where he was first Head of Research and then Head of Department. He was then Pro-Vice-Chancellor for Partnerships and Knowledge Exchange before taking up the role as Deputy Vice-Chancellor at Sunderland in 2019. Jon is a previous recipient of a Royal Society-Wolfson Research Merit Award and a Royal Academy of Engineering Enterprise Fellowship. Jon co-founded a company to commercialise his research in modelling and simulation applied in the pharmaceutical industry in 2014.

Evolving swarms across scales: from nanomedicine to city logistics

As robot swarms move from the laboratory to application, we will need to make them easy to design, monitor, control, and validate. Yet the decentralised nature of swarms makes each of these steps challenging. In this talk we look at mechanisms to evolve ‘swarms for people’, in applications ranging from medicine to environmental monitoring and logistics. We highlight technical properties of swarms, such as proficiency, scalability, robustness, and adaptability and their role in building trust. Finally, we discuss the future of swarm robotics and conclude by suggesting areas of advancement which may help build human and society’s trust towards robot swarms.

Sabine Hauert

Sabine Hauert is Professor of Swarm Engineering at the University of Bristol in the UK. Her research focusses on making swarms for people, and across scales, from nanorobots for cancer treatment, to larger robots for environmental monitoring, or logistics. Profoundly cross-disciplinary, Sabine works between Engineering Mathematics, the Bristol Robotics Laboratory, and Life Sciences. She’s PI or Co-I on more than 30M GBP in grant funding and has served on national and international committees, including the UK Robotics Growth Partnership, the Royal Society Working Group on Machine Learning and Data Community of Interest, and several IEEE boards. Before joining the University of Bristol, Sabine engineered swarms of nanoparticles for cancer treatment at MIT, and deployed swarms of flying robots at EPFL.

Sabine is also President and Co-founder of, and executive trustee of, two non-profits dedicated to connecting the robotics and AI communities to the public.

As an expert in science communication with 15 years of experience, Sabine is often invited to discuss the future of robotics and AI, including in the journals Science and Nature, at the European Parliament, and at the Royal Society. Her work has been featured in mainstream media including BBC, CNN, The Guardian, The Economist, TEDx, WIRED, and New Scientist.