British Science Association debate: Robotics

It is no longer a question of whether machines will ever outperform human intelligence. The question is “when”? Artificial intelligence, machine vision and physical movement technologies are capable of stirring both fear and hope. Are super intelligent machines threatening our very existence? Or will they help us solve some of our biggest problems, such as crop production and access to medical health in third-world countries?

Join us when the Cambridgeshire British Science Association is hosting a public debate on artificial intelligence on 3rd March from 6:30 - 8:00 pm at The Science Lecture Room at Hill’s Road Sixth Form College (details: http://www.hillsroad.ac.uk/facilities/room-hire/room-hire-detail/lecture-room). With the famous Naked Scientist, Ginny Smith, in the chair position and four renowned speakers, this is bound to be a lively and insightful evening!

Get you free ticket here:
www.bsa-robotics.eventbrite.com

Speaker information:
Dr Fumiya IIda (Machine Intelligence Lab, University of Cambridge)
Dr Ilda received his bachelor and master degrees in mechanical engineering at Tokyo University of Science (Japan, 1999), and Dr. sc. nat. in Informatics at University of Zurich (2006). In 2004 and 2005, he was also engaged in biomechanics research of human locomotion at Locomotion Laboratory, University of Jena (Germany). From 2006 to 2009, he worked as a postdoctoral associate at the Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology in USA. In 2006, he was awarded the Fellowship for Prospective Researchers from the Swiss National Science Foundation, and in 2009, he was appointed as a Swiss National Science Foundation Professor for bio-inspired robotics at ETH Zurich. His research interests include biologically inspired robotics, embodied artificial intelligence, and biomechanics, and he has been involved in a number of research projects related to dynamic legged locomotion, navigation of autonomous robots, and human-machine interactions.
Dr Sean Holden (Machine Intelligence Lab, University of Cambridge)
Dr Holden is University Senior Lecturer in Machine Learning and Fellow and Director of Studies in Computer Science at Trinity College Cambridge. He obtained his BSc in Electronic Systems Engineering from the University of East Anglia and his PhD in Information Engineering from Cambridge University. He was postdoctoral researcher at King's College London and Cambridge University Engineering Department before taking up a Lectureship in Computer Science at University College London, where he set up and ran the MSc programme in Intelligent Systems. He was appointed Lecturer in Machine Learning in Cambridge in 2002.
He currently teaches the courses Artificial Intelligence I and Artificial Intelligence II to second and third year students respectively. Dr Holden’s research interests include: machine learning algorithms, computational learning theory, Bayesian inference and Bayes networks, planning algorithms, functional languages for machine learning, probabilistic programming languages, application of machine learning in theorem proving, drug design, retinal opthalmology and organelle proteomics.
Dr Thrishantha Nanayakkara (Centre for Robotics Research, Kings College London)
Dr Nanayakkara’s group is interested in understanding how and why the brain sometimes withdraws from direct close loop control between sensed states and actions to an indirect mode of involvement where it controls joint impedance to partially allow passive dynamic control in the body. When required, it gives up control altogether to prevent damage to the body. Though most robots still find it difficult to cover this whole spectrum of control modes, they provide a good paradigm to test many underlying hypotheses.
Dr Edward Johns (Dyson Robotics Lab, Imperial College London)
Dr Johns received a BA and MEng from University of Cambridge, after which he moved to Imperial College London to complete his PhD. Following a year at UCL, he returned to Imperial to help set up the Dyson Robotics Lab. As a Dyson Research Fellow, he works in computer vision, robotics, and machine learning. His research involves developing new techniques for computers to understand and interpret images. In turn, this aims to equip robots with capacities such as recognising, picking up and manipulating an object, or reconstructing the 3D geometry of a room and navigating through it.