As the programme for event develops, additional profiles of those involved will be added. Be sure to check back regularly!
Marta Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College, University of Oxford. Prior to this she was Professor in the School of Computer Science at the University of Birmingham, Lecturer at the University of Leicester and Assistant Professor at the Jagiellonian University in Cracow, Poland. Kwiatkowska has made fundamental contributions to the theory and practice of model checking for probabilistic systems, focusing on automated techniques for verification and synthesis from quantitative specifications. She led the development of the PRISM model checker (www.prismmodelchecker.org), the leading software tool in the area and winner of the HVC Award 2016. Probabilistic model checking has been adopted in many diverse fields, including distributed computing, wireless networks, security, robotics, game theory, systems biology, DNA computing and nanotechnology, with genuine flaws found and corrected in real-world protocols. Kwiatkowska was awarded an honorary doctorate from KTH Royal Institute of Technology in Stockholm in 2014 and the Royal Society Milner Medal in 2018. Her recent work was supported by the ERC Advanced Grant VERIWARE “From software verification to ‘everyware’ verification” and the EPSRC Programme Grant on Mobile Autonomy. She is a Fellow of ACM and Member of Academia Europea.
Thomas Lukasiewicz is a Professor of Computer Science in Oxford University’s Department of Computer Science since 2010. Prior to this, he was holding a prestigious Heisenberg Fellowship by the German Research Foundation (DFG), affiliated with the University of Oxford, TU Vienna, Austria, and Sapienza University of Rome, Italy. His research interests are in artificial intelligence (AI) and information systems, including especially machine/deep learning, personalised search and recommender systems, natural language processing and question answering, knowledge representation and reasoning, uncertainty in AI, the (Social/Semantic) Web, ontology-based data access, and databases. Among his recent awards are the AIJ Prominent Paper Award 2013 and the RuleML 2015 Best Paper Award. He is area editor for the journal ACM TOCL, associate editor for the journals JAIR and AIJ, and editor for the journal Semantic Web.
Paul Newman is the BP Professor of Information Engineering at the University of Oxford and an EPSRC Leadership Fellow. He heads up the Oxford Robotics Institute within the Department of Engineering Science which enjoys a world leading reputation in mobile autonomy, developing machines and robots which map, navigate through and understand their environments. You can read more about his work here.
Michael A Osborne (DPhil Oxon) works to develop machine intelligence in sympathy with societal needs. His work in Machine Learning has been successfully applied in diverse contexts, from aiding the detection of planets in distant solar systems to enabling self-driving cars to determine when their maps may have changed due to roadworks. Dr Osborne also has deep interests in the broader societal consequences of machine learning and robotics, and has analysed how intelligent algorithms might soon substitute for human workers.
Dr Osborne is the Dyson Associate Professor in Machine Learning, a co-director of the Oxford Martin programme on Technology and Employment, an Official Fellow of Exeter College, and a co-director of the EPSRC Centre for Doctoral Training in Autonomous Intelligent Machines and Systems, all at the University of Oxford.
Stephen Roberts is the RAEng-Man Professor of Machine Learning at the University of Oxford. He is a Fellow of the Royal Academy of Engineering, the Royal Statistical Society, the Institute of Physics and is a Faculty Fellow of the Alan Turing Institute. Stephen is Director of the Oxford-Man Institute of Quantitative Finance, founding-Director of the Oxford Centre for Doctoral Training in Autonomous Intelligent Machines and Systems (AIMS) and co-founder of the University Machine Learning spin-out company, Mind Foundry. He has published widely, having over 300 publications which have accrued some 19,000 citations. Stephen’s interests lie in methods for machine learning and data analysis in complex problems, especially those in which noise and uncertainty abound. His current major interests include the application of machine learning to huge astrophysical data sets (for discovering exoplanets, pulsars and cosmological models), biodiversity monitoring (for detecting changes in ecology and spread of disease), smart networks (for reducing energy consumption and impact), sensor networks (to better acquire and model complex events) and finance (to provide better insight into time-series and aggregate large numbers of unstructured information streams).
Mihaela van der Schaar
Mihaela van der Schaar is Man Professor at University of Oxford, Department of Engineering Science and Oxford Man Institute, and a Faculty Fellow at the Alan Turing Institute. Prior to this Mihaela was a Chancellor’s Professor at University of California Los Angeles (UCLA). Her research expertise is in developing novel machine learning theory and methods for medicine.
Shimon Whiteson is an Associate Professor in the Department of Computer Science at the University of Oxford, and a tutorial fellow at St. Catherine’s College.
His research focuses on artificial intelligence; to design, analyse, and evaluate the algorithms that enable computational systems to acquire and execute intelligent behaviour. His particular interests are in machine learning, with which computers can learn from experience, and decision-theoretic planning, from which they can reason about their goals and deduce behavioural strategies that maximise their utility. In addition to theoretical work on these topics, in recent years he has also focused on applying them to practical problems in robotics and search engine optimisation.
Michael Wooldridge is a Professor of Computer Science and Head of Department of Computer Science at the University of Oxford. He has been an AI researcher for more than 25 years, and has published more than 350 scientific articles on the subject. He is a Fellow of the Association for Computing Machinery (ACM), the Association for the Advancement of AI (AAAI), and the European Association for AI (EurAI). From 2014-16, he was President of the European Association for AI, and from 2015-17 he was President of the International Joint Conference on AI (IJCAI).
Andrew Zisserman leads the Visual Geometry Group in the Department of Engineering Science. Andrew’s research interests include visual recognition, image retrieval, multi-view geometry, and other aspects of computer vision. Some of Andrew’s papers are amongst the most highly cited works in the field. His contributions received multiple awards at the top computer vision conferences including three Marr prizes at the International Conferences on Computer Vision. He has published several books including “Visual Reconstruction” (with Andrew Blake) and “Multiple View Geometry in Computer Vision” (with Richard Hartley). He is a fellow of the Royal Society. You can read more about the work of his group here.