Distinguished lectures
A series of distinguished lectures which aim to present excellent speakers exploring intriguing topics in an engaging style.
The Informatics Distinguished Lectures address a broad audience, that includes all members of the School of Informatics, members of the University and the general public. Invitations to provide a Distinguished Lecture are issued by the Head of School on the recommendation of the School's Director of Research and the Director(s) of the relevant Research Institute(s).
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Upcoming Lectures
- TBC
Previous lectures
Speaker |
Position |
Talk Details |
Bio |
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Andrew Fitzgibbon FREng |
Research Theme Lead, Microsoft Cambridge, UK |
Making Computer Vision Systems that Work: Boujou, Kinect, HoloLens
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Andrew Fitzgibbon leads the "All Data AI" (ADA) research group at Microsoft in Cmabridge, UK. He is a computer vision researcher, best known for his work on 3D vision, having been a core contributor to the Emmy-award-wining 3D camera tracker "boujou", to body tracking for Kinect for Xbox 360, and for the articulated hand-tracking interface to Microsoft's Hololens. He has published numerous highly-cited papers, and received many awards for his work, including ten “best paper” prizes at various venues, the Silver medal of the Royal Academy of Engineering, and the BCS Roger Needham award. |
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Mari Ostendorf IEEE Fellow
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System Design Methodologies Professor, Associate Vice Provost for Research, University of Washington |
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Mari Ostendorf joined the University of Washington in 1999. She is an Endowed Professor of System Design Methodologies in the Electrical & Computer Engineering Department, an Adjunct Professor in Linguistics and in Computer Science & Engineering, and Associate Vice Provost for Research. She is a Fellow of the IEEE, ISCA and ACL, a Scottish Informatics and Computer Science Alliance Distinguished Visiting Fellow, a former Australian-American Fulbright Scholar, and a member of the Washington State Academy of Sciences. |
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Brian Cantwell Smith PhD |
Reid Hoffman Professor of Artificial Intelligence and the Human, Professor of Information, Philosophy, Cognitive Science, and the History and Philosophy of Science and Technology, Massey College
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Brian Cantwell Smith holds BS, MS and PhD degrees from the Massachusetts Institute of Technology (MIT). From 1981 to 1996 he was a Principal Scientist at the Xerox Palo Alto Research Center (PARC) and Adjunct Professor of Philosophy at Stanford University. From 1996 to 2001 he was Professor of Cognitive Science, Computer Science, and Philosophy at Indiana University, and from 2001 to 2003 was Kimberly J. Jenkins University Distinguished Professor of Philosophy and New Technologies at Duke University. Smith moved to the University of Toronto in 2003, initially to serve as Dean of the Faculty of Information (2003–2008). | |
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Michael Kölling FBCS |
Vice Dean (Education) in the Faculty of Natural & Mathematical Sciences and Professor of Computer Science, King's College London |
Michael Kölling holds a PhD in computer science from Sydney University, and has worked in Australia, Denmark and the UK. He has published numerous papers on object-orientation and computing education topics and is the author and co-author of two Java textbooks. He is a UK National Teaching Fellow, Fellow of the UK Higher Education Academy, Oracle Java Champion, and a Distinguished Educator of the ACM. In 2013, he received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education.
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| Barbara Grosz CorrFRSE | Higgins Research Professor of Natural Sciences in the School of Engineering and Applied Sciences, Harvard University |
From Ethical Challenges of Intelligent Systems to Embedding Ethics in Computer Science Education
|
Barbara Grosz is Higgins Research Professor of Natural Sciences in the School of Engineering and Applied Sciences at Harvard University and a member of the External Faculty of Santa Fe Institute. She has made ground-breaking contributions to the field of Artificial Intelligence (AI) through her pioneering research in natural language processing and in theories of multi-agent collaboration and their application to human-computer interaction. Her current research explores ways to use models developed in this research to improve health care coordination and science education. |
| Rami Bahsoon FRSE | Senior Lecturer (Associate Professor) at the School of Computer Science, University of Birmingham |
Dr Rami Bahsoon's research is in the area of software architecture, cloud and services software engineering, self-aware software architectures, self-adaptive and managed software engineering, economics-driven software engineering and technical debt management in software. He co-edited four books on Software Architecture, including Economics-Driven Software Architecture; Software Architecture for Big Data and the Cloud; Aligning Enterprise, System, and Software Architecture. He is a fellow of the Royal Society of Arts and Associate Editor of IEEE Software - Software Economies.
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J.P. de Ruiter APS Fellow |
Bridge Profesor in the Cognitive Sciences, Tufts University (Medford, Massachusetts) |
Jan (J.P.) de Ruiter is a cognitive scientist whose primary research focus is on the cognitive foundations of human communication. He has published in linguistic, psycholinguistic, methodological, neurocognitive, and cognitive-psychological journals. His interests include conversation analysis, philosophy of science, artificial intelligence, and inferential statistics. He has initiated and/or been involved in several large-scale European and US projects in social robotics, focusing on collaborative interaction between humans and artificial systems.
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| Kimberley Hambuchen PhD | NASA Space Technology Mission Directorate's (STMD) Principal Technologist for Robotics |
NASA Robotics Technology Development
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As Principal Technologist, Dr. Kimberly Hambuchen serves as the STMD technical expert and advocate for robotics development across all NASA centers for STMD programs. She has spent the last 20 years at NASA’s Johnson Space Center developing software and applications to advance the intelligence, usefulness and operational intuitiveness of NASA robots, including Robonauts 1 and 2, the Space Exploration Vehicle (SEV), and the bipedal humanoid, Valkyrie. |
| Moshe Vardi Guggenheim Fellow | George Distinguished Service Professor in Computational Engineering, Director of the Ken Kennedy Institute for Information Technology, Rice University |
Moshe Y. Vardi is the recipient of numerous awards, including three IBM Outstanding Innovation Awards, the ACM SIGACT Goedel Prize, and the ACM Kanellakis Award. He is a Fellow of the Association for Computing Machinery, the American Association for Artificial Intelligence, the American Association for the Advancement of Science, the European Association for Theoretical Computer Science, the Institute for Electrical and Electronic Engineers, and the Society for Industrial and Applied Mathematics. He is currently a Senior Editor of the Communications of the ACM, having served for a decade as Editor-in-Chief.
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| David Dunson FASA | Arts and Sciences Distinguished Professor of Statistical Science, Mathematics, and Electrical & Computer Engineering, Duke University |
Machine learning for scientific inferences: Debunking the Hype |
David Dunson's research focuses on Bayesian statistical theory and methods motivated by high-dimensional and complex applications. His work involves inter-disciplinary thinking at the intersection of statistics, mathematics and computer science. Professor Dunson is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. He is winner of the 2007 Mortimer Spiegelman Award, the 2010 Myrto Lefkopoulou Distinguished Lectureship at Harvard University, the 2010 COPSS Presidents' Award, and the 2012 Youden Award for inter-laboratory testing methods.
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| Thomas G. Diettrich FACM | Professor Emeritus and Director of Intelligent Systems Research in the School of Electrical Engineering and Computer Science, Oregon State University |
Dr. Dietterich is one of the pioneers of the field of Machine Learning and has authored more than 190 refereed publications and two books. His research is motivated by challenging real world problems with a special focus on ecological science, ecosystem management, and sustainable development. He is best known for his work on ensemble methods in machine learning including the development of error-correcting output coding. Dietterich has also invented important reinforcement learning algorithms including the MAXQ method for hierarchical reinforcement learning.
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Distinguished lectures that took place before 2018 have been archived.