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Annual Report 2018–19
Annual report 2018–19 2018 –19 Annual Report 2018–19 Part 1 Our year 3 Part 2 Trustees’ and strategic report 74 Part 3 Financial statements 84 Our year 1.1 Chair’s foreword 1.2 Institute Director and Chief Executive’s foreword 1 1.3 Outputs, impact and equalities 1.4 Turing trends and statistics 1.5 Research mapping: Linking research, people and activities 3 Creating real world impact We have had yet another year of rapid growth Since 2016, researchers at the Institute have produced and remarkable progress. over 200 publications in leading journals and demonstrated early impacts with great potential. Some of the impacts The Alan Turing Institute is a multidisciplinary institute are captured in this annual report and we are excited to formed through partnerships with some of the UK’s see the translation of our data science and AI research leading universities. This innovative approach gives us into a real-world context. access to expertise and skills in data science and AI that is unparalleled outside of a handful of large tech platforms. We are witnessing a massive growth of data science Our substantial convening power enables us to work and AI. We are also seeing important challenges and across the economy: with large corporations, the public breakthroughs in many areas including safe and ethical sector including government departments, charitable AI, quantum computing, urban transport, defence, foundations and small businesses. These collaborations manufacturing, health and financial services. Across cut across disciplines and break through institutional the Institute we are leading the public conversation in boundaries. -
STEM Education Centre E-Bulletin: March 2014
STEM Education Centre E-bulletin: March 2014 Welcome to the March e-bulletin from the University of Birmingham’s STEM Education Centre. It is designed to provide you with information about STEM-related events, resources, news and updates that may be of interest to you and your colleagues. STEM Policy and Practice News Budget 2014: Alan Turing Institute to lead big data research A £42m Alan Turing Institute is to be founded to ensure that Britain leads the way in big data and algorithm research, George Osborne has announced. Drawing on the name of the British mathematician who led code-breaking work at Bletchley Park during the World War II, the institute is intended to help British companies by bringing together expertise and experience in tackling problems requiring huge computational power. Turing’s work led to the cracking of the German "Enigma" codes, which used highly compl ex encryption, is believed to have saved hundreds or even thousands of lives. He later formed a number of theories that underpin modern computing, and formalised the idea of algorithms – sequences of instructions – for a computer. This announcement marks further official rehabilitation of a scientist who many see as having been treated badly by the British government after his work during the war. Turing, who was gay, was convicted of indecency in March 1952, and lost his security clearance with GCHQ, the successor to Bletchley Park. He killed himself in June 1954. Only after a series of public campaigns was he given an official pardon by the UK government in December 2013. Public Attitudes to Science (PAS) 2014 Public Attitudes to Science (PAS) 2014 is the fifth in a series of studies looking at attitudes to science, scientists and science policy among the UK public. -
Gilaie-Dotan, Sharon; Rees, Geraint; Butterworth, Brian and Cappelletti, Marinella
Gilaie-Dotan, Sharon; Rees, Geraint; Butterworth, Brian and Cappelletti, Marinella. 2014. Im- paired Numerical Ability Affects Supra-Second Time Estimation. Timing & Time Perception, 2(2), pp. 169-187. ISSN 2213-445X [Article] http://research.gold.ac.uk/23637/ The version presented here may differ from the published, performed or presented work. Please go to the persistent GRO record above for more information. If you believe that any material held in the repository infringes copyright law, please contact the Repository Team at Goldsmiths, University of London via the following email address: [email protected]. The item will be removed from the repository while any claim is being investigated. For more information, please contact the GRO team: [email protected] Timing & Time Perception 2 (2014) 169–187 brill.com/time Impaired Numerical Ability Affects Supra-Second Time Estimation Sharon Gilaie-Dotan 1,∗, Geraint Rees 1,2, Brian Butterworth 1 and Marinella Cappelletti 1,3,∗ 1 UCL Institute of Cognitive Neuroscience, 17 Queen Square, London, WC1N 3AR, UK 2 Wellcome Trust Centre for Neuroimaging, University College London, 12 Queen Square, London WC1N 3BG, UK 3 Psychology Department, Goldsmiths College, University of London, UK Received 24 September 2013; accepted 11 March 2014 Abstract It has been suggested that the human ability to process number and time both rely on common magni- tude mechanisms, yet for time this commonality has mainly been investigated in the sub-second rather than longer time ranges. Here we examined whether number processing is associated with timing in time ranges greater than a second. Specifically, we tested long duration estimation abilities in adults with a devel- opmental impairment in numerical processing (dyscalculia), reasoning that any such timing impairment co-occurring with dyscalculia may be consistent with joint mechanisms for time estimation and num- ber processing. -
Automating Data Science: Prospects and Challenges
Final m/s version of paper accepted (April 2021) for publication in Communications of the ACM. Please cite the journal version when it is published; this will contain the final version of the figures. Automating Data Science: Prospects and Challenges Tijl De Bie Luc De Raedt IDLab – Dept. of Electronics and Information Systems Dept. of Computer Science AASS Ghent University KU Leuven Örebro University Belgium Belgium Sweden José Hernández-Orallo Holger H. Hoos vrAIn LIACS Universitat Politècnica de València Universiteit Leiden Spain The Netherlands Padhraic Smyth Christopher K. I. Williams Department of Computer Science School of Informatics Alan Turing Institute University of California, Irvine University of Edinburgh London USA United Kingdom United Kingdom May 13, 2021 Given the complexity of typical data science projects and the associated demand for human expertise, automation has the potential to transform the data science process. Key insights arXiv:2105.05699v1 [cs.DB] 12 May 2021 • Automation in data science aims to facilitate and transform the work of data scientists, not to replace them. • Important parts of data science are already being automated, especially in the modeling stages, where techniques such as automated machine learning (Au- toML) are gaining traction. • Other aspects are harder to automate, not only because of technological chal- lenges, but because open-ended and context-dependent tasks require human in- teraction. 1 Introduction Data science covers the full spectrum of deriving insight from data, from initial data gathering and interpretation, via processing and engineering of data, and exploration and modeling, to eventually producing novel insights and decision support systems. Data science can be viewed as overlapping or broader in scope than other data-analytic methodological disciplines, such as statistics, machine learning, databases, or visualization [10]. -
Neural Correlates of Consciousness
Ann. N.Y. Acad. Sci. ISSN 0077-8923 ANNALS OF THE NEW YORK ACADEMY OF SCIENCES Issue: The Year in Cognitive Neuroscience Neural correlates of consciousness Geraint Rees UCL Institute of Cognitive Neuroscience and Wellcome Trust Centre for Neuroimaging, University College London, London, United Kingdom Address for correspondence: Professor Geraint Rees, UCL Institute of Cognitive Neuroscience, 17 Queen Square, London WC1N 3AR, UK. [email protected] Jon Driver’s scientific work was characterized by an innovative combination of new methods for studying mental processes in the human brain in an integrative manner. In our collaborative work, he applied this approach to the study of attention and awareness, and their relationship to neural activity in the human brain. Here I review Jon’s scientific work that relates to the neural basis of human consciousness, relating our collaborative work to a broader scientific context. I seek to show how his insights led to a deeper understanding of the causal connections between distant brain structures that are now believed to characterize the neural underpinnings of human consciousness. Keywords: fMRI; vision; consciousness; awareness; neglect; extinction for noninvasive measurement of human brain Introduction activity such as functional magnetic resonance Our awareness of the external world is central to imaging (fMRI), positron emission tomography, our everyday lives. People consistently and univer- electroencephalography (EEG), and magnetoen- sally use verbal and nonverbal reports to indicate cephalography (MEG) can reveal the neural sub- that they have subjective experiences that reflect the strates of sensory processing in the human brain, sensory properties of objects in the world around and together we used these approaches to explore them. -
Alan Turing Institute Symposium on Reproducibility for Data-Intensive Research – FINAL REPORT Page | 1 Lucie C
Alan Turing Institute Symposium on Reproducibility for Data-Intensive Research – FINAL REPORT Page | 1 Lucie C. Burgess, David Crotty, David de Roure, Jeremy Gibbons, Carole Goble, Paolo Missier, Richard Mortier, 21 July 2016 Thomas E. Nichols, Richard O’Beirne Dickson Poon China Centre, St. Hugh’s College, University of Oxford, 6th and 7th April 2016 ALAN TURING INSTITUTE SYMPOSIUM ON REPRODUCIBILITY FOR DATA-INTENSIVE RESEARCH – FINAL REPORT AUTHORS Lucie C. Burgess1, David Crotty2, David de Roure1, Jeremy Gibbons1, Carole Goble3, Paolo Missier4, Richard Mortier5, Thomas E. Nichols6, Richard O’Beirne2 1. University of Oxford 2. Oxford University Press 3. University of Manchester 4. Newcastle University 5. University of Cambridge 6. University of Warwick TABLE OF CONTENTS 1. Symposium overview – p.2 1.1 Objectives 1.2 Citing this report 1.3 Organising committee 1.4 Format 1.5 Delegates 1.6 Funding 2. Executive summary – p.4 2.1 What is reproducibility and why is it important? 2.2 Summary of recommendations 3. Data provenance to support reproducibility – p.7 4. Computational models and simulations – p.10 5. Reproducibility for real-time big data – p.13 6. Publication of data-intensive research – p.16 7. Novel architectures and infrastructure to support reproducibility – p.19 8. References - p.22 Annex A – Symposium programme and biographies for the organising committee and speakers Annex B – Delegate list ACKNOWLEDGEMENTS The Organising Committee would like to thanks the speakers, session chairs and delegates to the symposium, and in particular all those who wrote notes during the sessions and provided feedback on the report. This report is available online at: https://osf.io/bcef5/ (report and supplementary materials) https://dx.doi.org/10.6084/m9.figshare.3487382 (report only) Alan Turing Institute Symposium on Reproducibility for Data-Intensive Research – FINAL REPORT Page | 2 Lucie C. -
CV Adilet Otemissov
CV Adilet Otemissov RESEARCH INTERESTS Global Optimization; Stochastic Methods for Optimisation; Random Matrices EDUCATION DPhil (PhD) in Mathematics 2016{2021 University of Oxford The Alan Turing Institute, the UK's national institute for data science and AI - Thesis title: Dimensionality reduction techniques for global optimization (supervised by Dr Coralia Cartis) MSc in Applied Mathematics with Industrial Modelling 2015{2016 University of Manchester - Thesis title: Matrix Completion and Euclidean Distance Matrices (supervised by Dr Martin Lotz) BSc in Mathematics 2011{2015 Nazarbayev University AWARDS & ACHIEVEMENTS - SEDA Professional Development Framework Supporting Learning award for successfully completing Developing Learning and Teaching course; more details can be found on https://www.seda.ac.uk/supporting-learning, 2020 - The Alan Turing Doctoral Studentship: highly competitive full PhD funding, providing also a vibrant interdisciplinary research environment at the Institute in London, as well as extensive training in the state-of-the-art data science subjects from world's leading researchers, 2016{2020 - NAG MSc student prize in Applied Mathematics with Industrial Modelling for achieving the highest overall mark in the numerical analysis course units in my cohort at the University of Manchester, 2016 PUBLICATIONS - C. Cartis, E. Massart, and A. Otemissov. Applications of conic integral geometry in global optimization. 2021. Research completed, in preparation - C. Cartis, E. Massart, and A. Otemissov. Constrained global optimization of functions with low effective dimensionality using multiple random embeddings. ArXiv e-prints, page arXiv:2009.10446, 2020. Manuscript (41 pages) submitted for publication in Mathematical Programming. Got back from the first round of reviewing - C. Cartis and A. Otemissov. A dimensionality reduction technique for unconstrained global optimization of functions with low effective dimensionality. -
Phenomenal Consciousness As Scientific Phenomenon? a Critical Investigation of the New Science of Consciousness
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by D-Scholarship@Pitt PHENOMENAL CONSCIOUSNESS AS SCIENTIFIC PHENOMENON? A CRITICAL INVESTIGATION OF THE NEW SCIENCE OF CONSCIOUSNESS by Justin M. Sytsma BS in Computer Science, University of Minnesota, 2003 BS in Neuroscience, University of Minnesota, 1999 MA in Philosophy, University of Pittsburgh, 2008 MA in History and Philosophy of Science, University of Pittsburgh, 2008 Submitted to the Graduate Faculty of School of Arts & Sciences in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2010 UNIVERSITY OF PITTSBURGH SCHOOL OF ARTS & SCIENCES This dissertation was presented by Justin M. Sytsma It was defended on August 5, 2010 and approved by Peter Machamer, PhD, Professor, History and Philosophy of Science Anil Gupta, PhD, Distinguished Professor, Philosophy Jesse Prinz, PhD, Distinguished Professor, City University of New York Graduate Center Dissertation Co-Director: Edouard Machery, PhD, Associate Professor, History and Philosophy of Science Dissertation Co-Director: Kenneth Schaffner, PhD, Distinguished University Professor, History and Philosophy of Science ii Copyright © by Justin Sytsma 2010 iii PHENOMENAL CONSCIOUSNESS AS SCIENTIFIC PHENOMENON? A CRITICAL INVESTIGATION OF THE NEW SCIENCE OF CONSCIOUSNESS Justin Sytsma, PhD University of Pittsburgh, 2010 Phenomenal consciousness poses something of a puzzle for philosophy of science. This puzzle arises from two facts: It is common for philosophers (and some scientists) to take its existence to be phenomenologically obvious and yet modern science arguably has little (if anything) to tell us about it. And, this is despite over 20 years of work targeting phenomenal consciousness in what I call the new science of consciousness. -
Enabling a World-Leading Regional Digital Economy Through Data Driven Innovation
©Jonathan Clark Fine Art, Representatives of the Artist's Estate Enabling a World-Leading Regional Digital Economy through Data Driven Innovation Edinburgh & South East Scotland City Region A Science and Innovation Audit Report sponsored by the Department for Business, Energy & Industrial Strategy MAIN REPORT Edinburgh and South East Scotland City Region Consortium Foreword In Autumn 2015 the UK Government announced regional Science and Innovation Audits (SIAs) to catalyse a new approach to regional economic development. SIAs enable local Consortia to focus on analysing regional strengths and identify mechanisms to realise their potential. In the Edinburgh and South East Scotland City Region, a Consortium was formed to focus on our rapidly growing strength in Data-Driven Innovation (DDI). This report presents the results which includes broad-ranging analysis of the City Region’s DDI capabilities, the challenges and the substantial opportunities for future economic growth. Data-led disruption will be at the heart of future growth in the Digital Economy, and will enable transformational change across the broader economy. However, the exact scope, scale and timing of these impacts remains unclear1. The questions we face are simple yet far-reaching – given this uncertainty, is now the right time to commit fully to the DDI opportunity? If so, what are the investments we should make to optimise regional economic growth? This SIA provides evidence that we must take concerted action now to best position the City Region to benefit from the disruptive effects of DDI. If investment is deferred, we run the risk of losing both competitiveness and output to other leading digital clusters that have the confidence to invest. -
Atypical Intrinsic Neural Timescale in Autism Takamitsu Watanabe1,2*, Geraint Rees1,3, Naoki Masuda4*
RESEARCH ARTICLE Atypical intrinsic neural timescale in autism Takamitsu Watanabe1,2*, Geraint Rees1,3, Naoki Masuda4* 1Institute of Cognitive Neuroscience, University College London, London, United Kingdom; 2RIKEN Centre for Brain Science, Wako, Japan; 3Wellcome Trust Centre for Human Neuroimaging, University College London, London, United Kingdom; 4Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom Abstract How long neural information is stored in a local brain area reflects functions of that region and is often estimated by the magnitude of the autocorrelation of intrinsic neural signals in the area. Here, we investigated such intrinsic neural timescales in high-functioning adults with autism and examined whether local brain dynamics reflected their atypical behaviours. By analysing resting-state fMRI data, we identified shorter neural timescales in the sensory/visual cortices and a longer timescale in the right caudate in autism. The shorter intrinsic timescales in the sensory/visual areas were correlated with the severity of autism, whereas the longer timescale in the caudate was associated with cognitive rigidity. These observations were confirmed from neurodevelopmental perspectives and replicated in two independent cross-sectional datasets. Moreover, the intrinsic timescale was correlated with local grey matter volume. This study shows that functional and structural atypicality in local brain areas is linked to higher-order cognitive symptoms in autism. DOI: https://doi.org/10.7554/eLife.42256.001 -
PCAST Report
INDUSTRIES OF THE FUTURE INSTITUTES: A NEW MODEL FOR AMERICAN SCIENCE AND TECHNOLOGY LEADERSHIP A Report to the President of the United States of America The President’s Council of Advisors on Science and Technology January 2021 INDUSTRIES OF THE FUTURE INSTITUTES: A NEW MODEL FOR AMERICAN SCIENCE AND TECHNOLOGY LEADERSHIP About the President’s Council of Advisors on Science and Technology Created by Executive Order in 2019, PCAST advises the President on matters involving science, technology, education, and innovation policy. The Council also provides the President with scientific and technical information that is needed to inform public policy relating to the American economy, the American worker, national and homeland security, and other topics. Members include distinguished individuals from sectors outside of the Federal Government having diverse perspectives and expertise in science, technology, education, and innovation. More information is available at https://science.osti.gov/About/PCAST. About this Document This document follows up on a recommendation from PCAST’s report, released June 30, 2020, involving the formation of a new type of multi-sector research and development organization: Industries of the Future Institutes (IotFIs). This document provides a framework to inform the design of IotFIs and thus should be used as preliminary guidance by funders and as a starting point for discussion among those considering participation. The features described here are not intended to be a comprehensive list, nor is it necessary that each IotFI have every feature detailed here. Month 2020 – i – INDUSTRIES OF THE FUTURE INSTITUTES: A NEW MODEL FOR AMERICAN SCIENCE AND TECHNOLOGY LEADERSHIP The President’s Council of Advisors on Science and Technology Chair Kelvin K. -
Artificial Intelligence Research in Northern Ireland and the Potential for a Regional Centre of Excellence
Artificial Intelligence Research in Northern Ireland and the Potential for a Regional Centre of Excellence Review Prepared by Ken Guy1 and Rob Procter2 with inputs from Franz Kiraly3 and Adrian Weller4 on behalf of The Alan Turing Institute5 April 2019 1 Ken Guy, Director, Wise Guys Ltd. 2 Professor Rob Procter, Turing Fellow, University of Warwick 3 Dr. Franz Kiraly, Turing Fellow, University College London 4 Dr. Adrian Weller, Programme Director and Turing Fellow, University of Cambridge 5 Although prepared on behalf of The Alan Turing Institute, responsibility for the views expressed in this document lie solely with the two main authors, Ken Guy and Rob Procter. Contents Foreword by Dr. Robert Grundy, Chair of Matrix ................................................................... i Foreword by Tom Gray, Chair of the Review Panel ............................................................. ii Executive Summary ................................................................................................................ vi 1. Introduction ....................................................................................................................... 11 1.1 Objectives ......................................................................................................................... 12 1.2 Expectations ..................................................................................................................... 13 1.3 Methodology ...................................................................................................................