BEGIN:VCALENDAR VERSION:2.0 PRODID:-//Research on Research - ECPv6.9.1//NONSGML v1.0//EN CALSCALE:GREGORIAN METHOD:PUBLISH X-WR-CALNAME:Research on Research X-ORIGINAL-URL:https://researchonresearch.org X-WR-CALDESC:Events for Research on Research REFRESH-INTERVAL;VALUE=DURATION:PT1H X-Robots-Tag:noindex X-PUBLISHED-TTL:PT1H BEGIN:VTIMEZONE TZID:UTC BEGIN:STANDARD TZOFFSETFROM:+0000 TZOFFSETTO:+0000 TZNAME:UTC DTSTART:20220101T000000 END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTART;TZID=UTC:20230615T180000 DTEND;TZID=UTC:20230615T193000 DTSTAMP:20250708T070458 CREATED:20250128T110759Z LAST-MODIFIED:20250128T110759Z UID:2141-1686852000-1686857400@researchonresearch.org SUMMARY:Can AI predict research impacts? DESCRIPTION:The success or failure of medical research is judged by patient outcomes far downstream of the strategic decisions that initiate it. Optimising translational impact therefore relies on long range forecasting\, for which no established framework exists. The evaluation of research proposals by expert appraisal of their content is undermined by difficulties with scaling\, reproducibility\, generalisability\, and bias. Evaluation by summary bibliometrics of public reception offers greater objectivity but doubtful fidelity. Both approaches favour the familiar\, the conventional\, the plausible\, and the incremental; and oppose the unusual\, the unorthodox\, the counter-intuitive\, and the disruptive: rare characteristics on which translational success increasingly depends.  \n\n\n\n\n\n\n\n\n\nIn this talk\, Amy Nelson and Parashkev Nachev (UCL) advocate for a third way\, founded on richly expressive models of research content\, that seeks to combine the finesse of a human expert with the rigour of a machine. They argue such models can successfully capture regularities too intricate to be either intuitively apprehensible or reducible to summary metrics\, thereby illuminating complex characteristics of translational success in which testable hypotheses about optimal research strategy may be grounded.  \n\n\n\nThey describe a proof-of-concept analysis of the comparative predictability of future real-world translation—as indexed by inclusion in patents\, guidelines\, or policy documents—from complex models of title/abstract-level published research content versus citations and metadata alone. Quantifying predictive performance out-of-sample\, ahead of time\, across major domains\, using the entire corpus of biomedical research captured by Microsoft Academic Graph from 1990–2019\, encompassing 43.3 million papers\, they show that high-dimensional models of titles\, abstracts\, and metadata exhibit substantially higher fidelity (AUC > 0.9) than simple models\, generalise across time and domain\, and transfer to recognising the papers of Nobel laureates. Their talk will build on this recent paper in Patterns. \n\n\n\nThe Speakers\n\n\n\nAmy Nelson is a Senior Research Associate in the High Dimensional Neurology Group at UCL Queen Square Institute of Neurology\, Research Impact Fellow at the NIHR UCLH Biomedical Research Centre\, and a junior doctor. Dr Nelson builds AI models for clinical\, operational and research impact objectives across computer vision\, deep representation learning\, and natural language processing domains. \n\n\n\nParashkev Nachev is a Professor of Neurology at the UCL Institute of Neurology\, and Honorary Consultant Neurologist at the National Hospital for Neurology and Neurosurgery\, Queen Square. His High-Dimensional Neurology Group develops novel computational methods for drawing representational\, predictive\, and prescriptive intelligence from rich data. URL:https://researchonresearch.org/event/can-ai-predict-research-impacts/ CATEGORIES:Online,Seminar,Ai ATTACH;FMTTYPE=image/jpeg:https://researchonresearch.org/wp-content/uploads/2023/09/artificial-intelligence-ai-and-machine-learning-2023-05-21-04-29-23-utc-scaled-e1737735189337.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20230518T180000 DTEND;TZID=UTC:20230518T190000 DTSTAMP:20250708T070458 CREATED:20250128T110800Z LAST-MODIFIED:20250128T110800Z UID:2142-1684432800-1684436400@researchonresearch.org SUMMARY:Invert the order! Government's role in shaping a science superpower DESCRIPTION:What is required for the UK to stay at the cutting edge of science and technology and make harnessing its benefits our national purpose? And what role does the government have in that? \n\n\n\nFormer special adviser on Science & Technology to the UK Prime Minister\, James Phillips\, reflects on his experiences at the nerve centre of UK research and innovation policy.  \n\n\n\nJames argues that there are opportunities and pitfalls that arise from government bureaucracies taking greater interest in S&T. He outlines priorities for a reform agenda over the next decade\, drawing upon his experiences in Number Ten\, as a research scientist\, and as a co-author of the recent Tony Blair-William Hague report ‘A New National Purpose’.  \n\n\n\nJames also outlines a provocative recent paper he co-authored with Paul Nightingale\, which argues that the UK is falling behind the cutting edge in some crucial areas of science. Finally\, he explores how the metascience community could support and advance a new national purpose in science and technology.  \n\n\n\nRead James Phillips’ article which accompanies this talk on Substack here. \n\n\n\nThe Speaker\n\n\n\nJames Phillips is a former special adviser on science and technology to UK Prime Minister Boris Johnson; one of the ‘weirdos and misfits’ hired to work in Number Ten. He worked on setting up ARIA\, which he had called for with others in a 2018 Telegraph op-ed. He also helped to drive rapid lateral flow testing in government\, including being part of the team that published the first modelling of rapid testing in April 2020. Prior to government\, he worked at HHMI’s Janelia Research Campus and did a PhD in Neuroscience at the University of Cambridge\, where he was awarded the British Neuroscience Association’s graduate thesis of the year award. He is currently an honorary senior research fellow at UCL’s Department of Science\, Technology\, Engineering and Public Policy (UCL-STEaPP). He blogs at jameswphillips.substack.com. URL:https://researchonresearch.org/event/invert-the-order-governments-role-in-shaping-a-science-superpower-2/ CATEGORIES:Online,UCL,Science ATTACH;FMTTYPE=image/jpeg:https://researchonresearch.org/wp-content/uploads/2023/09/science-2022-10-31-23-20-34-utc-scaled.jpg END:VEVENT BEGIN:VEVENT DTSTART;TZID=UTC:20220616T153000 DTEND;TZID=UTC:20220616T163000 DTSTAMP:20250708T070458 CREATED:20250128T110801Z LAST-MODIFIED:20250128T110801Z UID:2145-1655393400-1655397000@researchonresearch.org SUMMARY:The Quantified Scholar DESCRIPTION:Around the world\, the good\, the bad and the ugly in research cultures are the focus of unprecedented scrutiny and debate. Imperatives of equality\, diversity\, inclusion\, impact\, integrity and sustainability are forcing overdue change to institutions\, policies and practices. But there is still a long way to go. \n\n\n\n\n\n\n\n\n\nJuan Pablo Pardo-Guerra\, associate professor of sociology at the University of California\, San Diego and author of the book The Quantified Scholar\, explores how processes of research evaluation themselves shape disciplines\, promote conformity and limit diversity. \n\n\n\nProf. Sarah de Rijcke\, Co-Chair of RoRI and Scientific Director at the Centre for Science and Technology Studies (CWTS)\, Leiden University and Dr Molly Morgan Jones\, Director of Policy at The British Academy\, offer their responses. \n\n\n\nThis seminar was organised by RoRI and Sheffield Metascience Network (MetaNet) at the University of Sheffield. URL:https://researchonresearch.org/event/the-quantified-scholar/ CATEGORIES:Online,Seminar,Research Evaluation ATTACH;FMTTYPE=image/jpeg:https://researchonresearch.org/wp-content/uploads/2024/03/stack-of-books-on-a-chair-e1737735006476.jpg END:VEVENT END:VCALENDAR