Griffis, Denis, Dr

About

I am a data scientist by way of computer science, computational linguistics, and health informatics. I completed my undergraduate degree in Computer Science and Russian, then worked as a business software developer for two years before completing postgraduate training in Computer Science and Engineering, working with the National Institutes of Health Clinical Center on developing natural language processing (NLP) methods to support and inform the U.S. Social Security Administration's disability benefits programmes. I completed postdoctoral training in the Department of Biomedical Informatics at the University of Pittsburgh before joining the Information School as a Lecturer in Data Science in 2022. In December 2024 I started a new role as the Theme Lead in AI for Health at the Centre for M

Selected publications

• Newman-Griffis D, Woods HB, Wu Y, Thelwall M & Holm J (2025) Funding by Algorithm - A handbook for responsible uses of AI and machine learning by research funders. Research on Research Institute. View this article in WRRO
• Guy H, Cox A, Bhalla N, Miltner K & Newman-Griffis D (2026) The fragmentation of responsible AI: sector variation in organisational AI policies and statements of principle. AI and Society. View this article in WRRO
• Ibrahimi M, Masso A, Kesselring S, Lobanova K & Newman-Griffis D (2026) In the blind spot of AI-based mobility: eye-tracking visual attention to people with reduced mobility in autonomous vehicles and the ethics of inclusive design. AI & SOCIETY, 1-22.
• Egbetokun A, MacGlone U, McKeon E, Newman-Griffis D, Sedgwick C & Tavoulari A (2025) The labour of thought: reflections on interdisciplinarity in practice. Exchanges: The Interdisciplinary Research Journal, 12(2), 33-50. View this article in WRRO
• Newman-Griffis D (2025) AI thinking: a framework for rethinking artificial intelligence in practice. Royal Society Open Science, 12(1). View this article in WRRO
• Kaelin VC, Bosak DL, Saluja S, Newman-Griffis D, Boyd AD & Khetani MA (2025) Representation of child and youth participation within the Unified Medical Language System (UMLS). Disability and Rehabilitation, 47(1), 114-119. View this article in WRRO
• Newman-Griffis D, Desmet B, Zirikly A, Tamang S & Chang C-H (2023) Editorial: Artificial intelligence for human function and disability. Frontiers in Digital Health, 5. View this article in WRRO
• Newman-Griffis D, Rauchberg JS, Alharbi R, Hickman L & Hochheiser H (2023) Definition drives design: Disability models and mechanisms of bias in AI technologies. First Monday, 28(1).
• Newman-Griffis DR, Hurwitz MB, McKernan GP, Houtrow AJ & Dicianno BE (2022) A roadmap to reduce information inequities in disability with digital health and natural language processing. PLOS Digital Health, 1(11).
• Zirikly A, Desmet B, Newman-Griffis D, Marfeo EE, McDonough C, Goldman H & Chan L (2022) Information extraction framework for disability determination using a mental functioning use-case. JMIR Medical Informatics, 10(3). View this article in WRRO