Dr Denis Newman-Griffis (they/them)

BA (Carleton), MSc (Ohio State), PhD (Ohio State)

Information School

Lecturer in Data Science

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+44 114 222 2647

Full contact details

Dr Denis Newman-Griffis
Information School
Room C224
The Wave
2 Whitham Road
S10 2AH

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.

My research explores equitable AI and data science for human well-being, including intersections of data and disability, health NLP, and policy and practice of responsible AI. I have published extensively across these topics in computer science, health informatics, and social science venues, and am leading funded projects in responsible AI practice and disability informatics.  I organise the workshop series on AI for Function, Disability, and Health, and received the American Medical Informatics Association (AMIA) Doctoral Dissertation Award for my work on NLP and disability.

I am a member of the UK Young Academy and currently serve as its Co-Chair. I am proud to be a queer researcher in data science, and I serve as a Non-Binary Role Model at the University of Sheffield. I have previously been involved in organising events through Queer in AI, and I am passionate about supporting LGBT+/queer students and staff in the academic community.

University responsibilities

  • Deputy Programme Coordinator, BSc Data Science (2023-)
  • Interim Programme Coordinator, BSc Data Science (Semester 2, 2023-2024)
  • Deputy Programme Coordinator, MSc Data Science (2022-2023)
  • Member of the University Task & Finish Group on Generative AI (2022-2023)
  • Member of the University Academic and Student Product Board (2023-)
Research interests

My research investigates better ways to connect people with data-driven insights using artificial intelligence. I approach this in a highly interdisciplinary way, drawing on AI and data science, critical disability studies, health informatics, critical data studies and linguistics.

My recent research generally follows three themes:

Responsible AI practices: I am leading the Research on Research Institute’s GRAIL project on responsible use of AI and machine learning in research funding and evaluation, supported by an international collaboration of research funding agencies.

Data, AI, and disability: I work on developing new NLP approaches to analyse information about function and disability experience for health and well-being, as well as critically analysing AI technology design and implementation from disability-centred perspectives. I am supervising a PhD student (Jun Wang) investigating information needs for disability-centred care.

Practical health NLP: I work on improving generalisability of methods for extracting health information from text, and developing new approaches for evaluating real-world impact of health NLP.

I am interested in supervising PhD projects across these areas, as well as in research on effective data science education. I primarily use quantitative methods, particularly statistical analysis and machine learning, but my work includes survey-based and qualitative methods as well.


Journal articles

Conference proceedings papers

Working papers

  • Newman-Griffis D, Holm J, Waltman L & Wilsdon J () Good practice in the use of machine learning & AI by research funding organisations: insights from a workshop series. RIS download Bibtex download


Research group

I am currently supervising the following PhD students:

  • Ian Widdows: Secondary school accountability measures in England - their effectiveness, effects and an exploration of alternative approaches. (With Jo Bates)
  • Jun Wang: Understanding information needs in person-centred care for age-related disease, multimorbidity, and disability. (Fully-funded Healthy Lifespan Institute PhD studentship; with Peter Bath and Steven Ariss)
  • Yi Jiang (visiting PhD student September 2023-March 2024): Semantically-enriched keyphrase generation for scientific papers. (With Mike Thelwall)

I have supervised 10 MSc students to date and strongly support MSc students in pursuing publishable dissertation research.


FRAIM: Framing Responsible AI Implementation & Management


Project Lead


1 February 2024

6 months

The FRAIM project brings together cross-sector perspectives on organisational RAI policy and process to scope key stakeholders, shared values, and actionable research needs for building the evidence base on implementing and managing RAI.

GRAIL: Getting Responsible about AI and Machine Learning in Research Funding and Evaluation

Research on Research Institute

Project Lead


1 April 2023

24 months

The GRAIL project is exploring good principles and practices for using AI and machine learning in the research funding ecosystem in ways that are both ethical and effective.

Faculty of Social Science Education Fund: Student Voice in MSc in Data Science

TUoS Faculty of Social Science

Principal Investigator


21 April 2023

3 months

Programme-level review of student feedback for MSc in Data Science course, covering academic years 2017-2018 to 2021-2022. 

Teaching interests

I currently co-coordinate the BSc in Data Science (with Dr. Morgan Harvey). I helped lead development of Level 1 modules, including a novel integrated programme week to introduce students to the Data Science curriculum, and am helping lead development of Level 2 modules. I designed the Level 1 module INF111 Practical Programming for Data Science 1 (first taught 2023-2024), including development of module assessments and a joint assessment with INF112.

I was formerly Deputy Programme Coordinator for the MSc in Data Science and actively teach on the course, primarily focusing on data mining and AI skills as well as use of big data platforms. I led a funded project reviewing five years of student feedback on the course and am contributing to ongoing curriculum enhancement efforts.

I am highly interested in developing and researching effective data science pedagogy, and I am committed to bringing evidence-based best practices into my teaching. I use active learning methodologies frequently in the classroom and regularly engage with student feedback to adapt and improve my teaching. I am particularly interested in working with students to develop effective, practice-focused interventions to improve synthesis of data science skills.

Teaching activities

Module Coordinator:

  • INF111 Practical Programming for Data Science 1
  • INF216 Responsible Data Science Lab 1

I further contribute teaching to:

  • INF6027 Introduction to Data Science
  • INF6032 Big Data Analytics
Professional activities and memberships

I am an active member of:

  • American Medical Informatics Association (since 2016)
  • Association for Computational Linguistics (since 2017)
  • British Computer Society (since 2022)

I am Co-Chair and Executive Group member of the UK Young Academy, and a member of the Young Academy’s 2023 cohort.

I am also a Special Volunteer with the Epidemiology & Biostatistics Section of the U.S. National Institutes of Health Clinical Center, on a project with the U.S. Social Security Administration to develop informatics methods for supporting disability benefits determination.

I am active on the DEI Committee of the American Medical Informatics Association and regularly serve as a Scientific Program Committee member for AMIA conferences.

I regularly serve as a programme committee member and reviewer for a variety of conferences and journals in natural language processing and health informatics, including Association for Computational Linguistics (ACL) conferences (ACL, NAACL, EMNLP, EACL), American Medical Informatics Association (AMIA) conferences (Annual Symposium, Informatics Summit), Association for the Advancement of Artificial Intelligence (AAAI), Journal of the American Medical Informatics Association (JAMIA), Journal of Biomedical Informatics, Frontiers in Digital Health, and BMC Medical Informatics and Decision Making.

I am strongly committed to developing and mentoring student researchers, and I regularly serve as a reviewer for ACL series Student Research Workshops. I also served on the AMIA Student Paper Competition Committee (2021-2023).

I founded and organise the Workshop Series on Artificial Intelligence for Function, Disability, and Health (AI4Function) since 2020. I also guest edited a Research Topic on AI4Function in Frontiers in Digital Health.