PeopleofSuperintelligence

Researcher

David Antony Selby

David Antony Selby is a statistician and AI researcher at DFKI whose work covers reproducible research, academic citation networks and longitudinal symptom data. He earned a BSc (Hons.) in Mathematics and Statistics at Edinburgh in 2015 and a PhD in Statistics at Warwick in 2020. In 2021, he released the R package index0 for zero-based indexing. In 2024, his work linked citation ranking with PageRank and he coauthored research on LLM-based Bayesian prior elicitation; in 2025, he coauthored work on XAI metric manipulation and biologically informed neural networks. In 2026, he coauthored a bias-correction method for LLM evaluation and is a Senior Researcher in DFKI's Data Science and its Applications group.

Timeline

  1. 2015–2020

    Mathematics and statistics degrees

    He earns a BSc (Hons.) in Mathematics and Statistics at the University of Edinburgh in 2015 and a PhD in Statistics at the University of Warwick in 2020.

  2. 2021

    Zero-based indexing in R

    In 2021, he publishes the R package index0, which lets R users extract and replace elements with zero-based indices.

  3. 2024

    PageRank and Bradley-Terry

    In 2024, his sole-authored paper connects Bradley-Terry scores to PageRank and draws out implications for citation-based journal ranking.

  4. 2024

    LLMs for Bayesian priors

    He coauthors a 2024 NeurIPS workshop paper that explores LLMs as a way to retrieve expert-informed prior distributions for Bayesian statistical models.

  5. 2025

    The X-hacking problem

    In 2025, he coauthors “X-Hacking: The Threat of Misguided AutoML,” a study of manipulation in explainable-AI metrics. It shows how automated model search can find a desired explanation among models with similar predictive performance.

  6. 2025

    Visible neural networks for multi-omics

    He coauthors a 2025 critical review of visible neural networks for multi-omics integration. The review explains how prior knowledge from gene ontologies and pathway databases constrains their connections.

  7. 2026

    Bias-aware LLM evaluation

    In 2026, he coauthors “Accounting for Bias Enables Sustainable LLM Evaluation.” The paper proposes a framework that jointly models pairwise and ordinal data to correct for bias and recover rankings with fewer comparisons.

  8. As of October 2026

    Senior researcher at DFKI

    As of October 2026, he is a Senior Researcher in DFKI's Data Science and its Applications group, with an affiliation at RPTU. His research interests include open and reproducible methods, academic citation networks, and longitudinal self-reported symptom data.

Career

  1. NowDFKISenior Researcher
  2. NowRPTU University Kaiserslautern-LandauAffiliation

Education

  1. 2020University of WarwickPhD in Statistics
  2. 2015University of EdinburghBSc (Hons.) in Mathematics and Statistics

From the biography.

  1. Nonprofit roles are 2.3 times as common in AI safetyIncludes DFKI. We estimate where people focused on safety, alignment and evaluation work. Nonprofit roles appear for 25.1% of safety people with known affiliations, compared with 11.0% in other areas.
  2. The top 10 organizations employed 22% of people shaping AI in 2025: 51% of company researchers and 21% of university researchersIncludes DFKI. We estimate the share of people shaping AI who worked at the top 10 organizations each year from 1955 to 2025, comparing concentration across companies, universities, and institutes and labs.
  3. The United States employs an estimated 48% of people shaping AIIncludes DFKI. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  4. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes RPTU University Kaiserslautern-Landau. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.

Sources and credits

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  1. David Antony Selby — Data Science and its Applications dsa.dfki.de. Checked 21 October 2026.
  2. index0: Zero-Based Indexing in R cran.r-project.org. Checked 21 October 2026.
  3. PageRank and the Bradley-Terry model arxiv.org. Checked 21 October 2026.
  4. Had enough of experts? Elicitation and evaluation of Bayesian priors from large language models www-live.dfki.de. Checked 21 October 2026.
  5. X-Hacking: The Threat of Misguided AutoML proceedings.mlr.press. Checked 21 October 2026.
  6. Visible neural networks for multi-omics integration: a critical review frontiersin.org. Checked 21 October 2026.
  7. Accounting for Bias Enables Sustainable LLM Evaluation arxiv.org. Checked 21 October 2026.
  8. Team — Data Science and its Applications dsa.dfki.de. Checked 21 October 2026.