Team
GPTfake is run by a distributed team working across AI research, data science, and ethics. Where we publish dated reports and research, we attach named author bylines so readers and journalists can assess expertise and contact the people behind a finding directly.
Last updated: June 2026
Placeholder profiles. The names, roles, and credentials below are placeholders pending confirmation of the public researcher roster. If you are listed here and want your details corrected, contact us.
Researchers
[NEEDS HUMAN] — Lead AI Researcher
Specialist in NLP, model evaluation, and LLM behavior. Leads the design of the prompt sets and scoring rubric behind GPTfake’s monitoring methodology.
- Role: Lead AI Researcher
- Focus: Evaluation design, refusal taxonomy, model behavior
- Profiles: Google Scholar
[NEEDS HUMAN]· GitHub[NEEDS HUMAN]· ORCID[NEEDS HUMAN]· LinkedIn[NEEDS HUMAN]
[NEEDS HUMAN] — Data Scientist, Longitudinal Analysis
Focused on longitudinal analysis and statistical rigor — the time-series tracking that surfaces policy drift across model versions.
- Role: Data Scientist
- Focus: Longitudinal studies, statistical methods, change detection
- Profiles: Google Scholar
[NEEDS HUMAN]· GitHub[NEEDS HUMAN]· ORCID[NEEDS HUMAN]· LinkedIn[NEEDS HUMAN]
[NEEDS HUMAN] — Ethics & Policy Lead
Focused on AI governance and accountability. Frames findings for policymakers and ensures claims are reported as measured findings, not accusations of intent.
- Role: Ethics & Policy Lead
- Focus: AI governance, policy analysis, accountability
- Profiles: Google Scholar
[NEEDS HUMAN]· GitHub[NEEDS HUMAN]· ORCID[NEEDS HUMAN]· LinkedIn[NEEDS HUMAN]
[NEEDS HUMAN] — Engineering Lead
Builds and maintains the monitoring infrastructure: the prompt-dispatch harness, response logging, and the pipeline that publishes results.
- Role: Engineering Lead
- Focus: Monitoring infrastructure, data pipeline, reproducibility tooling
- Profiles: GitHub
[NEEDS HUMAN]· LinkedIn[NEEDS HUMAN]
How we attribute work
Every data-bearing page on GPTfake carries a named author byline with the publish date, and — where a finding was independently checked — a “reviewed by” line. This is a deliberate trust practice: a “careful person” (a journalist deciding whether to cite, a researcher building on our data) should be able to see exactly who is accountable for a claim and how to reach them.
If you need attributed commentary for a story, or want to verify a researcher’s credentials, contact us.
Corrections
Found an error in a finding, or a credential that needs updating? See our corrections policy and tell us — we respond to good-faith reports.
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