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Aderonke Thompson, PhD

Researcher working on how to assess, secure and govern AI systems, from enterprise vendors to frontier models, with a background in adversarial ML and industrial cybersecurity. I build practical tools and evidence-based frameworks that organisations and funders can use.

  • 🛡️ Frontier AI governance: third-party assurance, evaluations and incident reporting. Completed BlueDot Impact's Future of AI course.

  • 🧰 AI Assurance Toolkit: open-source toolkit for assessing third-party AI risk, with a draft frontier developer module

  • 🤖 AI Vendor Assurance Agent: an evidence-aware Copilot agent for vendor assessment with mandatory human approval, tested on contrasting scenarios

  • 🧠 Adversarial robustness: GAOR, a genetic algorithm-based method (Network, 2025)

  • 🏛️ Institutions and democracy: co-author of VTT's EnergyDAO white paper (2023) and a paper on direct democracy platforms (IARIA, 2023)

  • 🏭 Industrial cybersecurity: hands-on OT/ICS experimentation with simulated Modbus TCP processes

  • 🎓 PhD Computer Science (Information Security) · Former ERCIM Postdoctoral Fellow, VTT

  • Member, NIST AI RMF working group, AI Governance Collective

  • 📫 LinkedIn, ORCID

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  1. ai-assurance-toolkit ai-assurance-toolkit Public

    Open-source toolkit for assessing and governing third-party AI, from enterprise vendors to frontier model providers. ISO 42001, EU AI Act, NIST AI RMF, NIS2, DORA.

    1

  2. gaor-adversarial-ml-robustness gaor-adversarial-ml-robustness Public

    GAOR-related research notebooks exploring genetic-algorithm feature selection and adversarial robustness in network intrusion detection.

    Jupyter Notebook