Sanmi Koyejo
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Recent

Tutorials & Talks

Recent Keynotes & Major Presentations (2023-2025)

  • Keynote: European Conference on Computer Vision (ECCV 2024)

    • “Is Distribution Shift still an AI Problem?” (September 2024)

  • Keynote: ACM Conference on Fairness, Accountability, and Transparency (FAccT 2024)

    • “Predictability and Surprise in Language Model Benchmarks” (June 2024)

  • Keynote: Conference on Health, Inference, and Learning (CHIL 2024)

    • “Handling distribution shifts (in healthcare) like a pro!” (June 2024)

  • Keynote: Data Science Nigeria Symposium (August 2023)

  • Keynote: International Symposium on Biomedical Imaging (ISBI 2023)

    • “Algorithmic Fairness Where are we now and where are we going?” (April 2023)

Recent Tutorials & Workshops (2023-2025)

  • Tutorial: Towards Trustworthy Large Language Models (WSDM 2024)

    • With Bo Li

  • Tutorial: Privacy and Fairness in Computer Vision (WACV 2024)

  • Workshop: MLSS 2025 Senegal

    • “Machine Learning from Human Feedback” (July 2025)

Policy & Governance Presentations (2023-2025)

  • Congressional Black Caucus Roundtable on AI Policy

    • “AI Impact on Underrepresented Communities” (February 2024)

  • US-Africa Frontiers of Science, Engineering, and Medicine Symposium (January 2024)

Academic & Industry Seminars (2023-2025)

  • Stanford HAI Seminar

    • “Beyond Benchmarks: Building a Science of AI Measurement” (March 2025)

  • Nvidia GTC

    • “From Guardrails to Agents: Navigating Safety and Security at AI's Frontier” (March 2025)

  • NYU Abu Dhabi Seminar

    • “Trustworthy AI Research” (September 2024)

Selected Media & Podcasts

  • The TWIML AI Podcast: “Are Emergent Behaviors in LLMs an Illusion?”
    [web] (February 2024)

  • HAI: “How Trustworthy Are Large Language Models Like GPT?”
    [web] (August 2023)

Earlier Presentations (2019-2022)

  • Tutorial: Algorithmic Fairness: Why It's Hard and Why It's Interesting (With Olga Russakovsky)
    [web] (CVPR 2022)

  • Tutorial: Representation Learning and Fairness (with Moustapha Cisse)
    [slides (pdf)]

    • at NeurIPS [video] (December 2019)

  • Keynote: Montreal AI Symposium

    • “Towards algorithms for measuring and mitigating ML unfairness” (September 2022)

  • AI for Healthcare Applications and Challenges
    [slides (pdf)]

    • at c3.AI Digital Transformation Institute [video] (September 2020)

  • Synthesizing fMRI using generative adversarial networks (Tutorial)

    • at Neurohackacademy [video] (August 2018)

    • at OHBM Education Course (June 2019)

  • Eliciting Machine Learning Metrics

    • at Kavli Frontiers of Science [video] (February 2019)

Media Coverage & Press

  • Citation in NYTimes: “When A.I. Fails the Language Test, Who Is Left Out of the Conversation?” (July 2024)

  • Citation in 2024 Economic Report of the President for “Are Emergent Abilities of Large Language Models a Mirage?”

  • Wired Magazine: “Large Language Models’ Emergent Abilities Are a Mirage” (March 2024)

  • Quanta Magazine: “How Quickly Do Large Language Models Learn Unexpected Skills?” (February 2024