Julia Kim 🦊
Julia Kim

MIT ORC PhD Candidate

About Me

Hi! I’m an incoming second-year PhD student at the MIT Operations Research Center. My research lies at the intersection of AI safety, evaluation, and optimisation, with a particular interest in multimodal and generative AI.

My current research interests span three broad directions:

  1. Non-generative safety evaluation: developing methods to identify harmful model capabilities without producing harmful content, with applications to child sexual abuse material (CSAM), non-consensual intimate imagery (NCII), and biological misuse.
  2. Epistemic harms from AI: studying how hallucinations, sycophancy, homogenisation, and overreliance on AI-generated information affect what people know, believe, imagine, and regard as possible.
  3. Efficient and responsible machine learning: reducing the computational and energy demands of modern AI systems without compromising their safety or reliability.

Across these directions, I hope to develop rigorous methods that improve the human condition, positively affect people’s lives, and deepen our understanding of how increasingly powerful AI systems behave and influence the world.

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Interests
  • Optimisation
  • Machine Learning
  • Decision Analytics
Education
  • PhD Operations Research

    Massachusetts Institute of Technology

  • Advanced Study in Mathematics

    University of Cambridge

  • HBSc Mathematics & Physics

    University of Toronto

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