Grey Kuling, Ph.D.

Lecturer in Biomedical Informatics · Curriculum & Research Fellow — Harvard Medical School (DBMI)

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I'm a mathematician and statistician, by training, who builds artificial-intelligence and machine-learning algorithms — the kind that turn messy, high-stakes data into structure people can actually understand and trust. My path runs from physics and applied mathematics into medical biophysics, and my work has always lived where rigorous methods meet real-world problems.

What I care about is how information gets organized, represented, and learned — from medical images and clinical text to course materials and student knowledge. Those methods have carried me across several fields: medical imaging and clinical informatics, biomedical research, and, most recently, graduate and medical education. As a Lecturer and Curriculum & Research Fellow in Biomedical Informatics at Harvard Medical School, I build and study AI systems that help clinicians, researchers, and learners make sense of complex information.

Across all of it, I care most about transparency, trust, and access — making sure models are interpretable, evaluated honestly, and genuinely useful to the people they serve. Whether the data represent patients or students, the goal is the same: turn complexity into clarity.

  • Department of Biomedical Informatics · Blavatnik Institute · HMS
  • Based in Boston, MA · Canadian citizen
  • Recent work on LLM-based short-answer assessment published in NEJM AI (2026)

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