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Articole: 10
  1. Evaluating Insight, Not Just Computation

    What I Actually Want to Measure When I give an exam, my primary concern is not whether a student can carry out a long computation without mistakes.

  2. Interpolation, Extrapolation, and What Exams Really Measure

    This is Part 3 of a series on AI, education, and expertise.

  3. Formal Verification and the Path to Machine Discovery

    This is Part 2 of a series on AI, education, and expertise.

  4. This is Part 1 of a series on AI, education, and expertise.

  5. Teaching a Graph of Knowledge as a Story

    I have the chance to teach several courses: computer graphics, CUDA programming, and machine learning.

  6. Why I Prefer Bayesian Data Analysis Over NHST I’m by no means a statistician, and what follows reflects only my view.

  7. Strong Types in Scientific Software - Safety and Pitfalls

    Why I Use Rich Types in My Code — Even for Temperature I’ve seen many interesting posts online about programming with types, especially around the idea of avoiding naked primitives like int, float, or size_t for domain-specific values.

  8. Better Scientific Writing Prompts

    Large Language Models (LLMs) have significantly changed how we write.

  9. A Tribute to Ramanujan’s Genius

    Srinivasa Ramanujan (1887–1920) is one of the greatest mathematicians in history.

  10. Rust Workspaces

    While working on a Rust project involving multiple libraries and applications, I explored Rust workspaces to manage interconnected components.