For prospective students and postdocs

We are always looking for graduate (or internship) students and postdoc collaborators with a strong interest in the area of machine/deep learning.

In particular, if you are KAIST undergraduate students, here are some tips

  • Decide first what kinds of fields you love to investigate, instead of how to optimize your career on some “hot” fields. For example, read “Should I do a PhD?”.

  • Take as many mathematics courses (e.g., MAS212, MAS241, MAS250, MAS311, MAS477, CS206, CS300, EE205, EE213, EE326) as possible.

  • Improve your programming skills (e.g., C, Python, not necessarily though machine/deep learning platforms) through courses (e.g., EE209, EE324, EE415) or industrial internships (e.g., apply EE Co-op program).

  • Do not consider too much why the above courses are useful for machine/deep learning. Take any courses if they look interesting to you.

  • Apply (by sending an email to me) an individual study in our lab, typically at your 3rd (or early 4th) year (since we typically have many such candidates).

  • Do not worry about your technical background/experience: your passion, attitude and intellectual curiosity matter (more than your talent) for understanding fundamentals of the area.

  • Nevertheless, if you are a beginner for machine/deep learning, I recommend to take some online courses (e.g., machine learning, deep learning).

If you are interested in joining our lab, send an email to me ( with your transcript or CV. Please understand that I cannot respond to other questions, e.g., “how to study machine learning?”.