I am an assistant professor at AIGS, UNIST. I strive to derive human-like machine intelligence from interactive and autonomous learning experiences. I focus on exploiting/uncovering the merits of Bayesian learning that provides principled way of allowing machine intelligence to adapt and generalize to unseen data/environments in conjunction with the deep learning models and frameworks.

If you are interested in working with me, send me an email or visit the lab page.

2021 - 2023 Postdoctoral Researcher at RIKEN, AIP: Team [approximate Bayesian inference (ABI)]((https://team-approx-bayes.github.io/)

2020 - 2021 Researcher at Microsoft Research Cambridge

2019 Research Intern at Microsoft Research Cambridge

2017 Research Intern at Max Planck Institute for Software Systems

Recent Publications

Jooyeon Kim, Angus Lamb, Simon Woodhead, Simon Peyton Jones, Cheng Zhang and Miltiadis Allamanis. "CoRGi: Content-Rich Graph Neural Networks with Attention", International Conference on Knowledge Discovery and Data Mining (KDD), 2022


  • Ph.D., School of Computing, KAIST, 2020
  • M.S., School of Computing, KAIST, 2016
  • B.E., Department of Systems Innovation, The University of Tokyo, 2014