Junu Kim

I’m Junu Kim, a Ph.D. student at the KAIST Graduate School of AI. My primary interest is in machine learning for healthcare (ML4H). I'm currently under the advisement of Professor Edward Choi.


General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History

Junu Kim, Chaeeun Shim, Bosco Seong Kyu Yang, Chami Im, Sung Yoon Lim, Han-Gil Jeong, Edward Choi

[Arxiv] [Github]

We propose the Retrieval-Enhanced Medical prediction model (REMed), the first to introduce a retrieval-based approach to medical prediction tasks, thereby reducing the need for domain experts in the development process.

Asclepius: Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes

Sunjun Kweon*, Junu Kim*, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, Jungwoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, Seungjin Baek, Chang Hoon Han, Yoon Bin Jung, Yohan Jo, Edward Choi

[Arxiv] [Github] [Huggingface]

We introduce the first publicly sharable clinical large language model, Asclepius.

Universal EHR Federated Learning Framework

Junu Kim, Kyunghoon Hur, Seongjun Yang, Edward Choi

[Arxiv] [Github]

Our study is the first approach to unify heterogeneous EHRs into a single FL framework.

UniHPF : Universal Healthcare Predictive Framework with Zero Domain Knowledge

Kyunghoon Hur, Jungwoo Oh, Junu Kim, Min Jae Lee, Eunbyeol Cho, Jiyoun Kim, Seong-Eun Moon, Young-Hak Kim, Edward Choi


We propose Universal Healthcare Predictive Framework (UniHPF), which requires no medical domain knowledge and minimal pre-processing for multiple prediction tasks.

Projects & Abstracts

Toward general‑purpose ICU predictive model: without task‑specific feature selection and infinite observation windows

Junu Kim, Chaeeun Shim, Edward Choi, Han-Gil Jeong

[ESICM LIVES 2023 Abstract]

We propose a novel machine learning approach that can handle, theoretically, an infinite amount of events.

CAMEL: Clinically Adapted Model Enhanced from LLaMA

Sunjun Kweon*, Junu Kim*, Seongsu Bae**, Eunbyeol Cho**, Sujeong Im**, Jiyoun Kim**, Gyubok Lee**, JongHak Moon**, JeongWoo Oh**, Edward Choi

[Blog] [Github] [Demo]

Clinically Adapted LLaMA, pre-trained and fine-tuned on clinical notes.


KoSAIM 2023 Summer School Hands-on Session: Transformer



KAIST Graduate School for AI

MS-Ph.D. Integrated Course, 2022-Current

KAIST Computer Science

BSc Computer Science, 2018-2022