Yoonjoo Lee




I am a Ph.D. student in the School of Computing at KAIST. I work with Juho Kim as a member of KIXLAB.

My research interest lies in the intersection of human-computer interaction (HCI) and natural language processing (NLP). I aim to support people to learn from and make sense of dense information (e.g., content in lecture videos, scientific articles) by creating diverse scaffoldings (e.g., QAs, dialogues, explanations) using AI models. Recently, I have been interested in generating outputs that align with diverse human characteristics and evaluating how well this alignment is performed.


Conference Papers

One vs. Many: Comprehending Accurate Information from Multiple Erroneous and Inconsistent AI Generations
Yoonjoo Lee, Kihoon Son, Tae Soo Kim, Jisu Kim, John Joon Young Chung, Eytan Adar, Juho Kim
Under review

PaperWeaver: Enriching Topical Paper Alerts by Contextualizing Recommended Papers with User-collected Papers
Yoonjoo Lee, Hyeonsu B Kang, Matt Latzke, Juho Kim, Jonathan Bragg, Joseph Chee Chang, and Pao Siangliulue
Accepted in CHI2024 | arxiv

EvalLM: Interactive Evaluation of Large Language Model Prompts on User-Defined Criteria
Tae Soo Kim, Yoonjoo Lee, Jamin Shin, Young-Ho Kim, and Juho Kim
Accepted in CHI2024 | arxiv | video

VIVID: Human-AI Collaborative Authoring of Vicarious Dialogues from Lecture Videos
Seulgi Choi, Hyewon Lee, Yoonjoo Lee, and Juho Kim
Accepted in CHI2024

QASA: Answering Advanced Questions on Scientific Articles
Yoonjoo Lee*, Kyungjae Lee*, Sunghyun Park, Dasol Hwang, Jaehyeon Kim, Hong-in Lee, and Moontae Lee
ICML 2023 | data link

Cells, Generators, and Lenses: Design Framework for Object-Oriented Interaction with Large Language Models
Tae Soo Kim, Yoonjoo Lee, Minsuk Chang, and Juho Kim
UIST 2023 | project website

DAPIE: Interactive Step-by-Step Explanatory Dialogues to Answer Children’s Why and How Questions
Yoonjoo Lee, Tae Soo Kim, Sungdong Kim, Yohan Yun, and Juho Kim
CHI 2023 | acm dl | video presentation | project website

Promptiverse: Scalable Generation of Scaffolding Prompts Through Human-AI Hybrid Knowledge Graph Annotation

Yoonjoo Lee, John Joon Young Chung, Tae Soo Kim, Jean Y. Song, and Juho Kim

CHI 2022 | acm dl | video presentation | project website

Personalizing Ambience and Illusionary Presence: How People Use “Study with Me” Videos to Create Effective Studying Environments
Yoonjoo Lee, John Joon Young Chung, Jean Y. Song, Minsuk Chang, and Juho Kim
CHI 2021 | acm dl | video presentation

A Machine Learning Approach that meets Axiomatic Properties in Probabilistic Analysis of LTE Spectral Efficiency
Yoonjoo Lee, Yunbae Kim, and Seungken Park
ICTC, Oct. 2019 | ieee dl

Journal Articles

Forecasting realized volatility using data normalization and recurrent neural network
Yoonjoo Lee, Dong Wan Shin, and Ji Eun Choi
Communications for Statistical Applications and Methods, Vol. 31, No. 1, 1–23, 2024

Probabilistic Analysis of Spectral Efficiency for LTE based on PDCCH Measurement Data
Yoonjoo Lee, Yunbae Kim, Yeongyu Park, and Seungken Park
IEEE Communications Letters, vol. 23, no. 9, Sep. 2019 | ieee dl

Posters, Workshop Papers

LMCanvas: Object-Oriented Interaction to Personalize Large Language Model-Powered Writing Environments
Tae Soo Kim, Arghya Sarkar, Yoonjoo Lee, Minsuk Chang, and Juho Kim
CHI 2023 Workshop on Generative AI and HCI

Interactive Children’s Story Rewriting Through Parent-Children Interaction
Yoonjoo Lee, Tae Soo Kim, Minsuk Chang, and Juho Kim
ACL 2022 workshop on In2Writing

XDesign: Integrating Interface Design into Explainable AI Education
Hyungyu Shin, Nabila Sindi, Yoonjoo Lee, Jaeryoung Ka, Jean Y. Song, and Juho Kim
SIGCSE TS 2022 Posters

A Study on the Distribution Analysis of LTE Resource Block Usage from TSME Measurement Data
Yoonjoo Lee, Yunbae Kim, and Seungken Park
KICS, Jun. 2018 | dbpia dl

A Study on the Estimation of Probability Distribution of the Spectral Efficiency of LTE based on TSME Measurement Data
Yunbae Kim, Yoonjoo Lee, and Seungken Park
KICS, Jun. 2018 | PDF

Research Experience

Allen Institute for AI (AI2)
Research Scientist Intern (Mentor: Pao Siangliulue, Joseph Chee Chang, Jonathan Bragg, Kyle Lo)
May 2023 -

LG AI Research
Research Scientist Intern (Mentor: Moontae Lee)
Nov. 2022 - Mar. 2023

Electronics and Telecommunications Research Institute(ETRI)
Graduate Research Assistant (Mentor: Yunbae Kim and Seungken Park)
Jan. 2018 - Dec. 2019


Reviewer: EMNLP 2023, CHI 2022-2023, UIST 2022-2023, ACL 2023, CSCW 2023, C&C 2022, IEEE TLT
Program Committee: CHI LBW 2023
Student Volunteer: CHI 2022


Ph.D. in School of Computing, KAIST
Sep. 2020 - present
M.S. in Statistics, Ewha Womans University
Mar. 2018 - Feb. 2020
B.S. in Math Education, Ewha Womans University (Minor: Statistics)
Mar. 2014 - Feb. 2018, Magna Cum Laude