Yoonjoo Lee

About

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 is supporting people to perform tasks ranging from teaching, writing, to prototyping effectively by 1) building AI powered systems with humans in the loop and 2) analyzing and adapting large scale data and models. Specifically, one of my research goals is to create computational methods and systems that support scalable teaching and learning using human-AI collaboration.

Publications

Conference Papers

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

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

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

From Jan. 2018 to Dec. 2019, as a Research Assistant at the Electronics and Telecommunications Research Institute(ETRI), I worked on performing analysis of Spectral Efficiency for LTE with probabilistic modeling and Deep Neural Network. I also worked on research to predict future Resource Block Usage with stochastic modeling and Recurrent Neural Network. During the research, I was advised by Yunbae Kim.

Services

Reviewer: CHI 2022, C&C 2022, IEEE TLT Student Volunteer: CHI 2022

Education

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}