Hello, I’m jaechang Kim. I’m a graduate student in POSTECH ML Lab since 2021.

Research Interest

I treat machine learning as a method to solve under-determined problems by learning priors from data. I’m interested in applications of machine learning and reasoning how a neural network is working.

• Source Separation
• Machine Learning Applications in sound domain
• Trustworthy AI
• Reasoning in ML

Publication

pre-print

• Jaechang Kim, Jeongyeon Hwang, Soheun Yi, Jaewoong Cho, and Jungseul Ok, “Addressing Feature Imbalance in Sound Source Separation,” 2023

major conferences

• Jaechang Kim*, Yunjoo Lee*, Hyun Mi Cho, Dong Woo Kim, Chi Hoon Song, and Jungseul Ok, “Activity-informed Industrial Audio Anomaly Detection via Source Separation,” in ICASSP, 2023
• Jaechang Kim*, Yunjoo Lee*, Seunghoon Hong, and Jungseul Ok, “Learning Continuous Representation of Audio for Arbitrary Scale Super Resolution,” in ICASSP, 2022
• Jinwoo Jeon*, Jaechang Kim*, Kangwook Lee, Sewoong Oh, and Jungseul Ok, “Gradient Inversion with Generative Image Prior,” in NeurIPS 2021 (and FL-ICML’21), 2021

domestic conferences

• Hyejin Park*, Byungchan Ko*, Jaechang Kim*, Hoyoung Kim, Jinwoo Jeon, and Jungseul Ok, “Effect of Privacy Preserving in Personalized Federated Learning with Heterogeneous Data from Wearable Devices,” KSC2021, 2021

Education

• Ph.D. in POSTECH Graduate School of Artificial Intelligence (2021 ~ )
• B.S. in POSTECH Department of Computer Science & Engineering (2016 ~ 2021)

Work Experience

• Internship in Naver Corp (2020.07 ~ 2020.08)

• Internship with Prof. Sungwoo Park (2019.05 ~ 2019.10) https://www.datamonad.com/

• Internship in Netmarble AI Revolution Center (2018.06 ~ 2018.08)