I am a Ph.D. candidate at Data Science Lab, advised by Prof. Meeyoung Cha at Korea Advanced Institute of Science and Technology (KAIST). Previously, I received a B.S and M.S in Computer Science, from KAIST. 

Contact Information

Email : psw0416@kaist.ac.kr 

Google Scholar / Github  /  LinkedIn 

My research has been focused on 

• AI for Social Good 

• Social Computing

Towards Attack-tolerant Federated Learning via Critical Parameter Analysis
S. Park,  S. Han, F. Wu,  S. Kim, B.B. Zhu, X. Xie,  M. Cha
ICCV 2023
[arxiv]

FedDefender: Client-Side Attack-Tolerant Federated Learning
S. Park,  S. Han, F. Wu,  S. Kim, B.B. Zhu, X. Xie,  M. Cha
KDD 2023
[arxiv]

A human-machine collaborative approach measures economic development using satellite imagery
D. Ahn, J. Yang, M. Cha, H. Yang, J. Kim, S. Park, S. Han, E. Lee, S. Lee, S. Park
Nature Communications 2023
[arxiv]

Disaster assessment using computer vision and satellite imagery: Applications in water-related building damage detection
D. Kim, J. Won, E. Lee, K. Park, J. Kim, J. Kim, S. Park, H. Yang, S. Park, D. Ahn, M. Cha
AAAI AI4SG WORKSHOP 2023 

[arxiv]

FedX: Unsupervised Federated Learning with Cross Knowledge Distillation
S. Park,  S. Han, F. Wu,  S. Kim,  X. Xie,  M. Cha
ECCV 2022 (Top-10 self-supervised learning models in 2022)
[arxiv]

Downscaling Earth System Models with Deep Learning
S. Park,  K. Singh,  A. Nellikkattil,  E. Zeller,  T. Mai,  M. Cha
KDD 2022 (Accepted as Oral, Acceptance Rate=7 %)
[arxiv]

Active Learning for Human-in-the-Loop Customs Inspection
S. Kim,  T. Mai,  S. Han,  S. Park,  T. D.K,  J. So,  K. Singh, M. Cha,
TKDE 2022
[arxiv]

Learning Economic Indicators by Aggregating Multi-Level Geospatial Information
S. Park,  S. Han,  D. Ahn,  J. Kim,  S. Lee,  S. Hong,  J. Kim,  S. Park,  H. Yang,  M. Cha.
AAAI 2022 (Acceptance Rate=15 %)
[arxiv]

Knowledge Sharing via Domain Adaptation in Customs Fraud Detection
S. Park,  S. Kim,  M. Cha
AAAI 2022 (Acceptance Rate=15 %)
[arxiv]

Elsa: Energy-based learning for semi-supervised anomaly detection
S. Han, H. Song, S. Lee, S. Park, M. Cha
BMVC 2021
[arxiv]

Improving Unsupervised Image Clustering With Robust Learning
S. Park,  S. Han,  S. Kim,  D. Kim,  S. Park,  S. Hong,  M. Cha.
CVPR 2021
[arxiv]

Weakly supervised method to predict economic development: A case study for Nepal and Cambodia
D. Ahn,  J. Yang, S. Park,  S. Han,  E. Lee,  S. Lee,  H. Yang, S. Park, J. Kim, M. Cha.
KDD Data-driven Humanitarian Mapping 2021
[arxiv]

Mitigating Embedding and Class Assignment Mismatch in Unsupervised Image Classification
S. Han, S. Park, S. Park, S. Kim, M. Cha
ECCV 2020
[arxiv]

Learning to Score Economic Development from Satellite Imagery
S. Han,  D. Ahn,  S. Park,  J. Yang,  S. Lee,  J. Kim,  H. Yang,  S. Park,  M. Cha
KDD 2020
[arxiv]

Lightweight and robust representation of economic scales from satellite imagery
S. Han,  D. Ahn,  H. Cha,  J. Yang,  S, Park,  M. Cha
AAAI 2020, (Accepted as Oral)
[arxiv]

A Comprehensive Approach to Unsupervised Embedding Learning based on AND Algorithm
Y. Xu,  S. Han,  S. Park,  M. Cha,  CT. LI
BigData 2020 (Acceptance Rate=15.5 %)
[arxiv]