Publications

Fed-Joint: Joint Modeling of Non-parametric Degradation Signals and Failure Events for Remaining Useful Life Prediction using Federated Learning

Cheong, J. and Yue, X., and Chung, S.*

Reliability Engineering and System Safety, 267 (A), 111833.

Fairness in Machine Learning-based Hand Load Estimation: A Case Study on Load Carriage Tasks

Rahman, A.†, Sol, L., and Chung, S.*

Applied Ergonomics, 130, 104642.

Federated Automatic Latent Variable Selection in Multi-output Gaussian Processes

Gao, J†. and Chung, S*

Pattern Recognition, 172 (Part A), 112410.

An Optimization Model and Algorithm for Job Scheduling with Extra Resource Allocation in Shipbuilding

Chung, S., Park, C., Cha, H.*, and Cheong, T.*

International Journal of Production Research.

Real-time Adaptation for Time-series Signal Prediction Using Label-aware Neural Processes

Chung, S.* and Kontar, R.

Reliability Engineering & System Safety, 257, 110833.

QCRE Best Track Paper Finalist, 2024 IISE Annual Conference

Network of Artificial Olfactory Receptors for Spatiotemporal Monitoring of Toxic Gas

Baek, Y., Bae, B., Yang, J., Cho, W., Sim, I., Yoo, G., Chung, S., Heo, J.*, and Lee, K.*

Science Advances, 10(42), eadr2659.

Federated Multi-output Gaussian Processes

Chung, S. and Kontar, R.*

Technometrics, 66(1), 90–103.

Quality, Statistics, and Reliability Best Paper Finalist, 2022 INFORMS Annual Meeting

Federated Condition Monitoring Signal Prediction with Improved Generalization

Chung, S. and Kontar, R.*

IEEE Transactions on Reliability, 73(1), 438–450.

Weakly-supervised Multi-output Regression via Correlated Gaussian Processes

Chung, S., Kontar, R.*, and Wu, Z.

INFORMS Journal on Data Science, 1(2), 115–137.

QCRE Best Student Paper Finalist, 2021 IISE Annual Conference

A Multi-stage Approach for Knowledge-guided Predictions with Application to Additive Manufacturing

Chung, S., Chou, C.-H., Fang, X., Kontar, R.*, and Okwudire, C.

IEEE Transactions on Automation Science and Engineering, 19(3), 1675–1687.

The Internet of Federated Things (IoFT)

Kontar, R.*, Shi, N., Yue, X., Chung, S., Byon, E., Chowdhury, M., Jin, J., Kontar, W., Masoud, N., Noueihed, M., Okwudire, C. E., Raskutti, G., Saigal, R., Singh, K., and Ye, Z.

IEEE Access, 9, 156071.

Featured Article of the Year, IEEE Access

Look-ahead Decision Making for Renewable Energy: A Dynamic "Predict and Store" Approach

Wang, J., Chung, S., AlShelahi, A., Kontar, R., Byon, E., and Saigal, R.

Applied Energy, 296, 117068.

Functional Principal Component Analysis for Extrapolating Multi-stream Longitudinal Data

Chung, S. and Kontar, R.*

IEEE Transactions on Reliability, 70(4), 1321.

A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation

Chung, S., Park, Y.-W.*, and Cheong, T.

Pattern Recognition, 108, 107565.

Intelligent Traffic Control for Autonomous Vehicle Systems Based on Machine Learning

Lee, S., Kim, Y., Kahng, H., Lee, S.-K., Chung, S., Cheong, T., Shin, K., Park, J., and Kim, S. B.∗

Expert Systems with Applications, 144, 113074.

Accounting for Fairness in a Two-stage Stochastic Programming Model for Kidney Exchange Programs

Lee, H., Chung, S., Cheong, T.*, and Song, S. H.

International Journal of Environmental Research and Public Health, 15(7), 1491.

Sharing of Benefits from a Logistics Alliance Based on a Hub-Spoke Network: A Cooperative Game Theoretic Approach

Yea, M., Chung, S., Cheong, T.*, and Kim, D.

Sustainability, 10(6), 1855.

Reformulation-linearization Technique Approach for Kidney Exchange Program IT Healthcare Platforms

Yuh, J., Chung, S., and Cheong, T.*

Applied Sciences, 7(8), 847.

Rethinking Personalized Reward Modeling for LLMs under Preference Heterogeneity via Group-Debiased Federated Learning

Kim, S., Cho, B., Oh, J., Chung, S.*, and Yun, S. Y.*

Embodied Edge Computing for Real-time Perception in Physical AI

Bae, B., Seokho Kim, S., Choi, S. B., Sim, I., Bezzo, N.*, Hong, S.*, Heo, J.*, Lee, I.*, Chung, S.*, Fioretto, F.*, Iqbal, T.*, Kung, J.*, and Lee, K.*

Personalizable Gait Sensing through Meta-learned On-chip Enrollment

Baek, Y., Bae, B., Seo, D., Cho, J., Sim, I., Gong, Y., Kim D., Kim, S., Kim, S., Kim, D., Chung, S., Song, S. H., Song, Y. M., Lee, Y. S., and Lee, K.*

Gait-based Hand Load Estimation via Deep Latent Variable Models with Auxiliary Information

Gao, J†., Sol, L., and Chung, S.*

TimeSets: A Real-Time Adaptive Prediction Framework for Multivariate Time Series

Gao, J†., Rahman, A.†, Sol, L., and Chung, S.*

Morphology-Aware Ambiguity Learning for Wafer Defect Decision Support

Chu, S†. and Chung, S.*