Spatially Cohesive Service Discovery and Dynamic Service Handover for Distributed IoT Environments. - Kyeong-Deok Baek; In-Young Ko (ICWE, 2017)

Spatio-Cohesive Service Selection Using Machine Learning in Dynamic IoT Environments. - Kyeong-Deok Baek; In-Young Ko (ICWE, 2018)

Effect-Driven Selection of Web of Things Services in Cyber-Physical Systems Using Reinforcement Learning. - Kyeong-Deok Baek; In-Young Ko (ICWE, 2019)

VR-Powered Scenario-Based Testing for Visual and Acoustic Web of Things Services. - Kyeong-Deok Baek; HyeongCheol Moon; In-Young Ko (ICWE, 2019)

Environment-Aware and Human-Centric Software Testing Framework for Cyber-Physical Systems. - In-Young Ko; Kyeong-Deok Baek; Jung-Hyun Kwon; Hernan Lira; HyeongCheol Moon (ICWE Workshops, 2019)

Effect-Driven Dynamic Selection of Physical Media for Visual IoT Services Using Reinforcement Learning. - Kyeong-Deok Baek; In-Young Ko (ICWS, 2019)

Cache-Sharing Distributed Service Registry for Highly Dynamic V2X Environments. - HyeongCheol Moon; Kyeong-Deok Baek; In-Young Ko (COMPSAC, 2020)

A Human-centric and Environment-aware Testing Framework for Providing Safe and Reliable Cyber-Physical System Services. - In-Young Ko; Kyeong-Deok Baek; Jung-Hyun Kwon; Hernan Lira; HyeongCheol Moon (J. Web Eng., 2020)

Learning-Based Quality of Experience Prediction for Selecting Web of Things Services in Public Spaces. - KyeongDeok Baek; In-Young Ko (ICWE, 2023)

DESA: Decentralized Self-adaptive Horizontal Autoscaling for Bursts of Load in Fog Computing. - Eun-Chan Park; KyeongDeok Baek; Eunho Cho; In-Young Ko (ICWE Workshops, 2023)

Fully Decentralized Horizontal Autoscaling for Burst of Load in Fog Computing. - Eun-Chan Park; KyeongDeok Baek; Eunho Cho; In-Young Ko (J. Web Eng., 2023)

Dynamic and Effect-Driven Output Service Selection for IoT Environments Using Deep Reinforcement Learning. - Kyeong-Deok Baek; In-Young Ko (IEEE Internet Things J., 2023)

Effective Model Replacement for Solving Objective Mismatches in Pre-trained Model Compositions. - Arogya Kharel; KyeongDeok Baek; In-Young Ko (APSEC, 2024)

EPFLU: Efficient Peer-to-Peer Federated Learning for Personalized User Models in Edge-Cloud Environments. - Xiangchi Song; Zhaoyan Wang; KyeongDeok Baek; In-Young Ko (ICWE Workshops, 2024)

HiDRA: A Hierarchical Decentralized Reactive Autoscaler for Spatio-temporal Bursts of Load. - Eun-Chan Park; KyeongDeok Baek; In-Young Ko (ICWS, 2024)

WYSIMWYG: Simulation-based Decision Support for Data Distribution of Hyperlocal Services in Edge Cloud Environments. - Sujeong Lim; KyeongDeok Baek; In-Young Ko (CHI Extended Abstracts, 2025)

Personalized User Models in a Real-world Edge Computing Environment: A Peer-to-peer Federated Learning Framework. - Xiangchi Song; Zhaoyan Wang; KyeongDeok Baek; In-Young Ko (J. Web Eng., 2025)

Effective selection of public IoT services by learning uncertain environmental factors using fingerprint attention. - KyeongDeok Baek; In-Young Ko (Appl. Intell., 2025)

MultiFedRL: Efficient Training of Service Agents for Heterogeneous Internet of Things Environments. - KyeongDeok Baek; In-Young Ko (IEEE Internet Things J., 2025)