Comprehensive Updates in Network Synthesis Models to Create An Improved Benchmark for Network Alignment Algorithms. - Hyun-Myung Woo; Hyundoo Jeong; Byung-Jun Yoon (BCB, 2018)

Machine Learning Enabled Adaptive Wireless Power Transmission System for Neuroscience Study. - Hyun-Myung Woo; Woo Seok Kim; Sungcheol Hong; Vivekanand Jeevakumar; Clay M. Smithhart; Theodore J. Price; Byung-Jun Yoon; Sung Il Park (ACSSC, 2020)

Network-Based RNA Structural Alignment Through Optimal Local Neighborhood Matching. - Hyun-Myung Woo; Byung-Jun Yoon (ACSSC, 2020)

AI-Enabled High-Throughput Wireless Telemetry for Effective Photodynamic Therapy. - Woo Seok Kim; Hyun-Myung Woo; M. Ibrahim Khot; Sungcheol Hong; David G. Jayne; Byung-Jun Yoon; Sung Il Park (ACSCC, 2021)

MONACO: accurate biological network alignment through optimal neighborhood matching between focal nodes. - Hyun-Myung Woo; Byung-Jun Yoon (Bioinform., 2021)

Accelerating Optimal Experimental Design for Robust Synchronization of Uncertain Kuramoto Oscillator Model Using Machine Learning. - Hyun-Myung Woo; Youngjoon Hong; Bongsuk Kwon; Byung-Jun Yoon (IEEE Trans. Signal Process., 2021)

Neural message-passing for objective-based uncertainty quantification and optimal experimental design. - Qihua Chen; Xuejin Chen; Hyun-Myung Woo; Byung-Jun Yoon (Eng. Appl. Artif. Intell., 2023)

Optimal decision-making in high-throughput virtual screening pipelines. - Hyun-Myung Woo; Xiaoning Qian; Li Tan; Shantenu Jha; Francis J. Alexander; Edward R. Dougherty; Byung-Jun Yoon (Patterns, 2023)