Dr. Joo Yong Shim
Dr. Joo Yong Shim has been a postdoctoral scholar at the Department of Electrical and Computer Engineering, Korea University, Seoul, Republic of Korea, since March 2024, where she received her Ph.D. in electrical and computer engineering (Advisor: Prof. Jong-Kook Kim), in February 2024. She also received her B.S. in electrical engineering from Korea University, Seoul, Republic of Korea, in Feburary 2019. Her research interests are in deep learning theory and network/mobility applications, quantum neural network (QNN) theory and applications, QNN software engineering and programming languages, and AI-based autonomous control for distributed computing systems.
(Research Topics)
Quantum Machine Learning (QML): QML Programming Methods, Quantum Reinforcement Learning, Quantum Fedeated Learning
AI-based Autonomous Control for Distributed Computing Systems
(Journals)
Reliable Transpilation Control for Cloud-based Quantum AI Systems
IEEE Journal on Emerging and Selected Topics in Circuits and Systems (Review since 07-Jun-2024) J. Y. Shim, X. Piao, S. Park, J. Kim, J.-K. KimStabilized Performance Maximization for GAN-based Real-Time Authentication Image Generation over Internet
Multimedia Tools and Applications (Springer), 83(22):62045-62059, July 2024. J. Y. Shim, S. Jung, J. Kim, J.-K. KimAudio-to-Visual Cross-Modal Generation of Birds
IEEE Access, 11:27719-27729, March 2023. J. Y. Shim, J. Kim, J.-K. Kim
(Conferences)
Quantum Error Mitigation in Open Systems using Diffusion Models: Stochastic Differential Equation and Shrodinger Bridge Approaches
IJCAI Workshop on Quantum Algorithms, Optimization, and AI (Jeju, Korea, August 2024) J. Y. Shim, J. KimMulti-Channel Quantum Convolutional Neural Network
IJCAI Workshop on Quantum Algorithms, Optimization, and AI (Jeju, Korea, August 2024) E. J. Roh, J. Y. Shim, S. Park, J. KimQuantum Style Transfer in Hybrid Quantum-Classical Computing
IJCAI Workshop on Quantum Algorithms, Optimization, and AI (Jeju, Korea, August 2024) E. J. Roh, J. Y. Shim, S. Park, J. KimOn the Tradeoff Between Computation-Time and Learning-Accuracy in GAN-Based Super-Resolution Deep Learning
IEEE ICOIN (Jeju, Korea, January 2021) J. Y. Shim, J. Kim, J.-K. KimS2I-Bird: Sound-to-Image Generation of Bird Species using Generative Adversarial Networks
IEEE ICPR (Virtual, January 2021) J. Y. Shim, J. Kim, J.-K. KimÂ