Jonggyu Jang
Postdoctoral Researcher
Purdue University
Email | Google Scholar | Curriculum Vitae | Portrait image

Hi! Welcome to my home page. πŸ‘‹

I am a postdoctoral researcher at Purdue University hosted by Prof. David J. Love.

Before, I received the B.Sc and Ph.D. degress from the Ulsan National Institute of Science and Technology (UNIST) in 2017 and 2021, respectively. I was fortunate to be advised by Prof. Hyun Jong Yang. From 2021 to 2024, I was a postdoctoral researcher at POSTECH from 2021 to 2024. From 2024 to 2025, I was a postdoctoral researcher at AiSLab in the department of electrical and computer engineering, Seoul National University (SNU). I am interested in publishing flagship journals and conferences in Communication/AI field, such as TWC, TCOM, TMC, INFOCOM, TON, TVT, NeurIPS, ICML, and AISTATS. . For more about me, please check my CV and google scholar.

I am also open to collaborating to explore AI-and-Networking research topics, such as federated learning, over-the-air computing, radio resource management, AI-based signal processing, semantic communication, and AI-RAN.

Publications (πŸ“: equal contribution or corresponding)

Full publication list is available here

  • [14] Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding
    Jonggyu Jang, Hyeonsu Lyu, Seongjin Hwang, Hyun Jong Yang
    IEEE Transactions on Neural Networks and Learning Systems(TNNLS), 2025 | paper
    • Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding
    [14] Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding

    Jonggyu Jang, Hyeonsu Lyu, Seongjin Hwang, Hyun Jong Yang

    IEEE Transactions on Neural Networks and Learning Systems TNNLS, 2025-03-17

    [paper]

    Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding
    [14] Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding

    Jonggyu Jang, Hyeonsu Lyu, Seongjin Hwang, Hyun Jong Yang

    IEEE Transactions on Neural Networks and Learning SystemsTNNLS, 2025-03-17

    [paper]

  • [13] Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach
    Youjin Kim, Jonggyu Jang, Hyun Jong Yang
    IEEE Communications Letters(CL), 2025 | paper
    • Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach
    [13] Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach

    Youjin Kim, Jonggyu Jang, Hyun Jong Yang

    IEEE Communications Letters CL, 2025-03-08

    [paper]

    Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach
    [13] Enhancing Sum-Rate Performance in Constrained Multicell Networks: A Low-Information Exchange Approach

    Youjin Kim, Jonggyu Jang, Hyun Jong Yang

    IEEE Communications LettersCL, 2025-03-08

    [paper]

  • [12] Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network
    Hyeonsu LyuπŸ“, Jonggyu JangπŸ“, Harim Lee, Hyun Jong Yang
    IEEE Transactions on Wireless Communications(TWC), 2025 | paper
    • Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network
    [12] Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network

    Hyeonsu LyuπŸ“, Jonggyu JangπŸ“, Harim Lee, Hyun Jong Yang

    IEEE Transactions on Wireless Communications TWC, 2025-02-24

    [paper]

    Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network
    [12] Non-iterative Optimization of Trajectory and Radio Resource for Aerial Network

    Hyeonsu LyuπŸ“, Jonggyu JangπŸ“, Harim Lee, Hyun Jong Yang

    IEEE Transactions on Wireless CommunicationsTWC, 2025-02-24

    [paper]

  • [11] Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks
    Minwoo KimπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang
    IEEE Transactions on Mobile Computing(TMC), 2024 | paper
    • Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks
    [11] Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks

    Minwoo KimπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang

    IEEE Transactions on Mobile Computing TMC, 2024-09-02

    [paper]

    Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks
    [11] Age-of-Information-Aware Distributed Task Offloading and Resource Allocation in Mobile Edge Computing Networks

    Minwoo KimπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang

    IEEE Transactions on Mobile ComputingTMC, 2024-09-02

    [paper]

  • [10] Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
    Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang
    International Conference on Machine Learning(ICML), 2024 | paper | code
    • Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
    [10] Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD

    Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang

    International Conference on Machine Learning ICML, 2024-07-20

    Our study delves into an intriguing question: "Can we find a more efficient substitute for Gaussian noise to secure privacy in DP-signSGD?" We propose an answer with a Logistic mechanism, which conforms to signSGD principles and is interestingly evolved from an exponential mechanism.

    [paper] [code]

    Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD
    [10] Rethinking DP-SGD in Discrete Domain: Exploring Logistic Distribution in the Realm of signSGD

    Jonggyu Jang, Seongjin Hwang, Hyun Jong Yang

    International Conference on Machine LearningICML, 2024-07-20

    Our study delves into an intriguing question: "Can we find a more efficient substitute for Gaussian noise to secure privacy in DP-signSGD?" We propose an answer with a Logistic mechanism, which conforms to signSGD principles and is interestingly evolved from an exponential mechanism.

    [paper] [code]

  • [9] Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy
    Sehyun RyuπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang
    IEEE ACCESS, 2024 | paper
    • Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy
    [9] Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy

    Sehyun RyuπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang

    IEEE ACCESS , 2024-05-10

    In a nutshell, we propose a per-instance noise variance optimization (NVO) game, framed as a common interest sequential game, and show that the Nash equilibrium (NE) points of it inherently guarantee pDP for all data instances.

    [paper]

    Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy
    [9] Noise Variance Optimization in Differential Privacy: A Game-Theoretic Approach Through Per-Instance Differential Privacy

    Sehyun RyuπŸ“, Jonggyu JangπŸ“, Hyun Jong Yang

    IEEE ACCESS, 2024-05-10

    In a nutshell, we propose a per-instance noise variance optimization (NVO) game, framed as a common interest sequential game, and show that the Nash equilibrium (NE) points of it inherently guarantee pDP for all data instances.

    [paper]

  • [8] Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets
    Yeongjun Kim, Jonggyu JangπŸ“, Hyun Jong YangπŸ“
    IEEE Transactions on Vehicular Technology(TVT), 2024 | paper
    • Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets
    [8] Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets

    Yeongjun Kim, Jonggyu JangπŸ“, Hyun Jong YangπŸ“

    IEEE Transactions on Vehicular Technology TVT, 2024-02-20

    We propose a deep-reinforcement-learning (DRL)-based joint UA and RA scheme to maximize the minimum rate, i.e., max-min fairness (MMF), with highly limited information exchange among the BSs. The proposed DRL algorithm optimizes UA at each BS in a distributed manner to maximize an MMF objective function with only local CSI and without any iterative process.

    [paper]

    Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets
    [8] Distributed Resource Allocation and User Association for Max-Min Fairness in HetNets

    Yeongjun Kim, Jonggyu JangπŸ“, Hyun Jong YangπŸ“

    IEEE Transactions on Vehicular TechnologyTVT, 2024-02-20

    We propose a deep-reinforcement-learning (DRL)-based joint UA and RA scheme to maximize the minimum rate, i.e., max-min fairness (MMF), with highly limited information exchange among the BSs. The proposed DRL algorithm optimizes UA at each BS in a distributed manner to maximize an MMF objective function with only local CSI and without any iterative process.

    [paper]

  • [7] M2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
    Jonggyu Jang, Sangwoo Oh, Youjin Kim, Dongmin Seo, Youngchol Choi, Hyun Jong Yang
    Conference on Neural Information Processing Systems(NeurIPS), 2023 | paper | page
    • M<sup>2</sup>SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
    [7] M2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors

    Jonggyu Jang, Sangwoo Oh, Youjin Kim, Dongmin Seo, Youngchol Choi, Hyun Jong Yang

    Conference on Neural Information Processing Systems NeurIPS, 2023-12-10

    We have collected and annotated a new dataset called Multi-Modal Ship and flOating matter Detection in Aerial Images (M2SODAI), which includes synchronized image pairs of RGB and HSI data, along with bounding box labels for nearly 6,000 instances per category.

    [paper] [page]

    M<sup>2</sup>SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors
    [7] M2SODAI: Multi-Modal Maritime Object Detection Dataset With RGB and Hyperspectral Image Sensors

    Jonggyu Jang, Sangwoo Oh, Youjin Kim, Dongmin Seo, Youngchol Choi, Hyun Jong Yang

    Conference on Neural Information Processing SystemsNeurIPS, 2023-12-10

    We have collected and annotated a new dataset called Multi-Modal Ship and flOating matter Detection in Aerial Images (M2SODAI), which includes synchronized image pairs of RGB and HSI data, along with bounding box labels for nearly 6,000 instances per category.

    [paper] [page]

  • [6] Ξ±-Fairness Maximizing User Association in Energy-Constrained Small Cell Networks
    Jonggyu Jang, Hyun Jong Yang
    IEEE Transactions on Wireless Communications(TWC), 2022 | paper
    • Ξ±-Fairness Maximizing User Association in Energy-Constrained Small Cell Networks
    [6] Ξ±-Fairness Maximizing User Association in Energy-Constrained Small Cell Networks

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Wireless Communications TWC, 2022-09-20

    We aim to accelerate the computation of the UA and RA with DRL. The proposed scheme outperforms the optimization-based schemes in the throughput, proportional fairness, and max-min fairness metrics.

    [paper]

    Ξ±-Fairness Maximizing User Association in Energy-Constrained Small Cell Networks
    [6] Ξ±-Fairness Maximizing User Association in Energy-Constrained Small Cell Networks

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Wireless CommunicationsTWC, 2022-09-20

    We aim to accelerate the computation of the UA and RA with DRL. The proposed scheme outperforms the optimization-based schemes in the throughput, proportional fairness, and max-min fairness metrics.

    [paper]

  • [5] Deep Learning-Aided User Association and Power Control with Renewable Energy Sources
    Jonggyu Jang, Hyun Jong Yang
    IEEE Transactions on Communications(TCOM), 2022 | paper | code
    • Deep Learning-Aided User Association and Power Control with Renewable Energy Sources
    [5] Deep Learning-Aided User Association and Power Control with Renewable Energy Sources

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Communications TCOM, 2022-08-20

    This paper tackles the UA and PC optimization for the sum-rate maximization under quality-of-service (QoS) and backhaul constraints. We propose a deep learning-based UA and PC algorithm that can be applied to dynamic HetNets.

    [paper] [code]

    Deep Learning-Aided User Association and Power Control with Renewable Energy Sources
    [5] Deep Learning-Aided User Association and Power Control with Renewable Energy Sources

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on CommunicationsTCOM, 2022-08-20

    This paper tackles the UA and PC optimization for the sum-rate maximization under quality-of-service (QoS) and backhaul constraints. We propose a deep learning-based UA and PC algorithm that can be applied to dynamic HetNets.

    [paper] [code]

  • [4] Recurrent Neural Network-Based User Association and Power Control in Dynamic HetNets
    Jonggyu Jang, Hyun Jong Yang
    IEEE Transactions on Vehicular Technology(TVT), 2022 | paper
    • Recurrent Neural Network-Based User Association and Power Control in Dynamic HetNets
    [4] Recurrent Neural Network-Based User Association and Power Control in Dynamic HetNets

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Vehicular Technology TVT, 2022-04-20

    In pursuit of scalable neural network design, we propose an unsupervised learning-based UA and PC algorithm using a recurrent neural network (RNN).

    [paper]

    Recurrent Neural Network-Based User Association and Power Control in Dynamic HetNets
    [4] Recurrent Neural Network-Based User Association and Power Control in Dynamic HetNets

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Vehicular TechnologyTVT, 2022-04-20

    In pursuit of scalable neural network design, we propose an unsupervised learning-based UA and PC algorithm using a recurrent neural network (RNN).

    [paper]

  • [3] Deep Reinforcement Learning-based Resource Allocation and Power Control in Small Cells with Limited Information Exchange
    Jonggyu Jang, Hyun Jong Yang
    IEEE Transactions on Vehicular Technology(TVT), 2020 | paper
    • Deep Reinforcement Learning-based Resource Allocation and Power Control in Small Cells with Limited Information Exchange
    [3] Deep Reinforcement Learning-based Resource Allocation and Power Control in Small Cells with Limited Information Exchange

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Vehicular Technology TVT, 2020-08-30

    The proposed algorithm is self-adaptive in time-varying channels, since it is not divided into training and test phases. We modify the target neural network (TNN) scheme to enhance the sum-rate and the convergence speed.

    [paper]

    Deep Reinforcement Learning-based Resource Allocation and Power Control in Small Cells with Limited Information Exchange
    [3] Deep Reinforcement Learning-based Resource Allocation and Power Control in Small Cells with Limited Information Exchange

    Jonggyu Jang, Hyun Jong Yang

    IEEE Transactions on Vehicular TechnologyTVT, 2020-08-30

    The proposed algorithm is self-adaptive in time-varying channels, since it is not divided into training and test phases. We modify the target neural network (TNN) scheme to enhance the sum-rate and the convergence speed.

    [paper]

  • [2] Deep Learning-Based Autonomous Scanning Electron Microscope
    Jonggyu Jang, Moohyun Oh, Hyeonsu Lyu, Hyun Jong Yang, Junhee Lee
    IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS), 2020 | paper | video
    • Deep Learning-Based Autonomous Scanning Electron Microscope
    [2] Deep Learning-Based Autonomous Scanning Electron Microscope

    Jonggyu Jang, Moohyun Oh, Hyeonsu Lyu, Hyun Jong Yang, Junhee Lee

    IEEE/RSJ International Conference on Intelligent Robots and Systems IROS, 2020-08-10

    In this paper, we propose and implement a deep learning-based autonomous SEM machine, which assesses image quality and controls parameters autonomously to get high quality sample images just as if human experts do.

    [paper] [video]

    Deep Learning-Based Autonomous Scanning Electron Microscope
    [2] Deep Learning-Based Autonomous Scanning Electron Microscope

    Jonggyu Jang, Moohyun Oh, Hyeonsu Lyu, Hyun Jong Yang, Junhee Lee

    IEEE/RSJ International Conference on Intelligent Robots and SystemsIROS, 2020-08-10

    In this paper, we propose and implement a deep learning-based autonomous SEM machine, which assesses image quality and controls parameters autonomously to get high quality sample images just as if human experts do.

    [paper] [video]

  • [1] Resource Allocation and Power Control in Cooperative Small Cell Networks with Backhaul Constraint
    Jonggyu Jang, Hyun Jong Yang, Hyekyung Jwa
    IEEE Transactions on Vehicular Technology(TVT), 2019 | paper
    • Resource Allocation and Power Control in Cooperative Small Cell Networks with Backhaul Constraint
    [1] Resource Allocation and Power Control in Cooperative Small Cell Networks with Backhaul Constraint

    Jonggyu Jang, Hyun Jong Yang, Hyekyung Jwa

    IEEE Transactions on Vehicular Technology TVT, 2019-11-10

    Motivated by the fact that the condition for obtaining the near-global solution with the dual problem approach is rarely satisfied for increasing number of users, we derive explicit first order optimality conditions to obtain a 2-distance ring solution of the primal UA and RA problem, and propose a sequential optimization method. In addition, we propose a PC algorithm based on the first order KKT optimality conditions, in which transmission power of each RB is iteratively updated.

    [paper]

    Resource Allocation and Power Control in Cooperative Small Cell Networks with Backhaul Constraint
    [1] Resource Allocation and Power Control in Cooperative Small Cell Networks with Backhaul Constraint

    Jonggyu Jang, Hyun Jong Yang, Hyekyung Jwa

    IEEE Transactions on Vehicular TechnologyTVT, 2019-11-10

    Motivated by the fact that the condition for obtaining the near-global solution with the dual problem approach is rarely satisfied for increasing number of users, we derive explicit first order optimality conditions to obtain a 2-distance ring solution of the primal UA and RA problem, and propose a sequential optimization method. In addition, we propose a PC algorithm based on the first order KKT optimality conditions, in which transmission power of each RB is iteratively updated.

    [paper]