Kongyang Chen's homepage
Short Bio
Kongyang Chen is an Associate Professor at School of Artificial Intelligence, Guangzhou University, China. He is the Vice Director of Guangdong Provincial Engineering and Technology Research Center for Big Data Security and Privacy Preservation. He was a Postdoctoral Fellow at the Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China. From 2014 to 2018, he was an Assistant Professor at Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China. He received the PhD degree in computer science from the University of Chinese Academy of Sciences, China. His main research interests are artificial intelligence, edge computing, Internet of Things, etc. He has published over 70 papers in top conferences or journals such as IEEE INFOCOM, ACM MobiSys, IEEE TMC, IEEE TDSC, IEEE TPDS, ACM TOSN, ACM TOMM, etc.
Email: kychen@gzhu.edu.cn; kongyang.chen@gmail.com
Research Interests
Our group has a broad interest in distributed intelligence, including but not limited to Internet of Things (IoT), mobile computing, edge computing, edge AI, AI security, and privacy computing. We warmly welcome outstanding undergraduate and graduate students to join our team. Additionally, we actively seek collaboration with both academia and industry; please feel free to contact us for further discussion.
Selected Publications:
l Edge computing & edge AI (e.g., task offloading, task scheduling, federated learning, edge LLMs, etc.)
[1] Satellite-Terrestrial Edge Networks for Intelligent Services: A Case Study of AIGC-Assisted Digital Watermarking, IEEE Transactions on Consumer Electronics, to appear
[2] Adaptive Gradient Sparsification with Layer and Stage-wise for Accelerating Distributed DNN Training. Computer Networks, 2026
[3] Security-Sensitive Task Offloading in Integrated Satellite-Terrestrial Networks, IEEE Transactions on Mobile Computing, 2025
[4] EdgeStreaming: Secure Computation Intelligence in Distributed Edge Networks for Streaming Analytics, ACM Transactions on Multimedia Computing, Communications, and Applications, 2025
[5] Resilient Task Offloading in Integrated Satellite-Terrestrial Networks with Mobility-Induced Variability, Digital Communications and Networks, 2025
[6] Deep Reinforcement Learning for Privacy-Preserving Task Offloading in Integrated Satellite-Terrestrial Networks, IEEE Transactions on Mobile Computing, 2024
[7] Model Parameter Prediction Method for Accelerating Distributed DNN Training, Computer Networks, 2024
[8] Privacy Preserving Federated Learning for Full Heterogeneity, ISA Transactions, 2023
l AI security & privacy computing (e.g., machine unlearning, data/model attack and defense, etc.)
[9] Optimizing Federated Incremental Learning: Efficient Malicious Data Removal for Big Data Analytics, Tsinghua Science and Technology, to appear
[10] Accurate and Fast Machine Unlearning through Hessian-Guided Modeling and Overfitting Parameter Approximation, Neurocomputing, to appear
[11] Towards Structural Transformation-based Attack for Boosting Transferability of Adversarial Examples, Pattern Recognition, 2026
[12] Harnessing Transferable Adversarial Examples via Multi-layer Attention-guided Spatial Transformations, IEEE Transactions on Reliability, 2026
[13] Differential Private Data Stream Analytics in the Local and Shuffle Models, IEEE Transactions on Mobile Computing, 2025
[14] Fast Yet Versatile Machine Unlearning for Deep Neural Networks, Neural Networks, 2025
[15] Towards Adversarial Patch Attacks on Deep Crowd-Counting Networks via Density-aware Normalized Feature Learning, Knowledge-Based Systems, 2025
[16] Locally Private Set-valued Data Analyses: Distribution and Heavy Hitters Estimation, IEEE Transactions on Mobile Computing, 2024
[17] Model Architecture Level Privacy Leakage in Neural Networks. Science China Information Sciences, 2024
[18] Privacy Preserving Machine Unlearning for Smart Cities, Annals of Telecommunications, 2024
[19] Stealthy and Flexible Trojan in Deep Learning Framework, IEEE Transactions on Dependable and Secure Computing, 2023
[20] Shuffle Differential Private Data Aggregation for Random Population, IEEE Transactions on Parallel and Distributed Systems, 2023
[21] Revisiting the Transferability of Adversarial Examples via Source-agnostic Adversarial Feature Inducing Method, Pattern Recognition, 2023
[22] Towards Evaluating the Robustness of Deep Neural Semantic Segmentation Networks with Feature-Guided Method, Knowledge-Based Systems, 2023
[23] Backdoor Attacks against Distributed Swarm Learning, ISA Transactions, 2023
[24] Similarity-based Integrity Protection for Deep Learning Systems, Information Sciences, 2022
[25] N-gram MalGAN: Evading Machine Learning Detection via Feature N-gram. Digital Communications and Networks, 2022
[26] Optimal Locally Private Data Stream Analytics, IEEE INFOCOM, 2024
l Data trading & blockchain
[27] Distributed Edge Artificial Intelligence Empowered Data Trading: Theories, Algorithms, and Applications, Computer Science Review, 2026
[28] Privacy-preserving and Efficient Data Sharing for Blockchain-based Intelligent Transportation Systems, Information Sciences, 2023
[29] Hieraledger: Towards Malicious Gateways in Hierarchical Appendable-Block Blockchain Constructions for IoT, Information Sciences, 2023
l Internet of Things & mobile computing (e.g., wireless sensing, sensor networks, embedded systems, etc.)
[30] A Robust Underwater Object Tracking Model with Cross-Modal Selective Joint Representation and Relationship Enhancement of Text and Visual Features, Expert Systems with Applications, 2026
[31] SatProbe: Low-Energy and Fast Indoor/Outdoor Detection via Satellite Existence Sensing. IEEE Transactions on Mobile Computing, 2021
[32] Modeling and Improving the Energy Performance of GPS Receivers for Location Services. IEEE Sensors Journal, 2020
[33] BikeGPS: Localizing Shared Bikes in Street Canyons with Low-Level GPS Cooperation. ACM Transactions on Sensor Networks, 2019
[34] Slide: Towards Fast and Accurate Mobile Fingerprinting for WiFi Indoor Positioning Systems. IEEE Sensors Journal, 2018
[35] LIPS: A Light Intensity Based Positioning System for Indoor Environments. ACM Transactions on Sensor Networks, 2016
[36] CRSM: A Practical Crowdsourcing-based Road Surface Monitoring System. Wireless Networks, 2016
[37] Bumping: A Bump-Aided Inertial Navigation Method for Indoor Vehicles Using Smartphones. IEEE Transactions on Parallel and Distributed Systems, 2014
[38] BikeGPS: Accurate Localization of Shared Bikes in Street Canyons via Low-Level GPS Cooperation. ACM MobiSys,2018
[39] SatProbe: Low-Energy and Fast Indoor/Outdoor Detection based on Raw GPS Processing. In IEEE INFOCOM, 2017