Eunjeong Jeong

What does not kill me makes me stronger.

About me

Hi! I’m Eunjeong JEONG (pronoun: she/her). I am a postdoctoral researcher at Linköping University in the Department of Computer and Information Science, working with Nikolaos Pappas. My research interests include semantic communications and energy-efficient distributed learning.

I obtained a Ph.D. in communication systems at EURECOM in Sophia-Antipolis, France, where Marios Kountouris was my advisor. I studied decentralized (=serverless) federated learning for communication efficiency during the doctoral program.

Before moving to France, I was at the School of Electrical and Electronic Engineering at Yonsei University in Seoul, South Korea. Seong-Lyun Kim was my advisor during the master's program.

For more information, please check out my CV.

Selected Publications

E. Jeong and M. Kountouris, “DRACO: decentralized asynchronous federated learning over row-stochastic wireless networks,” in IEEE Open Journal of the Communications Society, vol. 6, pp. 4818-4839, 2025, doi: 10.1109/OJCOMS.2025.3574098.
E. Jeong and N. Pappas, "Computation-aware Energy-harvesting Federated Learning: Cyclic Scheduling with Selective Participation," submitted to a peer-reviewed journal, 2025.
E. Jeong, G. Perin, H. H. Yang, and N. Pappas, "Feature-Based Semantics-Aware Scheduling for Energy-Harvesting Federated Learning," to be presented at IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN), 2026.
G. Perin, E. Jeong, and N. Pappas, "Federated Learning Meets Random Access: Energy-Efficient Uplink Resource Allocation," to be presented in Workshop on Sustainable and Sustainability-Enabling 6G at IEEE International Conference on Communications (ICC), 2026.
G. Smpokos, E. Jeong, and N. Pappas, “Geofencing for privacy and security in federated learning over wireless channels”, submitted to IEEE International Workshop on Signal Processing and Artificial Intelligence for Wireless Communications (SPAWC), 2026.
E. Jeong*, S. Oh*, H. Kim, J. Park, M. Bennis, and S. -L. Kim, “Communication-efficient on-device machine learning: federated distillation and augmentation under non-IID private data,” presented at NeurIPS Workshop on Machine Learning on the Phone and other Consumer Devices (MLPCD), Montréal, Canada, Dec 2018.

*: Equal contribution.

More works are available on my Google Scholar profile.

Research Projects

ROBUST-6G (Horizon Europe/JU SNS project; Grant Agreement no. 101139068)
- Pursuit: development of data-driven, AI/ML-based security solutions for 6G networks.
- Enhanced sustainability by leveraging semantics-aware communication with quantification of information significance
MAGIC-6G (Horizon Europe/JU SNS project; Grant Agreement no. TBA)
- Pioneering Goal-oriented Networking (GoN) framework for 6G communication systems leveraging semantic representations and AI-native orchestration.
- Semantics-aware scheduling and energy-efficient communication policies for sustainable and safe goal-oriented networking

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