Postdoc
Angelo Rodio is a Postdoctoral Researcher at Linköping University, Sweden.
He works on decentralized machine learning with Professor Erik G. Larsson and Associate Professor Zheng Chen.
He received his PhD from Inria, France, in July 2024, working on federated learning.
His publications are available on Google Scholar, and more details can be found on his personal webpage.
Angelo Rodio, Giovanni Neglia, Zheng Chen, Erik G Larsson, 
A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication, FORTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, AAAI-26, VOL 40 NO 30, AAAI Conference on Artificial Intelligence, pp. 25151-25159, ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE (2026) 
https://doi.org/10.1609/aaai.v40i30.39705
Chuan Xu, Caelin Kaplan, Angelo Rodio, Tareq Si Salem, Giovanni Neglia, Federated Learning for Collaborative Inference Systems: The case of early exit networks, Performance evaluation (Print) 171:102538 (2026) https://doi.org/10.1016/j.peva.2025.102538
Daniel Pérez Herrera, Angelo Rodio, Zheng Chen, Erik G. Larsson, Power Allocation for Average Consensus in Wireless Networks with Link Failures, European WIRELESS 2025; 30th European Wireless Conference, pp. 172-177, VDE Verlag GmbH (2026)
Daniel Richards Arputharaj, Charlotte Rodriguez, Angelo Rodio, Giovanni Neglia, Carbon-Aware Client and Time Scheduling for Green Federated Learning, Performance evaluation (Print) 174:102597 (2026) https://doi.org/10.1016/j.peva.2026.102597
Angelo Rodio, Giovanni Neglia, Zheng Chen, Erik G. Larsson, A Unified Convergence Analysis for Semi-Decentralized Learning: Sampled-to-Sampled vs. Sampled-to-All Communication (2025) 
https://arxiv.org/abs/2511.11560