Zheng Chen (Assistant Professor with the Department of Electrical Engineering at Linköping University, Sweden) - Communication systems
Date: - Location: Eurecom
Abstract: Collaborative machine learning (ML) from decentralized data has garnered significant attention in both academia and industry in recent years. Its key characteristic lies in multiple agents/nodes collaboratively training a shared ML model, either through the coordination of a central parameter server or in a fully decentralized manner using peer-to-peer information exchange. However, distributed ML over wireless networks introduces new challenges due to communication resource limitations (such as frequency, time, and space) and channel uncertainty, which can greatly impact learning performance and training latency. In this talk, I will provide an overview of research opportunities in communication-efficient federated learning (FL) over wireless networks. Then, I will present our recent work on scheduling and resource allocation design for wireless FL with asynchronous training and energy-constrained FL with streaming data. The last part of the talk will focus on the effect of medium access control (MAC) protocol and communication topology on the performance of consensus-based decentralized ML systems. Biography: Zheng Chen is an Assistant Professor with the Department of Electrical Engineering at Linköping University, Sweden. She received her Ph.D. degree in 2016 from CentraleSupélec, Université Paris-Saclay, France. She has performed research on various aspects of wireless communication systems, including wireless edge caching, energy harvesting, and massive MIMO. Her current research interests focus on distributed information processing and machine learning over wireless networks. She is the recipient of the 2020 IEEE Communications Society Young Author Best Paper Award. She has served as the Workshop Co-Chair for the IEEE GLOBECOM Workshop on Wireless Communications for Distributed Intelligence in 2021-2023. She is currently an Editor of the IEEE Transactions on Green Communications and Networking.
