New TCOM paper accepted!

Our paper “Compressed Training for Dual-Wideband Time-Varying Sub-Terahertz Massive MIMO,” coauthored with my former Ph.D. student Tzu-Hsuan Chou and colleagues at Purdue University, David J. Love and James V. Krogmeier, has been accepted on the […]

New TCCN paper accepted!

Our paper “MAESTRO-X: Distributed Orchestration of Rotary-Wing UAV-Relay Swarms,” co-authored with Ph.D. students Bharath Keshavamurthy (ASU) and Matt Bliss (Purdue Univerisity) has been accepted on the IEEE Transactions on Cognitive Communications and Networking! Congratulations Bharath […]

Tzu-Hsuan successfully defended his thesis!

Tzu-Hsuan Chou (Purdue University) successfully defended his Ph.D. thesis “Channel Training and Signal Processing for massive MIMO Wireless Communications.” Congratulations Tzu-Hsuan!

New TIT paper accepted!

Our paper “Finite-Bit Quantization For Distributed Algorithms With Linear Convergence” has been accepted for publication at the IEEE Transactions on Information Theory! Co-authored with Gesualdo Scutari and Chang-Shen Lee. This paper studies distributed algorithms for […]

New TON paper accepted

Our paper “Multi-Stage Hybrid Federated Learning Over Large-Scale D2D-Enabled Fog Networks” has been accepted for publication at the IEEE/ACM Transactions on Networking! Authors: Seyyedali Hosseinalipour, Sheikh Shams Azam, Christopher G. Brinton, Nicolò Michelusi, Vaneet Aggarwal, […]

New TCCN paper accepted!

Our paper “Learning-based Spectrum Sensing in Cognitive Radio Networks via Approximate POMDPs” has been accepted for publication at the IEEE Transactions on Cognitive Communications and Networking! Co-authored by Bharath Keshavamurthy and myself. A novel LEarning-based […]

New JSAC paper accepted!

Our paper “Learning and Adaptation for Millimeter-Wave Beam Tracking and Training: a Dual Timescale Variational Framework ” has been accepted for publication at the IEEE JSAC special issue on Machine Learning in Communications and Networks! Co-authored […]

New JSAC paper accepted!

Our paper “Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations” has been accepted for publication at the IEEE JSAC special issue on Distributed Learning over Wireless Edge Networks! Co-authored by Frank Po-Chen Lin, Seyyedali Hosseinalipour, […]