Distributed Multi-Hop Traffic Engineering via Stochastic Policy Gradient Reinforcement Learning. - Pinyarash Pinyoanuntapong; Minwoo Lee 001; Pu Wang 001 (GLOBECOM, 2019)

Delay-Optimal Traffic Engineering through Multi-agent Reinforcement Learning. - Pinyarash Pinyoanuntapong; Minwoo Lee 001; Pu Wang 001 (INFOCOM Workshops, 2019)

Towards In-Band Telemetry for Self Driving Wireless Networks. - Prabhu Janakaraj; Pinyarash Pinyoanuntapong; Pu Wang 001; Minwoo Lee 001 (INFOCOM Workshops, 2020)

FedAir: Towards Multi-hop Federated Learning Over-the-Air. - Pinyarash Pinyoanuntapong; Prabhu Janakaraj; Pu Wang 001; Minwoo Lee 001; Chen Chen 001 (SPAWC, 2020)

Sim-to-Real Transfer in Multi-agent Reinforcement Networking for Federated Edge Computing. - Pinyarash Pinyoanuntapong; Tagore Pothuneedi; Ravikumar Balakrishnan; Minwoo Lee 001; Chen Chen 001; Pu Wang 001 (SEC, 2021)

EdgeML: Towards network-accelerated federated learning over wireless edge. - Pinyarash Pinyoanuntapong; Prabhu Janakaraj; Ravikumar Balakrishnan; Minwoo Lee 001; Chen Chen 001; Pu Wang 001 (Comput. Networks, 2022)

Toward Scalable and Robust AIoT via Decentralized Federated Learning. - Pinyarash Pinyoanuntapong; Wesley Houston Huff; Minwoo Lee 001; Chen Chen 001; Pu Wang 001 (IEEE Internet Things Mag., 2022)

Edge vs Cloud: How Do We Balance Cost, Latency, and Quality for Large Language Models Over 5G Networks? - Minsu Kim 003; Pinyarash Pinyoanuntapong; Bong-Ho Kim; Walid Saad; Doru Calin (WCNC, 2025)