Christopher G. Brinton, PhD

For an exhaustive list of publications, see my CV.

Books

• C. Brinton, M. Chiang. The Power of Networks: Six Principles That Connect Our Lives. Princeton University Press, Jan. 2017.
• C. Brinton, M. Chiang. Networks Illustrated: 8 Principles Without Calculus. EdWiser Scholastic Press, June 2013.

10 Representative Papers

• S. Zehtabi, D. Han, R. Parasnis, S. Hosseinalipour, C. Brinton. Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees. International Conference on Learning Representations (ICLR), p. 1-70, 2025. (ICLR 2025 spotlight paper)
• W. Fang, D. Han, E. Chen, S. Wang, C. Brinton. Hierarchical Federated Learning with Multi-Timescale Gradient Correction. Conference on Neural Information Processing Systems (NeurIPS), p. 1-35, 2024.
• J. Kim, T. Kim, D. Love, C. Brinton. Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning. International Conference on Machine Learning (ICML), p. 1-20, 2023.
• R. Sahay, M. Zhang, D. Love, C. Brinton. Defending Adversarial Attacks on Deep Learning Based Power Allocation in Massive MIMO Using Denoising Autoencoders. IEEE Transactions on Cognitive Communications and Networking, Vol. 9, No. 4, p. 913-926, 2023.
• J. Kim, T. Kim, M. Hashemi, D. Love, C. Brinton. Minimum Overhead Beamforming and Resource Allocation in D2D Edge Networks. IEEE/ACM Transactions on Networking, Vol. 30, No. 4, p. 1454-1468, 2022.
• S. Hosseinalipour, S. Azam, C. Brinton, N. Michelusi, V. Aggarwal, D. Love, H. Dai. Multi-Stage Hybrid Learning over Large-Scale Fog Networks. IEEE/ACM Transactions on Networking, p. 1-40, 2022. (2024 IEEE Communication Society William Bennett Prize)
• F. Lin, S. Hosseinalipour, S. Azam, C. Brinton. N. Michelusi. Semi-Decentralized Federated Learning with Cooperative D2D Local Model Aggregations. IEEE Journal on Selected Areas in Communications, Vol. 39, No. 12, p. 3851-3869, 2021.
• S. Wang, Y. Ruan, Y. Tu, S. Wagle, C. Brinton, C. Joe-Wong. Network-Aware Optimization of Distributed Learning for Fog Computing. IEEE/ACM Transactions on Networking, Vol. 29, No. 5, p. 2019-2032, 2021.
• C. Brinton, S. Buccapatnam, L. Zheng, D. Cao, A. Lan, F. Wong, S. Ha, M. Chiang, H.V. Poor. On the Efficiency of Online Social Learning Networks. IEEE/ACM Transactions on Networking, Vol. 26, No. 5, 2018.
• C. Brinton, S. Buccapatnam, M. Chiang, H.V. Poor. Mining MOOC Clickstreams: Video Watching Behavior versus In-Video Quiz Performance. IEEE Transactions on Signal Processing, Vol. 64, No. 14, Jul. 2016.

10 Recent Papers

• J. Kim, T. Kim, A. Das, S. Hosseinalipour, D. Love, C. Brinton. Coding for Gaussian Two-Way Channels: Linear and Learning-Based Approaches. IEEE/ACM Transactions on Information Theory, 2025.
• S. Wagle, A. Das, D. Love, C. Brinton. Multi-Agent Reinforcement Learning for Graph Discovery in D2D-Enabled Federated Learning. IEEE Journal on Selected Topics in Signal Processing, 2025.
• Y. Chu, D. Han, C. Brinton. Only Send What You Need: Learning to Communicate Efficiently in Federated Multilingual Machine Translation. IEEE Journal on Selected Topics in Signal Processing, 2025.
• W. Fang, D. Han, C. Brinton. Federated Learning over Hierarchical Wireless Networks: Training Latency Minimization via Submodel Partitioning. IEEE Transactions on Audio, Speech, and Language Processing, 2025.
• S. Kang, V. Tripathi, C. Brinton. Timely Trajectory Reconstruction in Finite Buffer Remote Tracking Systems. IEEE International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), 2025.
• G. Lan, D. Han, A. Hashemi, V. Aggarwal, C. Brinton. Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis. International Conference on Learning Representations (ICLR), 2025.
• Y. Chu, D. Han, S. Hosseinalipour, C. Brinton. Unlocking the Potential of Model Calibration in Federated Learning. International Conference on Learning Representations (ICLR), 2025.
• C. Brinton, M. Chiang, K. Kim, D. Love, M. Beesley, M. Repeta, J. Roese, P. Beming, E. Ekudden, C. Li, G. Wu, N. Batra, V. Ziegler, T. Ji, R. Prakash, J. Smee. Key Focus Areas and Enabling Technologies for 6G. IEEE Communications Magazine, 2025.
• M. Shisher, A. Piaseczny, Y. Sun, C. Brinton. Computation and Communication Co-scheduling for Timely Multi-Task Inference at the Wireless Edge. IEEE International Conference on Computer Communications (INFOCOM), 2025.
• Y. Chu, D. Han, S. Hosseinalipour, C. Brinton. Rethinking the Starting Point: Collaborative Pre-Training for Federated Downstream Tasks. Association for the Advancement in Artificial Intelligence (AAAI), 2025.

Patents

• C. Brinton, M. Chiang, S. Ha, W. Ju, R. Rill, J. Walker, E. Tenorio. Systems and Methods to Assist an Instructor of a Course. U.S. Patent #17/029,707. Issued Aug 2022.
• C. Brinton, W. Chen, M. Chiang, S. Ha, R. Rill. System and Method for Automated Course Individualization via Learning Behaviors and Natural Language Processing. U.S. Patent #10,339,822. Issued Jul 2019.