Christopher G. Brinton
Computer Science · Purdue University West Lafayette
Publications
310
Citations
3,279
Est. group size
~21
Recurring co-author estimate
Active years
17
Publishing since 2010
Christopher G. Brinton works on distributed and communication-efficient machine learning systems, especially federated learning, split learning, and large language model inference across mobile and wireless networks. His research also touches wireless communications topics like MIMO channel modeling and over-the-air distributed learning, often combining networking constraints with machine learning optimization. This work is generally aimed at making AI systems more efficient, robust, and privacy-preserving when deployed on distributed or edge devices.
Publication output grew substantially from 2017 through a peak around 2023, and has remained high (averaging about 43 papers/year over the last five years) with a slight decline in the most recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Decentralized Domain Generalization with Style Sharing: Formal Model and Convergence Analysis
2026
- Coherence-Aware Over-the-Air Distributed Learning under Heterogeneous Link Impairments
Open MIND · 2026
- Coherence-Aware Over-the-Air Distributed Learning Under Heterogeneous Link Impairments
IEEE Journal on Selected Areas in Information Theory · 2026
- Unlocking Realism and Interpretability in Wireless Channel Synthesis: A Physics-Guided Generative Approach
arXiv (Cornell University) · 2026
- Unlocking Realism and Interpretability in Wireless Channel Synthesis: A Physics-Guided Generative Approach
arXiv (Cornell University) · 2026
- Device-Cloud Collaborative LLM Inference with Multi-Modal, Multi-Task, Multi-Turn Conversations
IEEE Transactions on Networking · 2026
- Mitigating Evasion Attacks in Federated Learning Based Signal Classifiers
IEEE Transactions on Network Science and Engineering · 2025
- Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
IEEE Transactions on Neural Networks and Learning Systems · 2025
- Graph Neural Networks for the Optimization of Collaborative Federated Learning Energy Efficiency
IEEE Transactions on Mobile Computing · 2025
- LLMAP: LLM-Assisted Multi-Objective Route Planning with User Preferences
2025
- Serving Long-Context LLMs at the Mobile Edge: Test-Time Reinforcement Learning-based Model Caching and Inference Offloading
arXiv (Cornell University) · 2025
- Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings
2025
- Device-Cloud Collaborative LLM Inference with Multi-Modal, Multi-Task, Multi-Turn Conversations
arXiv (Cornell University) · 2025
- Joint Spatio-Temporal Feature Extraction for Channel State Prediction in MIMO Systems
2025
- Communication-Efficient Cooperative Localization: A Graph Neural Network Approach
2025
- arXiv (Cornell University)×117
- IEEE/ACM Transactions on Networking×9
- IEEE Journal on Selected Areas in Communications×7
- IEEE Transactions on Cognitive Communications and Networking×6
- IEEE Internet of Things Journal×5
- Wenzhi Fang
Computer Science · Purdue University West Lafayette
- Rohit Parasnis
Computer Science · Purdue University West Lafayette
- Dong-Jun Han
Computer Science · Purdue University West Lafayette
- Feijie Wu
Computer Science · Purdue University West Lafayette
- Sai Aparna Aketi
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile