MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks
TL;DR Peer review catches unreliable agent outputs, while longer-term monitoring guides exclusion and recovery.
Reinforcement learning · Language models
I am a PhD student in Electrical Engineering at Arizona State University, advised by Prof. Shaofeng Zou. I also work closely with Prof. Sen Lin and Prof. Yingbin Liang. Previously, I received my B.Eng. in Automation from Xi’an Jiaotong University.
I am interested in reinforcement learning, LLM post-training, and AI agents (including multi-agent systems), with a focus on safety, alignment, and decision-making under constraints. I am also interested in applications of these methods to healthcare.
TL;DR Peer review catches unreliable agent outputs, while longer-term monitoring guides exclusion and recovery.
Main Conference · Also at ICML 2026 DEMO Workshop
TL;DR Direct online exploration toward the uncertainty that remains after learning from offline data.
Main Conference
TL;DR Train language models to help users while treating system-instruction compliance as an explicit constraint.
TL;DR Align value estimates and adapt constraint penalties to safely fine-tune offline policies online.
13(4), 324
TL;DR A review of computational microscopy, from image reconstruction to digital pathology and deep learning.
PhD in Electrical Engineering · Advisor: Shaofeng Zou
B.Eng. in Automation
NeurIPS 2026 ICLR 2027 Scientific Reports IEEE/ACM Transactions on Networking
Away from my desk, I like to photograph landscapes, cities, and the night sky.
A few recent favorites. Click a photograph to take a closer look.