I'm Chao Zhao, I am an Associate Professor at the School of Mechanical Engineering and Automation, Northeastern University, China. I earned my Ph.D. in March 2025 from Huazhong University of Science and Technology, under the supervision of Prof. Weiming Shen. During my Ph.D., I was also a visiting scholar at Politecnico di Milano, Italy, under the guidance of Prof. Enrico Zio.
大家好，我是赵超，目前在东北大学（中国沈阳）机械工程与自动化学院任副教授。欢迎对智能制造和运维感兴趣的同学加入我的课题组！
📌 课题组现招收硕士研究生（2025年9月入学） 📌 欢迎本科生提前参与科研实践
本课题组注重平等交流、沟通融治，并与以下单位保持紧密合作：
- 华中科技大学 机械学院
- 米兰理工大学 能源系
- 福耀科技大学 等国内外高校
我们将为学生提供联合培养、科研合作与企业交流的机会。
我的论文发表：
If you're interested in any of the following areas, feel free to reach out via email — I’m always open to potential collaborations:
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Data-Model Hybrid Driven Intelligent Monitoring & Maintenance for Advanced Equipment （数模混合驱动的高端装备智能监测与运维）
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Application of Foundation Models in Smart Manufacturing （ 工业大模型在智能制造中的应用）
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Industrial Big Data Governance and Mining （ 工业大数据治理与挖掘）
Feel free to reach out to me via email: zhaochao0612@gmail.com
Here are my repositories related to my review paper:
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DG-PHM: This is a repository about Domain Generalization for PHM, including papers, code, datasets etc（基于领域泛化的故障预测与健康管理）.
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DGFD-Benchmark: This is a benckmark for domain generalization-based fault diagnosis（基于领域泛化的故障诊断基准实验）.
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LLM-PHM: This is a reposotory that includes paper about LLM-based fault diagnosis and prognosis（基于大模型的故障预测与健康管理）.
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Multimodal-PHM: This repository contains papers, code, and datasets related to multi-modal-based fault diagnosis（基于多模态数据的智能故障诊断）.
Some of my repositories related to research paper:
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AOSDGN: Adaptive open set domain generalization network: Learning to diagnose unknown faults under unknown working conditions. 任务：开集领域泛化故障诊断
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SDAGN: Imbalanced domain generalization via Semantic-Discriminative augmentation for intelligent fault diagnosis.任务：不平衡领域泛化故障诊断
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BWAN: A-balanced-and-weighted-alignment-network-for-partial-transfer-fault-diagnosis.任务：部分领域适应故障诊断
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MSDGN: Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions.任务：半监督领域泛化故障诊断
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FDDG: A federated distillation domain generalization framework for machinery fault diagnosis with data privacy.任务：联邦领域泛化故障诊断
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FedDGMC: Federated Domain Generalization: A Secure and Robust Framework for Intelligent Fault Diagnosis.任务：联邦领域泛化故障诊断
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DAN: Dual adversarial network for cross-domain open set fault diagnosis.任务：开集域适应故障诊断
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DGNIS: A domain generalization network combing invariance and specificity towards real-time intelligent fault diagnosis.任务：领域泛化故障诊断
Check out some of HUST datasets other datasets:
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HUSTbearing-dataset: This reposotory release a bearing failure dataset, which can support intelliegnt fault diagnosis research. 轴承数据集
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HUSTgearbox-dataset: This reposotory release a gearbox failure dataset, which can support intelliegnt fault diagnosis research. 齿轮数据集
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HUSTmotormultimodal-dataset:This repository has open-sourced a dataset of motor failure, including vibration signals and audio signals.多模态电机数据集
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HUSTTransmissionsystem-dataset: This reposotory release a Transmission system failure dataset. 传动系统数据集
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Opensource datasets: About An open-source mechanical failure dataset is available, comprising 30+ categories including bearings, gears, pumps, and others. 其他开源数据集
Here are some of the repositories that are related to personal summary of research:
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The-Ph.D.-journey-scenery: Collected a number of doctoral problems encountered and related information. 博士期间摘录的他人的干货
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Tips-for-Young-University-Teachers: The thinking transformation route of young teachers.观看B站Up主[老司机耿进财]的系列视频摘录的笔记-针对青年教师思维转变